ICES Journal of Marine Science: Journal du Conseil

Cavallo,, Alessandro;Peck, Lloyd, S

doi: 10.1093/icesjms/fsaa070pmid: N/A

Abstract Seasonality of food supply is a major driver of physiological and ecological adaptations of marine zooplankton. High-latitude marine copepods accumulate lipids for maintenance and reproductive maturation during the food-depleted winter period. The relationship between latitude and lipid storage in copepods is well established, but it is influenced by many factors, such as trophic position, sex, and depth distribution. In this study, the influence of latitude and collection depth, trophic level, sex, and the presence or absence of dormancy on the relative amount and composition of lipids stored was assessed by analysing published data. Our analyses confirmed higher lipid contents (expressed as % dry weight) in high-latitude species, and in deep-dwelling tropical copepods compared to shallow-living ones. Contrary to our original hypothesis, carnivorous and herbivorous copepods had similar lipid levels. Copepod species that undergo dormancy had higher levels of wax ester and were more common at polar and temperate latitudes. Lastly, adult male and female copepods did not significantly differ in the amount of lipids they store, suggesting that the portion of male reproductive investment, which may depend on lipid stores, has been underestimated. Taken together, these results both confirm some previously reported trends and refute others. Introduction Copepods are among the most abundant animals on Earth, with some estimates in the order of trillions globally (Humes, 1994). Their ecological importance is due to their trophic position, where they provide a link between their microplanktonic prey species and higher consumers. Copepods make up a major fraction of the diet of fish larvae (Helle, 1994; Turner, 2004; Buckley and Durbin, 2006; Llopiz, 2013; Robert et al., 2014) and planktivorous fish (Dommasnes et al., 2004). In this sense, their role is analogous to that of planktonic protozoans, which link bacterioplankton to metazoan micro- and mesoplankton through “trophic repackaging” (Gifford, 1991). Other copepod predators include chaetognaths (Oresland, 1987), jellyfish (Graham and Kroutil, 2001), baleen whales (Pendleton et al., 2009; Baumgartner et al., 2013), and seabirds (Springer and Roseneau, 1985). Indeed, copepod abundance is a good predictor of the endangered North Atlantic right whale’s distribution (Pendleton et al., 2009; Baumgartner et al., 2013). Copepods also contribute to the biological carbon pump, by both active and passive processes, namely vertical migration and faecal pellet production, respectively [reviewed in Turner (2015)]. Copepods’ input to the biological pump is realized by the utilization of storage lipids at depth, during periods of diapause (Jónasdóttir et al., 2015). Jónasdóttir et al. (2015) quantified the contribution of lipid-replete, diapausing Calanus finmarchicus copepodid V (CV) to carbon export in the North Atlantic (lipid pump), showing that it is of a similar magnitude to passive sinking processes. This contribution is primarily dependent on copepod stocks at depth, respiration rate, and mortality (Jónasdóttir et al., 2015). Therefore, knowledge of the annual lipid accumulation patterns, life cycle, and physiology (in particular, metabolic rate at depth) of seasonally migrating copepods is important for assessing their contribution to the biological pump through active carbon transport. In turn, this could be estimated by integrating information on the intrinsic and extrinsic drivers of lipid storage patterns in marine copepod species other than C. finmarchicus. Seasonality of food supply is a major factor affecting biological processes in polar marine species (Clarke, 1988; Arntz et al., 1994; Peck et al., 2005; Peck, 2018). It is considered a major ecological driver of lipid accumulation in high-latitude herbivorous copepods (Conover and Huntley, 1991; Lee et al., 2006). Furthermore, it has been proposed as the main factor limiting growth in polar waters, not just in copepods (Clarke, 1988; Peck, 2018). Seasonality of predation risk has also been proposed as an underappreciated factor potentially shaping high-latitude copepod life cycles (Kaartvedt, 2000; Varpe, 2012); however, its influence on lipid storage has not been investigated. At high latitudes, phytoplankton blooms provide a relatively short window of opportunity for foraging, during which early developmental stages of copepods typically grow at fast rates (Clarke and Peck, 1991; Søreide et al., 2010). At the onset of autumn/winter, late copepodid stages of herbivorous species typically migrate to the deep layers, where they undergo post-embryonic dormancy (or diapause) until the following spring (Lee et al., 2006). Dormancy is characterized by a termination of feeding activity and a marked decrease in metabolic and growth rates (Baumgartner and Tarrant, 2017). There can be substantial deviation from this generalized life cycle, with some species reproducing multiple times a year during the warmer months (multigeneration life cycle), others only reproducing once per life cycle (annual life cycle), and others needing 2 or more years to complete their life cycle (multiyear cycle, characteristic of some polar herbivorous species), following Conover’s (1988) categorization. Species with a broad geographical distribution also display considerable intraspecific variation in their life cycles and lipid accumulation patterns. For instance, the life-cycle duration of the arctic and subarctic copepod Calanus hyperboreus lasts between 1 and 4 years, depending on the location (Hirche, 1997 and references therein). Lipids are used up over the winter period for maintenance and reproductive maturation (Hirche, 1996; Evanson et al., 2000), and copepods start migrating from shallow depths only when they have stored sufficient lipid reserves (the lipid accumulation window hypothesis: Schmid et al., 2018). Mobilized storage lipids also fuel the activity of lecithotrophic early larval stages (nauplii) (Lee et al., 2006). A distinction should be made between species whose life history is characterized by capital breeding on one end of the continuum, where reproduction is fuelled by stored “capital” (Stephens et al., 2009), such as energetic reserves in the form of lipids, and income breeding on the other end, where reproductive costs are met by day-to-day foraging during the reproductive season (Jönsson and Jonsson, 1997; Stephens et al., 2009). Mathematical modelling evidence predicts that for capital breeders, the “sufficiency” of lipid reserves is dependent on the trade-off between predation risk during the foraging season and the benefit of continued feeding for reproductive maturation and/or maintenance during dormancy, while income breeders would store just enough lipids for maintenance (Varpe and Ejsmond, 2018). For omnivorous and carnivorous species, the adaptive significance of lipid storage is less clear, as their food supplies are expected to be less seasonally variable (Clarke, 1988). Nonetheless, some omnivorous and carnivorous copepods have been shown to store large amounts of lipids (Auel and Hagen, 2005), despite not undergoing dormancy and actively feeding throughout winter. For some opportunistic omnivores, such as Metridia longa, the phytoplankton bloom still represents the period of maximal prey quality and quantity (Båmstedt and Ervik, 1984). Thus, they are believed to store lipid, albeit to a lesser extent than their herbivorous counterparts, to cope with suboptimal foraging conditions during the winter (Båmstedt and Ervik, 1984). It has been hypothesized that seasonality should contribute less to the life cycle of omnivorous and carnivorous species (Clarke, 1988). However, annual variation in the availability of herbivorous copepods in surface waters may in turn impose a resource limitation for carnivorous species preying on them. This is the case for the planktivorous Atlantic herring Clupea harengus, which rapidly increases in body mass (Varpe et al., 2005) and relative lipid content (Stoddard, 1967; McGurk et al., 1980) after a short intensive feeding period in the spring and summer months, when its main prey C. finmarchicus is in surface waters. The two main storage lipid classes in marine copepods are wax ester (WE) and triacylglycerol (TAG). WEs are long-chain esters (C28–C42) of diet-derived fatty acids and de novo synthesized fatty alcohols (Sargent, 1978), while TAGs are triesters of glycerol and three fatty acid chains. Because dietary fatty acids are generally unmodified, they provide a chemical signature of the different prey taxa consumed by copepods (Graeve et al., 1994; Kattner and Hagen, 1995). WEs are the main long-term storage lipids of deep-sea and polar marine copepods, while TAGs make up a lesser proportion of the total storage lipids and fuel short-term metabolic needs (Lee and Barnes, 1975; Lee et al., 2006). The Antarctic calanoid Calanus propinquus represents an exception to this, as it stores mainly high-energy TAGs, containing de novo elongated fatty acids (Hagen et al., 1993; Kattner et al., 1994). The adaptive significance of WE synthesis and storage in most copepod species, as opposed to TAGs, is unclear. According to one hypothesis, WEs could be synthesized more quickly than TAGs (Bauermeister and Sargent, 1979); however, there is no evidence supporting this. TAGs, on the other hand, are utilized preferentially during short-term starvation; however, it is not clear whether this is because they can be catabolized more quickly, as it has been suggested (Lee et al., 2006). Because they are less dense than TAGs (Bauermeister and Sargent, 1979), WEs have been suggested to be important for buoyancy regulation; however, several studies have provided evidence against this hypothesis (see Discussion). The hypothesized key role of seasonality of food supply in shaping polar organisms’ life cycles and growth dynamics (Clarke, 1988) allows the following predictions to be made, concerning lipid accumulation in marine copepods. P1. Total lipid (TL) and WE contents will be higher with increasing latitude (Lee et al., 1971; Clarke and Peck, 1991). P2. Upwelling systems at lower latitudes are also highly seasonal (García‐Reyes and Largier, 2012; Vidal et al., 2017; Walter et al., 2018; Pinochet et al., 2019), and several copepod species inhabiting them undergo ontogenetic vertical migration and/or dormancy in winter (Peterson, 1998). These species store lipids to an extent comparable to that of their high-latitude counterparts (Verheye et al., 1992; Lee et al., 2006). For this reason, we predict that copepods sampled from areas characterized by upwelling will have a higher lipid and WE content than copepods sampled at similar latitudes but from areas not affected by upwelling. P3. Lipid and WE contents will increase with depth of occurrence, particularly in tropical species (Lee and Hirota, 1973). This is driven not only by seasonality of food supply (i.e. seasonal migrators to the deep sea) but also by the general food limitation of deep-sea habitats (Harding, 1974; Smith et al., 2008), which would make lipid storage beneficial for deep-sea copepods (Lee et al., 1971). Although metabolic rate decreases with depth in several taxa (Childress, 1975; Seibel and Drazen, 2007), this does not seem to be the case for copepods (Thuesen et al., 1998). Within-species, however, dormant stages typically have a reduced metabolic rate compared to non-dormant ones (Baumgartner and Tarrant, 2017), allowing a slow utilization of the stored lipids. P4. Lipid content will be highest in herbivorous species and lowest in omnivorous and carnivorous species, as food supplies for herbivorous species are predominantly restricted to the short summer productive season at high latitudes (Clarke, 1988; Clarke and Peck, 1991) or during upwelling events at lower latitudes (Verheye et al., 1992). P5. (A) In species that undergo dormancy, lipid content will be higher than in non-dormant species, due to the adaptive significance of lipid depots to many polar and temperate species for maintenance during dormancy and reproduction during or after dormancy (Hagen and Auel, 2001). Moreover, WE content will also be higher in species undergoing dormancy, given that many of these species are found in high-latitude environments and store large amounts of WEs (Lee et al., 1971). (B) Dormancy will be most prevalent at higher latitudes because of the progressively stronger environmental seasonality. P6. Lipid content may be the same in adult females and males, due to the underappreciated magnitude of spermatophore production costs (Bjærke et al., 2016). Previous laboratory experiments showed that, in some species, spermatophore production is dependent on food availability (Bjærke et al., 2016), which would suggest a limited dependence on stored lipids. However, this is not the case for other species (Burris and Dam, 2015). Studies comparing energetic investment into gametes of male and female copepods are lacking; however, male gametogenic investment is known to be equal to or higher than females’ in some other marine invertebrates (Tyler et al., 2003; Grange et al., 2004). Zooplankton lipid dynamics literature is characterized by a multitude of standalone reports, focused on single or selected few species (see Supplementary Table S1), with some notable exceptions (e.g. Lee et al., 1971; Lee and Hirota, 1973). Despite this, some authors have comprehensively reviewed zooplankton lipid accumulation drivers and features (e.g. Hagen and Auel, 2001; Lee et al., 2006). The present review aims to expand their work by quantitatively analysing published lipid content data for marine copepods, including almost 100 species. We specifically aim to assess whether lipid content data support the aforementioned predictions and to explore how various environmental, ecological, and intrinsic drivers may shape lipid storage and accumulation strategies in marine copepods. Material and methods Data selection On 31 July 2018, a literature search in Web of Science (All Databases) was performed, with the following queries: “copepod* AND (lipid storage OR storage lipid*)” and “zooplankton* AND (lipid storage OR storage lipid*)” (i.e. copepod/zooplankton lipid storage/storage lipids). The results were screened for relevant primary sources, and other references were retrieved from the literature cited in the primary articles. Three copepod lipid content measures were compiled from the published literature: TL as % dry weight, triglyceride/TAG, and WE, both expressed as % TL. In addition, absolute TL content (expressed as µg/individual) was also retrieved from the sources reporting it; however, it was not used in the analysis, as it would be expected to change with body size. Where necessary, data were extracted from plots using WebPlotDigitizer 4.1 (Rohatgi, 2018). Only studies where lipids were extracted by chemical methods (i.e. chloroform/dichloromethane:methanol extraction and chromatography-based lipid class analysis) were included in the analysis, therefore excluding lipid sac area/volume-based estimations of lipid content. A list of lipid isolation and lipid class analysis methods used in the selected primary sources is available in Supplementary Table S6. Furthermore, sources that did not report the developmental stage of the sampled copepods were excluded from the dataset. The following data, when available, were also recorded: collection period, location, depth, and sex of the sampled copepods. Species included were further classified into different “feeding guilds” (herbivorous, omnivorous, or carnivorous), based on published accounts of their feeding behaviour (from gut content analyses, mouth-part morphology-based assessments, feeding experiments, isotope and marker fatty acids/alcohols analyses). Similarly, information on seasonal (post-embryonic) dormancy (i.e. presence or absence of dormancy in the life cycle) was compiled. For the purpose of this review, dormancy was defined as a period spent at depth below the photic zone without feeding. Data analysis For the comparisons among latitudinal zones (P1, see Introduction), feeding guilds (P4), between species undergoing dormancy and those which do not (P5), and between sexes (P6), lipid content measurements of adult females were averaged across studies for each species, without first averaging multiple measurements obtained from the same study (Supplementary Table S2). For species where data were derived from a single source, multiple measurements were averaged for that source where applicable. For the comparison between copepods sampled from upwelling and non-upwelling areas (P2), lipid content measurements of adult females were averaged for each species, but the distinction between upwelling and non-upwelling areas was maintained. Thus, for some species, two average values were present: one for samples collected from upwelling areas and one for samples collected from non-upwelling areas (Supplementary Table S3). Similarly, for the comparison among depth classes (P3), lipid content measurements of adult females were averaged for each species, but the distinction between depth classes was maintained. Thus, some species presented more than one average value, e.g. one for samples collected from epipelagic depths and another for samples collected from mesopelagic depths (Supplementary Table S4; see below for definitions of each depth class). Data were not partitioned based on the collection period (i.e. season), so average values include all available data for any one species, regardless of the time sampling. In all instances, the average measure was either the mean or the median TL/TAG/WE content, depending on whether the distribution of the data was normal or not normal, respectively. Data distribution was assessed by inspecting normal Q–Q plots in R (R Core Team, 2018). The following broad latitudinal categorizations were made: polar (66.5–90°N or S), temperate (23.5–66.5°N or S), and tropical (23.5°N to 23.5°S). Collection depth data in published articles were often reported as ranges. For the purpose of this analysis, depths were therefore categorized as either epipelagic (0–200 m), mesopelagic (201–1000 m), or bathypelagic (1000–4000 m). Because TAG and WE contents were expected to be negatively correlated, a Spearman’s correlation test was performed on the subset of species where data were available for both measures. Adult female lipid content (TL, TAG, and WE) was compared among latitudinal classes, feeding guilds, and between species that undergo dormancy and those that do not. Lipid content (TL, TAG, and WE) of adult female copepods from tropical latitudes was also compared between upwelling vs. non-upwelling areas, and among depth classes. The datasets were restricted to adult females for consistency, mainly because data for adult males were relatively scarce in the literature. Moreover, lipid content was compared between sexes, restricting the analysis to adult stages of species where data for both sexes were available. Lastly, lipid content measures (TL, TAG, and WE) of CV stages were compared among latitudinal zones, feeding guilds, and between species that undergo dormancy and those that do not. One-way Analyses of Variance (ANOVAs) or two-sample t-tests were performed if the assumptions of normal distribution and homoscedasticity were met, whereas Kruskal–Wallis or Wilcoxon signed-rank/rank sum tests were performed when they were not. Such assumptions were assessed by Shapiro and Levene’s tests, respectively, and in some instances, the data were transformed (loge or square root) to achieve normal distribution and/or homoscedasticity. Post hoc tests (Tukey’s test or Dunn’s test with Benjamini–Hochberg correction) were performed where applicable, following ANOVA and Kruskal–Wallis tests, respectively. The relationship between dormancy and latitude (P5 B) was investigated by performing a two-way Chi-square test, scoring each species as either dormant or not, and assigning it to its respective latitudinal zone. A summary of the analyses performed is presented in Table 1. Table 1. Summary of the analyses performed. Analysis . Subset . Number of data sources . Lipid content measure . Sample sizes . Effect . WE and TAG correlation Adult females, species where both WE and TAG data were available 25 TAG and WE (% TL) n = 66 Spearman’s correlation rs = −0.508, p = 1.314 × 10−5 CV, species where both WE and TAG data were available 17 TAG and WE (% TL) n = 21 Spearman’s correlation rs = −0.407, p = 0.067 Latitude Adult females 39 TL (% DW) Polar: n = 16 Temperate: n = 32 Tropical: n = 41 Kruskal–Wallis test Χ2 = 8.661, df = 2, p = 0.013 32 WE (% TL) Polar: n = 13 Temperate: n = 29 Tropical: n = 40 Kruskal-Wallis test Χ2 = 5.531, df = 2, p = 0.063 CV 31 TL (% DW) Polar: n = 12 Temperate: n = 18 Tropical: n = 5 ANOVA F2,32 = 0.108, p = 0.898 25 WE (% TL) Polar: n = 10 Temperate: n = 17 Tropical: n = 4 Kruskal–Wallis test Χ2 = 1.514, df = 2, p = 0.469 Upwelling vs. non- upwelling Tropical species, adult females 6 TL (% DW) Upwelling: n = 27 Non-upwelling: n = 28 ANOVA F1,53 = 0.368, p = 0.547 7 WE (% TL) Upwelling: n = 30 Non-upwelling: n = 25 Kruskal–Wallis test Χ2 = 0.064, df = 1, p = 0.800 Depth Tropical species, adult females 4 TL (% DW) Epipelagic: n = 17 Mesopelagic: n = 28 Bathypelagic: n = 4 ANOVA F2,46 = 3.666, p = 0.033 5 WE (% TL) Epipelagic: n = 18 Mesopelagic: n = 27 Bathypelagic: n = 4 Kruskal–Wallis test Χ2 = 4.833, df = 2, p = 0.089 Tropical species from non-upwelling areas, adult females 2 TL (% DW) Epipelagic: n = 6 Mesopelagic: n = 12 Bathypelagic: n = 2 ANOVA F2,17 = 0.583, p = 0.569 3 WE (% TL) Epipelagic: n = 9 Mesopelagic: n = 12 Bathypelagic: n = 2 ANOVA F2,20 = 1.589, p = 0.229 Feeding guild Adult females 40 TL (% DW) Herbivorous: n = 13 Omnivorous: n = 42 Carnivorous: n = 27 ANOVA F2,79 = 4.201, p = 0.018 33 WE (% TL) Herbivorous: n = 10 Omnivorous: n = 40 Carnivorous: n = 24 ANOVA F2,71 = 4.800, p = 0.011 CV 32 TL (% DW) Herbivorous: n = 10 Omnivorous: n = 16 Carnivorous: n = 7 ANOVA F2,30 = 0.660, p = 0.524 25 WE (% TL) Herbivorous: n = 8 Omnivorous: n = 16 Carnivorous: n = 5 ANOVA F2,26 = 0.973, p = 0.391 Sex Adults, species with data for both sexes 23 TL (% DW) Females: n = 20 Males: n = 20 Paired two-sample t-test t19 = −0.849, p = 0.406 16 WE (% TL) Females: n = 15 Males: n = 15 Wilcoxon singed-rank test V = 25, p = 0.090 Dormancy Adult females 40 TL (% DW) Dormancy present: n = 14 Dormancy absent: n = 49 Two-sample t-test t23.39 = 2.057, p = 0.051 32 WE (% TL) Dormancy present: n = 14 Dormancy absent: n = 42 Wilcoxon rank sum test W = 421.5, p = 0.016 CV 30 TL (% DW) Dormancy present: n = 15 Dormancy absent: n = 17 Two-sample t-test T27.68 = 1.271, p = 0.214 23 WE (% TL) Dormancy present: n = 14 Dormancy absent: n = 15 Wilcoxon rank sum test W = 147, p = 0.070 Relationship between dormancy and latitude Species with information about both dormancy and collection zone 41 N/A Dormancy present: n = 14 Dormancy absent: n = 47 Polar: n = 15 Temperate: n = 24 Tropical: n = 22 Chi-square test Χ22 = 6.592, p = 0.037 Analysis . Subset . Number of data sources . Lipid content measure . Sample sizes . Effect . WE and TAG correlation Adult females, species where both WE and TAG data were available 25 TAG and WE (% TL) n = 66 Spearman’s correlation rs = −0.508, p = 1.314 × 10−5 CV, species where both WE and TAG data were available 17 TAG and WE (% TL) n = 21 Spearman’s correlation rs = −0.407, p = 0.067 Latitude Adult females 39 TL (% DW) Polar: n = 16 Temperate: n = 32 Tropical: n = 41 Kruskal–Wallis test Χ2 = 8.661, df = 2, p = 0.013 32 WE (% TL) Polar: n = 13 Temperate: n = 29 Tropical: n = 40 Kruskal-Wallis test Χ2 = 5.531, df = 2, p = 0.063 CV 31 TL (% DW) Polar: n = 12 Temperate: n = 18 Tropical: n = 5 ANOVA F2,32 = 0.108, p = 0.898 25 WE (% TL) Polar: n = 10 Temperate: n = 17 Tropical: n = 4 Kruskal–Wallis test Χ2 = 1.514, df = 2, p = 0.469 Upwelling vs. non- upwelling Tropical species, adult females 6 TL (% DW) Upwelling: n = 27 Non-upwelling: n = 28 ANOVA F1,53 = 0.368, p = 0.547 7 WE (% TL) Upwelling: n = 30 Non-upwelling: n = 25 Kruskal–Wallis test Χ2 = 0.064, df = 1, p = 0.800 Depth Tropical species, adult females 4 TL (% DW) Epipelagic: n = 17 Mesopelagic: n = 28 Bathypelagic: n = 4 ANOVA F2,46 = 3.666, p = 0.033 5 WE (% TL) Epipelagic: n = 18 Mesopelagic: n = 27 Bathypelagic: n = 4 Kruskal–Wallis test Χ2 = 4.833, df = 2, p = 0.089 Tropical species from non-upwelling areas, adult females 2 TL (% DW) Epipelagic: n = 6 Mesopelagic: n = 12 Bathypelagic: n = 2 ANOVA F2,17 = 0.583, p = 0.569 3 WE (% TL) Epipelagic: n = 9 Mesopelagic: n = 12 Bathypelagic: n = 2 ANOVA F2,20 = 1.589, p = 0.229 Feeding guild Adult females 40 TL (% DW) Herbivorous: n = 13 Omnivorous: n = 42 Carnivorous: n = 27 ANOVA F2,79 = 4.201, p = 0.018 33 WE (% TL) Herbivorous: n = 10 Omnivorous: n = 40 Carnivorous: n = 24 ANOVA F2,71 = 4.800, p = 0.011 CV 32 TL (% DW) Herbivorous: n = 10 Omnivorous: n = 16 Carnivorous: n = 7 ANOVA F2,30 = 0.660, p = 0.524 25 WE (% TL) Herbivorous: n = 8 Omnivorous: n = 16 Carnivorous: n = 5 ANOVA F2,26 = 0.973, p = 0.391 Sex Adults, species with data for both sexes 23 TL (% DW) Females: n = 20 Males: n = 20 Paired two-sample t-test t19 = −0.849, p = 0.406 16 WE (% TL) Females: n = 15 Males: n = 15 Wilcoxon singed-rank test V = 25, p = 0.090 Dormancy Adult females 40 TL (% DW) Dormancy present: n = 14 Dormancy absent: n = 49 Two-sample t-test t23.39 = 2.057, p = 0.051 32 WE (% TL) Dormancy present: n = 14 Dormancy absent: n = 42 Wilcoxon rank sum test W = 421.5, p = 0.016 CV 30 TL (% DW) Dormancy present: n = 15 Dormancy absent: n = 17 Two-sample t-test T27.68 = 1.271, p = 0.214 23 WE (% TL) Dormancy present: n = 14 Dormancy absent: n = 15 Wilcoxon rank sum test W = 147, p = 0.070 Relationship between dormancy and latitude Species with information about both dormancy and collection zone 41 N/A Dormancy present: n = 14 Dormancy absent: n = 47 Polar: n = 15 Temperate: n = 24 Tropical: n = 22 Chi-square test Χ22 = 6.592, p = 0.037 Significant differences or relationships (p < 0.05) highlighted in bold. Sample sizes (n) refer to the number of species in each factor level, except for the upwelling vs. non-upwelling and depth comparisons, where some species had more than one average lipid content measure (e.g. one for samples collected from epipelagic depths and one for samples collected from mesopelagic depths) (see Material and methods). Open in new tab Table 1. Summary of the analyses performed. Analysis . Subset . Number of data sources . Lipid content measure . Sample sizes . Effect . WE and TAG correlation Adult females, species where both WE and TAG data were available 25 TAG and WE (% TL) n = 66 Spearman’s correlation rs = −0.508, p = 1.314 × 10−5 CV, species where both WE and TAG data were available 17 TAG and WE (% TL) n = 21 Spearman’s correlation rs = −0.407, p = 0.067 Latitude Adult females 39 TL (% DW) Polar: n = 16 Temperate: n = 32 Tropical: n = 41 Kruskal–Wallis test Χ2 = 8.661, df = 2, p = 0.013 32 WE (% TL) Polar: n = 13 Temperate: n = 29 Tropical: n = 40 Kruskal-Wallis test Χ2 = 5.531, df = 2, p = 0.063 CV 31 TL (% DW) Polar: n = 12 Temperate: n = 18 Tropical: n = 5 ANOVA F2,32 = 0.108, p = 0.898 25 WE (% TL) Polar: n = 10 Temperate: n = 17 Tropical: n = 4 Kruskal–Wallis test Χ2 = 1.514, df = 2, p = 0.469 Upwelling vs. non- upwelling Tropical species, adult females 6 TL (% DW) Upwelling: n = 27 Non-upwelling: n = 28 ANOVA F1,53 = 0.368, p = 0.547 7 WE (% TL) Upwelling: n = 30 Non-upwelling: n = 25 Kruskal–Wallis test Χ2 = 0.064, df = 1, p = 0.800 Depth Tropical species, adult females 4 TL (% DW) Epipelagic: n = 17 Mesopelagic: n = 28 Bathypelagic: n = 4 ANOVA F2,46 = 3.666, p = 0.033 5 WE (% TL) Epipelagic: n = 18 Mesopelagic: n = 27 Bathypelagic: n = 4 Kruskal–Wallis test Χ2 = 4.833, df = 2, p = 0.089 Tropical species from non-upwelling areas, adult females 2 TL (% DW) Epipelagic: n = 6 Mesopelagic: n = 12 Bathypelagic: n = 2 ANOVA F2,17 = 0.583, p = 0.569 3 WE (% TL) Epipelagic: n = 9 Mesopelagic: n = 12 Bathypelagic: n = 2 ANOVA F2,20 = 1.589, p = 0.229 Feeding guild Adult females 40 TL (% DW) Herbivorous: n = 13 Omnivorous: n = 42 Carnivorous: n = 27 ANOVA F2,79 = 4.201, p = 0.018 33 WE (% TL) Herbivorous: n = 10 Omnivorous: n = 40 Carnivorous: n = 24 ANOVA F2,71 = 4.800, p = 0.011 CV 32 TL (% DW) Herbivorous: n = 10 Omnivorous: n = 16 Carnivorous: n = 7 ANOVA F2,30 = 0.660, p = 0.524 25 WE (% TL) Herbivorous: n = 8 Omnivorous: n = 16 Carnivorous: n = 5 ANOVA F2,26 = 0.973, p = 0.391 Sex Adults, species with data for both sexes 23 TL (% DW) Females: n = 20 Males: n = 20 Paired two-sample t-test t19 = −0.849, p = 0.406 16 WE (% TL) Females: n = 15 Males: n = 15 Wilcoxon singed-rank test V = 25, p = 0.090 Dormancy Adult females 40 TL (% DW) Dormancy present: n = 14 Dormancy absent: n = 49 Two-sample t-test t23.39 = 2.057, p = 0.051 32 WE (% TL) Dormancy present: n = 14 Dormancy absent: n = 42 Wilcoxon rank sum test W = 421.5, p = 0.016 CV 30 TL (% DW) Dormancy present: n = 15 Dormancy absent: n = 17 Two-sample t-test T27.68 = 1.271, p = 0.214 23 WE (% TL) Dormancy present: n = 14 Dormancy absent: n = 15 Wilcoxon rank sum test W = 147, p = 0.070 Relationship between dormancy and latitude Species with information about both dormancy and collection zone 41 N/A Dormancy present: n = 14 Dormancy absent: n = 47 Polar: n = 15 Temperate: n = 24 Tropical: n = 22 Chi-square test Χ22 = 6.592, p = 0.037 Analysis . Subset . Number of data sources . Lipid content measure . Sample sizes . Effect . WE and TAG correlation Adult females, species where both WE and TAG data were available 25 TAG and WE (% TL) n = 66 Spearman’s correlation rs = −0.508, p = 1.314 × 10−5 CV, species where both WE and TAG data were available 17 TAG and WE (% TL) n = 21 Spearman’s correlation rs = −0.407, p = 0.067 Latitude Adult females 39 TL (% DW) Polar: n = 16 Temperate: n = 32 Tropical: n = 41 Kruskal–Wallis test Χ2 = 8.661, df = 2, p = 0.013 32 WE (% TL) Polar: n = 13 Temperate: n = 29 Tropical: n = 40 Kruskal-Wallis test Χ2 = 5.531, df = 2, p = 0.063 CV 31 TL (% DW) Polar: n = 12 Temperate: n = 18 Tropical: n = 5 ANOVA F2,32 = 0.108, p = 0.898 25 WE (% TL) Polar: n = 10 Temperate: n = 17 Tropical: n = 4 Kruskal–Wallis test Χ2 = 1.514, df = 2, p = 0.469 Upwelling vs. non- upwelling Tropical species, adult females 6 TL (% DW) Upwelling: n = 27 Non-upwelling: n = 28 ANOVA F1,53 = 0.368, p = 0.547 7 WE (% TL) Upwelling: n = 30 Non-upwelling: n = 25 Kruskal–Wallis test Χ2 = 0.064, df = 1, p = 0.800 Depth Tropical species, adult females 4 TL (% DW) Epipelagic: n = 17 Mesopelagic: n = 28 Bathypelagic: n = 4 ANOVA F2,46 = 3.666, p = 0.033 5 WE (% TL) Epipelagic: n = 18 Mesopelagic: n = 27 Bathypelagic: n = 4 Kruskal–Wallis test Χ2 = 4.833, df = 2, p = 0.089 Tropical species from non-upwelling areas, adult females 2 TL (% DW) Epipelagic: n = 6 Mesopelagic: n = 12 Bathypelagic: n = 2 ANOVA F2,17 = 0.583, p = 0.569 3 WE (% TL) Epipelagic: n = 9 Mesopelagic: n = 12 Bathypelagic: n = 2 ANOVA F2,20 = 1.589, p = 0.229 Feeding guild Adult females 40 TL (% DW) Herbivorous: n = 13 Omnivorous: n = 42 Carnivorous: n = 27 ANOVA F2,79 = 4.201, p = 0.018 33 WE (% TL) Herbivorous: n = 10 Omnivorous: n = 40 Carnivorous: n = 24 ANOVA F2,71 = 4.800, p = 0.011 CV 32 TL (% DW) Herbivorous: n = 10 Omnivorous: n = 16 Carnivorous: n = 7 ANOVA F2,30 = 0.660, p = 0.524 25 WE (% TL) Herbivorous: n = 8 Omnivorous: n = 16 Carnivorous: n = 5 ANOVA F2,26 = 0.973, p = 0.391 Sex Adults, species with data for both sexes 23 TL (% DW) Females: n = 20 Males: n = 20 Paired two-sample t-test t19 = −0.849, p = 0.406 16 WE (% TL) Females: n = 15 Males: n = 15 Wilcoxon singed-rank test V = 25, p = 0.090 Dormancy Adult females 40 TL (% DW) Dormancy present: n = 14 Dormancy absent: n = 49 Two-sample t-test t23.39 = 2.057, p = 0.051 32 WE (% TL) Dormancy present: n = 14 Dormancy absent: n = 42 Wilcoxon rank sum test W = 421.5, p = 0.016 CV 30 TL (% DW) Dormancy present: n = 15 Dormancy absent: n = 17 Two-sample t-test T27.68 = 1.271, p = 0.214 23 WE (% TL) Dormancy present: n = 14 Dormancy absent: n = 15 Wilcoxon rank sum test W = 147, p = 0.070 Relationship between dormancy and latitude Species with information about both dormancy and collection zone 41 N/A Dormancy present: n = 14 Dormancy absent: n = 47 Polar: n = 15 Temperate: n = 24 Tropical: n = 22 Chi-square test Χ22 = 6.592, p = 0.037 Significant differences or relationships (p < 0.05) highlighted in bold. Sample sizes (n) refer to the number of species in each factor level, except for the upwelling vs. non-upwelling and depth comparisons, where some species had more than one average lipid content measure (e.g. one for samples collected from epipelagic depths and one for samples collected from mesopelagic depths) (see Material and methods). Open in new tab All analyses were performed in R, version 3.5.0 (R Core Team, 2018). Results A dataset of TL, TAG, and WE content measures of 99 species of marine copepods (Supplementary Table S1) was collated from published literature. The data were obtained through database searches yielding a total of 433 sources, of which 40 were selected according to the criteria outlined in Material and methods (Supplementary Table S1). Adult female WE and TAG contents were inversely correlated (Table 1); therefore, only the analyses on TL and WE contents are reported. While WE and TAG contents were not correlated in CV stages (Table 1), the analyses were also limited to TL and WE contents for consistency and ease of comparison. TAG content data are available in Supplementary Tables S1–S4. Copepod lipid content changes with latitude, but not between upwelling and non-upwelling areas Average lipid content values for each species were compared among latitudinal classes representative of where they were collected. Significant differences in TL content of adult females were identified among latitudinal zones (Table 1). In particular, polar copepods had significantly higher TL content than temperate and polar ones (Figure 1a). On the other hand, there were no significant differences in WE contents of adult females among latitudinal zones (Table 1); however, polar copepods also appeared to have the highest WE content (Figure 1b). TL and WE contents of CVs were not significantly different among latitudinal zones (Table 1; Supplementary Figure S1). Figure 1. Open in new tabDownload slide Total lipid content (a) and wax ester content (b) of adult female copepods across latitudinal zones. The boxplots show the medians and interquartile ranges, while the open circle represents an outlier. Significant differences between latitudinal zones (p < 0.05) are denoted with an asterisk, and sample sizes are reported below latitudinal zone names. Data were derived from primary literature listed in Supplementary Table S2. Figure 1. Open in new tabDownload slide Total lipid content (a) and wax ester content (b) of adult female copepods across latitudinal zones. The boxplots show the medians and interquartile ranges, while the open circle represents an outlier. Significant differences between latitudinal zones (p < 0.05) are denoted with an asterisk, and sample sizes are reported below latitudinal zone names. Data were derived from primary literature listed in Supplementary Table S2. Lipid content measures were also compared between copepods collected from upwelling vs. non-upwelling areas at tropical latitudes. There was no significant difference in TL or WE contents of adult female tropical copepods collected from upwelling areas compared to those collected from non-upwelling areas (Table 1; Supplementary Figure S2). Tropical deep-sea copepods have higher lipid content than shallow-living ones The influence of collection depth on tropical copepods’ lipid content was investigated. TL content of adult females was significantly different among depth classes (Table 1), with copepods sampled from the bathypelagic zone having a significantly higher TL content than those sampled from the epipelagic zone (Figure 2a). This was not the case for WEs (Table 1; Figure 2b). The analysis was repeated including only tropical copepods sampled from non-upwelling areas, to minimize the effect of dormancy and ontogenetic vertical migration on copepod lipid storage in upwelling areas. In this subset, there were no significant differences in TL or WE contents among depth classes (Table 1; Supplementary Figure S3). Figure 2. Open in new tabDownload slide Total lipid content (a) and wax ester content (b) of tropical copepods sampled from epipelagic, mesopelagic, and bathypelagic depths. The boxplots show the medians and interquartile ranges, while the open circles represent outliers. Significant differences between feeding guilds (p < 0.05) are denoted with an asterisk, and sample sizes are reported below latitudinal zone names. Data were derived from primary literature listed in Supplementary Table S4. E, epipelagic; M, mesopelagic; B, bathypelagic. Figure 2. Open in new tabDownload slide Total lipid content (a) and wax ester content (b) of tropical copepods sampled from epipelagic, mesopelagic, and bathypelagic depths. The boxplots show the medians and interquartile ranges, while the open circles represent outliers. Significant differences between feeding guilds (p < 0.05) are denoted with an asterisk, and sample sizes are reported below latitudinal zone names. Data were derived from primary literature listed in Supplementary Table S4. E, epipelagic; M, mesopelagic; B, bathypelagic. Carnivorous copepods store more lipids than omnivorous ones To determine whether diet may affect the amount of stored lipid in copepods, lipid content measures were compared among herbivorous, omnivorous, and carnivorous species. TL and WE contents were significantly higher in carnivorous species compared to omnivorous ones (adult female subset, Table 1; Figure 3). The same did not hold true for CVs (Table 1; Supplementary Figure S4). Figure 3. Open in new tabDownload slide Total lipid content (a) and wax ester content (b) of herbivorous, omnivorous, and carnivorous adult female copepods. The boxplots show the medians and interquartile ranges, while the open circles represent outliers. Significant differences between feeding guilds are denoted with one (p < 0.05) or two (p < 0.01) asterisk(s), and sample sizes are reported below feeding guild names. Data were derived from primary literature listed in Supplementary Table S2. Figure 3. Open in new tabDownload slide Total lipid content (a) and wax ester content (b) of herbivorous, omnivorous, and carnivorous adult female copepods. The boxplots show the medians and interquartile ranges, while the open circles represent outliers. Significant differences between feeding guilds are denoted with one (p < 0.05) or two (p < 0.01) asterisk(s), and sample sizes are reported below feeding guild names. Data were derived from primary literature listed in Supplementary Table S2. Copepods undergoing dormancy store more WEs than those that do not Lastly, the effect of dormancy on copepod lipid storage strategies was assessed, by comparing species that undergo dormancy with those that do not. Moreover, the relationship between the occurrence of dormancy and latitude was investigated. While there was no significant difference in TL content between species exhibiting and not exhibiting dormancy (Table 1; Figure 4a), the difference was clearly significant for WE content (Table 1; Figure 4b), which was higher in the former group (Figure 4b). On the other hand, CV copepod TL and WE contents did not vary significantly between species exhibiting or not exhibiting dormancy (Table 1; Supplementary Figure S5). There was a significant relationship between the occurrence of dormancy and latitudinal zone (Table 1). Species exhibiting dormancy were almost entirely restricted to polar and temperate latitudes, with only one tropical species out of 61 undergoing dormancy in its life cycle (Figure 4c). Figure 4. Open in new tabDownload slide Total lipid content (a) and wax ester content (b) of adult female copepods undergoing dormancy in their life cycle vs. non-dormant ones. Number of copepod species undergoing and not undergoing dormancy across latitudinal zones (c). The boxplots show the medians and interquartile ranges, while the open circle represents an outlier. Significant differences (p < 0.05) between non-dormant and dormant species are denoted with an asterisk, and sample sizes are reported below the group names. Data were derived from primary literature listed in Supplementary Table S2. Figure 4. Open in new tabDownload slide Total lipid content (a) and wax ester content (b) of adult female copepods undergoing dormancy in their life cycle vs. non-dormant ones. Number of copepod species undergoing and not undergoing dormancy across latitudinal zones (c). The boxplots show the medians and interquartile ranges, while the open circle represents an outlier. Significant differences (p < 0.05) between non-dormant and dormant species are denoted with an asterisk, and sample sizes are reported below the group names. Data were derived from primary literature listed in Supplementary Table S2. Female and male copepods do not differ in the amount of stored lipids Lipid content measures were also compared between sexes, in species where data were available for both sexes. Adult male and female copepods did not differ significantly in their TL or WE contents (Table 1; Supplementary Figure S6). Discussion The present study aimed to quantitatively assess the influence of environmental, life cycle, and biological factors on lipid accumulation patterns in marine copepods. In particular, six predictions (P1–6, see Introduction) were tested by analysing copepod lipid content data retrieved from the primary literature. Our analyses demonstrated that TL content in copepods increased with latitude (Figure 1) in an expected fashion (P1); however, tropical species sampled from upwelling areas did not store more TL or WE than those from non-upwelling areas, as hypothesized (P2). The results confirmed our initial prediction (P3) that tropical deeper-living copepods would have higher lipid content than shallow-living species (Figure 2a). This was not the case, however, for WEs (Figure 2b). Contrary to expectations (P4), carnivores had higher TL and WE contents than omnivorous species and their TL and WE levels were similar to herbivores’ (Figure 3b). Species exhibiting dormancy had higher WE contents than those that did not (Figure 4b), as expected (P5). Lastly, male and female copepods did not store significantly different amounts of lipids (Supplementary Figure S6), as was expected from P6. These points are dealt with in more detail below. CV stages broadly showed the same lipid accumulation trends as adult females (Supplementary Figures S1, S4, and S5); however, none of the factors analysed (latitude, depth and life cycles including dormancy) had a significant effect on TL or WE contents (Table 1). Given the considerably smaller sample sizes of the CV analyses (Table 1), this is likely a result of lower statistical power compared to the analyses restricted to adult females. Lipid storage data compiled in the present study were uneven across latitudinal regions: north temperate and tropical copepods comprised 72 out of 94 species where data were available (adult females subset, see Supplementary Table S1). Of these, 44 were tropical and 28 were north temperate, which aligns with the trend of relatively high diversity of copepods in tropical regions, that gradually decreases in north temperate and north polar regions, reported by Rombouts et al. (2009). South temperate copepods, however, despite being relatively diverse (Rombouts et al., 2009), only comprised 6 out of 94 species in the present dataset (Supplementary Table S2). This suggests that a sampling bias may be, at least partially, responsible for the latitudinal imbalance of lipid content data available in the literature and highlights a paucity of data and research in the southern hemisphere. Influence of latitude and upwelling on lipid content and composition Polar and temperate copepod species have previously been reported to have higher TL and WE contents than tropical species (Lee et al., 1971; Lee and Hirota, 1973). Hence, TL and WE contents were expected to increase with latitude (P1, see Introduction). The present analysis broadly confirmed this prediction for adult females (Figure 1) but not for CVs (Supplementary Figure S1). Copepods store lipids primarily for overwintering and/or reproduction in seasonal environments (Hagen and Schnack-Schiel, 1996; Varpe et al., 2009; Maps et al., 2014). Indeed, seasonality shapes many aspects of polar and temperate species’ life cycles (Arntz et al., 1994; Peck et al., 2006; Peck, 2018), as exemplified by the high incidence and adaptive value of capital breeding at these latitudes (Varpe et al., 2009). WEs followed the same trend (Figure 1b), which is not surprising, considering that most species primarily use WEs for storage (Supplementary Table S2). In fact, of the species where data were available for TAG and WE contents, only 27 out of 67 primarily stored TAGs, of which 16 were tropical and with low TL levels (mostly <20% of dry mass). Nevenzel (1970) proposed two hypotheses to explain the function of WE accumulation: to aid buoyancy and as an energy reserve. The role of WEs in buoyancy regulation has been the subject of ongoing debate in the scientific literature since then. Evidence from theoretical models and empirical data suggests that accumulation of WEs alone cannot be responsible for prolonged periods of neutral buoyancy at depth (Campbell and Dower, 2003). Instead, Campbell and Dower (2003) proposed that ionic buoyancy regulation may be employed by vertically migrating copepods, as is the case for many other pelagic marine invertebrates (Barnes et al., 2001). Although high haemolymph ammonium concentrations have been recorded in Antarctic copepod species, these do not appear to change with depth (Sartoris et al., 2010) or season (Schründer et al., 2013), suggesting that other factors may be at play. More recently, copepods have been hypothesized to control their buoyancy by modulating WE fatty alcohol saturation level, which would in turn affect the depth at which neutral buoyancy is achieved (Pond, 2012). If this was the case, there would be a clear advantage in storing WEs over TAGs, perhaps explaining the high incidence of WE as the main storage lipid in copepods (Pond, 2012), and the prevalence of WEs at high latitudes (Figure 1b). However, WEs are also major constituents of many non-diapausing tropical copepods’ storage lipids (e.g. Paraeuchaeta spp., Gaussia princeps, Megacalanus princeps, Gaetanus pileatus, see Supplementary Table S2), raising questions on whether the adaptive significance of this lipid class in these species is in fact related to buoyancy. In contrast to WEs, TAGs are believed to provide for short-term energy needs in most copepods and they are preferentially utilized during starvation (Lee and Barnes, 1975; Mauchline, 1998; Lee et al., 2006). However, there are exceptions, i.e. species that use TAGs as storage lipids (e.g. Calanus propinquus, Euchirella rostromagna, Paralabidocera antarctica, see Supplementary Table S2). In particular, Calanus simillimus, Eucalanus bungii and Eucalanus californicus not only primarily store TAGs but also undergo dormancy at depth (Supplementary Table S2). Considering the relatively minor contribution of WEs to their TL content, it is likely that these species do not rely on WEs for buoyancy regulation (see above). The molecular and physiological mechanisms underpinning preferential TAG utilization during short-term starvation are largely unknown. The evolutionarily conserved 3-hydroxyacyl-CoA dehydrogenase enzyme is central to fatty acid β-oxidation, and its activity is often used as a general biomarker for lipid catabolism (Hassett, 2006; Freese et al., 2017). However, it is unclear how lipid catabolic pathways are regulated in short-term TAG breakdown as opposed to long-term WE utilization. Tropical copepods in upwelling regions such as the Benguela and Humboldt upwelling systems are characterized by high relative lipid content, comparable to high-latitude species (Lee et al., 2006). Despite this, our analysis showed that copepods sampled in upwelling areas at tropical latitudes did not significantly differ in the amount of TL or WE they accumulated compared to ones sampled in non-upwelling areas (Supplementary Figure S2). It should be noted, however, that this analysis was based on a limited number of sources (Table 1), which presented lipid content data for only a small number of geographical regions, and thus, these data should be interpreted with care. The timing of dormancy and stage succession dynamics of tropical copepods in upwelling areas are not well understood, and the life-cycle information available has been described as “rudimentary” (Peterson, 1998). Lipid content data from a wider range of locations and with a higher temporal resolution will be needed to definitively rule out a difference in lipid accumulation strategies between copepods found in upwelling vs. non-upwelling areas at tropical latitudes. Influence of depth on lipid storage in tropical copepods The intraspecific differences in lipid content between depth zones are well established in ontogenetic migrants (Lee et al., 2006), reflecting a need to store lipids for overwintering at depth. Interspecific differences in lipid content between shallow- and deep-dwelling species have been observed in copepods (Lee et al., 1971) and zooplankton in general (Clarke and Peck, 1991), especially from tropical and subtropical latitudes. These observations are supported by our analysis, as there were a trend of increasing TL and WE contents from the epipelagic zone to the bathypelagic zone (Figure 2) and a significantly higher TL content in copepods collected from bathypelagic vs. epipelagic depths (Figure 2a). There was a large variability in WE content (Figure 2b), with values ranging from 0.1 to 91% of TL (Supplementary Figure S4). In an attempt to reduce this variability, an additional analysis restricted to tropical species collected from non-upwelling areas was performed (Table 1). The differences seen between depth zones were less clear in this subset (Supplementary Figure S3), likely due to the much smaller sample size. It should be noted that, in the vast majority of studies compiled, copepods were collected by vertical hauls to the surface, thus making depth comparisons difficult. Future studies should use higher resolution stratified sampling to facilitate wider scale interspecific comparisons of lipid storage patterns and other traits that may vary with depth of occurrence in copepods. The effect of diet on lipid content and composition Herbivorous copepods from high latitudes rely on a highly seasonal food supply, especially in polar zones, while omnivorous species often stay active during the winter (Graeve et al., 1994; Hagen and Auel, 2001). Likewise, carnivorous species tend to feed all year round (Øresland and Ward, 1993). Winter feeding in omnivorous and carnivorous species translates not only to lower lipid reserves than in herbivorous species (Clarke and Peck, 1991; Graeve et al., 1994; Mauchline, 1998) but also to slower lipid turnover in conditions of high prey abundance (Boissonnot et al., 2016). Whether the slower incorporation of diet-derived lipids into storage depots in omnivorous/carnivorous copepods is caused by fundamentally different physiological mechanisms of lipid utilization between omnivorous/carnivorous species and herbivorous ones is not known. Because omnivorous and carnivorous copepods continue feeding during the winter, it was predicted that they would have lower lipid content than herbivorous species (P4, see Introduction). Surprisingly, in the present analysis, TL and WE contents were not significantly different between herbivorous and carnivorous copepods (Figure 3). On the other hand, carnivorous copepods had significantly higher TL and WE contents than omnivorous species (Figure 3). Lipid-rich carnivorous species are well known, and lipid storage patterns are particularly well documented in Paraeuchaeta spp. (Auel and Hagen, 2005). Despite the fact that Paraeuchaeta spp. seem to continue feeding throughout the winter (Øresland and Ward, 1993), TL levels change seasonally and peak in the summer/autumn in epi-mesopelagic species (Auel and Hagen, 2005) such as P. antarctica (Figure 5). However, this seasonal trend is considerably less pronounced than in some herbivorous species (e.g. Calanoides acutus, see Figure 5). The seasonal trend in TL levels may be driven by suboptimal feeding conditions during the winter; however, the stark ontogenetic pattern of TL accumulation suggests that a large fraction of the stored lipids is invested into eggs and early developmental stages, which do not start feeding until CIII–IV (Auel and Hagen, 2005). If other carnivorous copepods were characterized by a comparably high reproductive investment, this could explain their relatively high TL and WE contents (Figure 3). High lipid content in carnivorous copepods may also be explained by the potential limitation imposed by the seasonal fluctuations in prey abundance, e.g. herbivorous copepod “standing crop” (Clarke, 1988). Nonetheless, the adaptive significance of a high lipid content in carnivorous copepods remains unresolved. Most seasonal studies have focused on diapausing herbivorous species, while carnivorous copepods have been assumed to stay active during the winter and to feed throughout. Future investigations should assess the seasonal patterns of lipid storage, feeding patterns, and depth distribution of carnivorous copepods, with a particular focus on reproductive investment and energy use during winter. Figure 5. Open in new tabDownload slide Seasonal changes in total lipid content of four representative copepod species belonging to different feeding guilds, sampled from the Weddell Sea. Data were derived from primary literature listed in Supplementary Table S5. January–February months correspond to the summer period, while April–May, July–August, and October–November correspond to the early, mid-, and late winter periods. The boxplots show the medians and interquartile ranges, while the open circles represent outliers. A line connecting the medians was added to highlight seasonal changes. For Calanoides acutus, the dormancy period is denoted by the dashed line. Figure 5. Open in new tabDownload slide Seasonal changes in total lipid content of four representative copepod species belonging to different feeding guilds, sampled from the Weddell Sea. Data were derived from primary literature listed in Supplementary Table S5. January–February months correspond to the summer period, while April–May, July–August, and October–November correspond to the early, mid-, and late winter periods. The boxplots show the medians and interquartile ranges, while the open circles represent outliers. A line connecting the medians was added to highlight seasonal changes. For Calanoides acutus, the dormancy period is denoted by the dashed line. A higher lipid content in carnivorous zooplankton would have potential implications for bioaccumulation (and possibly biomagnification) of lipophilic pollutants. Indeed, bioaccumulation potential increases with lipid content (LeBlanc, 1995), which in turn, as shown here, increases with trophic level in copepods. Moreover, bioaccumulation has been shown to be greater for pollutants taken up via feeding than passively through the surrounding water (Magnusson and Tiselius, 2010), although this was not the case for less recalcitrant pollutants such as polycyclic aromatic hydrocarbons (Arias et al., 2016). This suggests that the trophic link between herbivorous and carnivorous copepods would potentially be a prime route for the bioaccumulation of lipophilic compounds. Indeed, field evidence supports this hypothesis, as organic pollutant concentrations in carnivorous zooplankton and ice-associated fauna are higher than in herbivorous species in the Arctic (Borgå et al., 2002; Hallanger et al., 2011). However, laboratory experiments taking into account lipid content and composition of zooplankton are needed to identify the exact mechanisms of bioaccumulation between different trophic levels. The relationship between lipid storage and the occurrence of dormancy in copepods from different latitudinal zones It was predicted that species undergoing dormancy in their life cycles would have a higher lipid content than ones not exhibiting dormancy (P5 A, see Introduction). Our data did not have sufficient temporal resolution to allow differentiation between seasons, but time of sampling is expected to influence lipid content measures, e.g. in the pre- vs. post-dormancy periods. Nonetheless, the present analysis supported our prediction, especially when considering WE content (Figure 4b). Only one tropical species undergoing dormancy was identified: Rhincalanus nasutus in the Red Sea (Schnack-Schiel et al., 2008). Because of vertical mixing effects this species has a highly seasonal food supply (Farstey, 2001). All other species exhibiting dormancy were from polar or temperate latitudes (Figure 4c), and species from these latitudes were significantly more likely to exhibit dormancy in their life cycle (Table 1). In support of our result, a recent modelling study determined food availability (i.e. phytoplankton bloom dynamics) and temperature to be two major factors influencing seasonal vertical migration timing in high-latitude environments (Bandara et al., 2018). In the North Atlantic, phytoplankton blooms initiate later and are shorter with increasing latitude (Friedland et al., 2016). However, a recent analysis of satellite-obtained chlorophyll concentration data collected between 1997 and 2007 reported that the relationship between bloom duration and latitude was not linear (Sapiano et al., 2012). On the contrary, bloom duration was demonstrated to vary zonally rather than latitudinally on a global scale (Sapiano et al., 2012). This could potentially explain the higher number of temperate species undergoing dormancy compared to polar ones (Figure 4c). The relationship between dormancy duration, lipid storage, and latitude (or phytoplankton bloom duration) remains to be determined, especially when comparing temperate and polar species (Figure 4c). Modelling approaches (e.g. Maps et al., 2014; Bandara et al., 2018), coupled with high quality field and satellite data, hold great promise. Lipid storage and reproductive cycles There is a wealth of studies highlighting the relationship between lipid storage and gonad maturation in female copepods (e.g. Hirche and Kattner, 1993; Hagen and Schnack-Schiel, 1996; Hirche, 1996), which have traditionally been thought to invest more energy than males in sexual maturation (Gatten et al., 1980). Male copepods generally have a higher mortality rate than female copepods (Kiørboe, 2006), serving the “brief function” of reproduction (Conover, 1988). In some species, this is due to males having a naturally shorter lifespan than females. For instance, virgin Oithona davisae males live almost half as long as virgin females (Ceballos and Kiørboe, 2011). Many studies investigating changes in gonad mass upon spawning in other marine invertebrates show little or no difference between males and females (Grange et al., 2004, 2007), and some studies reported higher reproductive investment by males than by females, for example in the Antarctic scallop Adamussium colbecki (Tyler et al., 2003). Male reproductive investment in copepods is not well characterized (Titelman et al., 2007), and recent studies suggest that it could be higher than previously thought (Bjærke et al., 2016). In Calanus glacialis and C. finmarchicus, males develop earlier than females and before the phytoplankton bloom, suggesting that their gonad maturation is entirely reliant on lipid stores (Tande and Hopkins, 1981; Kosobokova, 1999). Kosobokova (1999) argued that the production of spermatozoa may be relatively more expensive in energy terms than ova on a unit mass basis, as they contain more energetically costly proteinaceous material. There were no significant differences in lipid content between adults of the two sexes in the present analysis (Supplementary Figure S6), indicating that overall energy cycles are very likely similar and that male reproductive investment, if, dependent on lipid stores, could bear a similar energetic cost to females. However, making general conclusions should only be done with great care, considering that lipid content information for adult males was only available for 22 out of 99 species (Supplementary Table S2). Summary and outlook The present analysis provides support for the well-established trend for higher lipid content with increasing latitude in copepods, confirming Clarke and Peck’s (1991) observed trend for zooplankton in general. This is likely due to the larger effect of seasonality, as lipid-rich diapausing species tend to inhabit polar and temperate basins (Figure 4c). However, the effect of seasonality is modulated by the life cycle and feeding habits of copepods, as exemplified by the seasonal lipid dynamics of four sympatric Antarctic copepods (Figure 5). Carnivorous copepods, unexpectedly, had higher lipid content than omnivorous species, and some species were influenced by seasonality, though to a lesser extent than herbivorous species (see Figure 5). Lipid content was not statistically different between male and female copepods, suggesting that the portion of male reproductive investment that may depend on lipid stores has been underestimated (Bjærke et al., 2016). The results presented here highlight a need for further research in several areas. First, annual field surveys should be conducted to elucidate carnivorous species’ life cycles: their high lipid content cannot be assumed to be constant throughout the year (see Figure 5). In general, field surveys should include depth-stratified sampling, to pinpoint the role of depth in shaping copepods’ lipid storage patterns. Second, male reproductive investment and lipid storage patterns, which have also been neglected in the literature, need to be quantified by field and experimental studies. Third, exact sample sizes (n) for each sample used to determine lipid content or composition should be clearly reported instead of ranges, as this will allow more rigorous analyses of available data. Lastly, our dataset revealed a striking sampling imbalance against south temperate species, despite copepods being very diverse in this region (Rombouts et al., 2009). Thus, there is a compelling need for more field surveys south of the Equator. Supplementary data Supplementary material is available at the ICESJMS online version of the manuscript. Acknowledgements The authors would like to thank Joseph White for collating some lipid content data from the literature in the early stages of the project. We would also like to thank Øystein Varpe and two anonymous reviewers for their comments and suggestions on how to improve the manuscript. Funding AC and LSP were financed by the U.K. Research and Innovation (UKRI) Natural Environment Research Council (NERC) core funds to the British Antarctic Survey. Author contributions AC collated and analysed the data. LSP conceived the study and obtained the funding. AC and LSP interpreted the results and co-wrote the original draft. References Arias A. H. , Souissi A., Roussin M., Ouddane B., Souissi S. 2016 . Bioaccumulation of PAHs in marine zooplankton: an experimental study in the copepod Pseudodiaptomus marinus . Environmental Earth Sciences , 75 : 691 . Google Scholar Crossref Search ADS WorldCat Arntz W. , Brey T., Gallardo V. A. 1994 . Antarctic zoobenthos . Oceanography and Marine Biology , 32 : 241 – 304 . OpenURL Placeholder Text WorldCat Auel H. , Hagen W. 2005 . Body mass and lipid dynamics of Arctic and Antarctic deep-sea copepods (Calanoida, Paraeuchaeta): ontogenetic and seasonal trends . Deep Sea Research Part I: Oceanographic Research Papers , 52 : 1272 – 1283 . Google Scholar Crossref Search ADS WorldCat Båmstedt U. , Ervik A. 1984 . Local variations in size and activity among Calanus finmarchicus an Metridia longa (Copepoda, Calanoida) overwintering on the west coast of Norway . Journal of Plankton Research , 6 : 843 – 857 . Google Scholar Crossref Search ADS WorldCat Bandara K. , Varpe Ø., Ji R., Eiane K. 2018 . A high-resolution modeling study on diel and seasonal vertical migrations of high-latitude copepods . Ecological Modelling , 368 : 357 – 376 . Google Scholar Crossref Search ADS WorldCat Barnes R. S. K. , Calow P. P., Olive P. J. W., Golding D. W., Spicer J. I. 2001 . The invertebrates: a synthesis. Blackwell Science , Malden, MA . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Bauermeister A. , Sargent J. R. 1979 . Wax esters: major metabolites in the marine environment . Trends in Biochemical Sciences , 4 : 209 – 211 . Google Scholar Crossref Search ADS WorldCat Baumgartner M. F. , Lysiak N. S. J., Carter Esch H., Zerbini A. N., Berchok C. L., Clapham P. J. 2013 . Associations between North Pacific right whales and their zooplanktonic prey in the southeastern Bering Sea . Marine Ecology Progress Series , 490 : 267 – 284 . Google Scholar Crossref Search ADS WorldCat Baumgartner M. F. , Tarrant A. M. 2017 . The Physiology and Ecology of Diapause in Marine Copepods . Annual Review of Marine Science , 9 : 387 – 411 . Google Scholar Crossref Search ADS PubMed WorldCat Bjærke O. , Andersen T., Baekkedal K. S., Nordbotten M., Skau L. F., Titelman J. 2016 . Paternal energetic investments in copepods . Limnology and Oceanography , 61 : 508 – 517 . Google Scholar Crossref Search ADS WorldCat Boissonnot L. , Niehoff B., Hagen W., Søreide J. E., Graeve M. 2016 . Lipid turnover reflects life-cycle strategies of small-sized Arctic copepods . Journal of Plankton Research , 38 : 1420 – 1432 . OpenURL Placeholder Text WorldCat Borgå K. , Gabrielsen G. W., Skaare J. U. 2002 . Differences in contamination load between pelagic and sympagic invertebrates in the Arctic marginal ice zone: influence of habitat, diet and geography . Marine Ecology Progress Series , 235 : 157 – 169 . Google Scholar Crossref Search ADS WorldCat Buckley L. J. , Durbin E. G. 2006 . Seasonal and inter-annual trends in the zooplankton prey and growth rate of Atlantic cod (Gadus morhua) and haddock (Melanogrammus aeglefinus) larvae on Georges Bank . Deep Sea Research Part II: Topical Studies in Oceanography , 53 : 2758 – 2770 . Google Scholar Crossref Search ADS WorldCat Burris Z. P. , Dam H. G. 2015 . Spermatophore production as a function of food abundance and age in the calanoid copepods, Acartia tonsa and Acartia hudsonica . Marine Biology , 162 : 841 – 853 . Google Scholar Crossref Search ADS WorldCat Campbell R. W. , Dower J. F. 2003 . Role of lipids in the maintenance of neutral buoyancy by zooplankton . Marine Ecology Progress Series , 263 : 93 – 99 . Google Scholar Crossref Search ADS WorldCat Ceballos S. , Kiørboe T. 2011 . Senescence and sexual selection in a pelagic copepod . PLoS One , 6 : e18870 . Google Scholar Crossref Search ADS PubMed WorldCat Childress J. J. 1975 . The respiratory rates of midwater crustaceans as a function of depth of occurrence and relation to the oxygen minimum layer off Southern California . Comparative Biochemistry and Physiology Part A: Physiology , 50 : 787 – 799 . Google Scholar Crossref Search ADS WorldCat Clarke A. 1988 . Seasonality in the antarctic marine environment . Comparative Biochemistry and Physiology Part B: Comparative Biochemistry , 90 : 461 – 473 . Google Scholar Crossref Search ADS WorldCat Clarke A. , Peck L. S. 1991 . The physiology of polar marine zooplankton . Polar Research , 10 : 355 – 369 . Google Scholar Crossref Search ADS WorldCat Conover R. J. 1988 . Comparative life histories in the genera Calanus and Neocalanus in high latitudes of the northern hemisphere . Hydrobiologia , 167-168 : 127 – 142 . Google Scholar Crossref Search ADS WorldCat Conover R. J. , Huntley M. 1991 . Copepods in ice-covered seas—distribution, adaptations to seasonally limited food, metabolism, growth patterns and life cycle strategies in polar seas . Journal of Marine Systems , 2 : 1 – 41 . Google Scholar Crossref Search ADS WorldCat Dommasnes A. , Melle W., Dalpadado P., Ellertsen B. 2004 . Herring as a major consumer in the Norwegian Sea . ICES Journal of Marine Science , 61 : 739 – 751 . Google Scholar Crossref Search ADS WorldCat Evanson M. , Bornhold E. A., Goldblatt R. H., Harrison P. J., Lewis A. G. 2000 . Temporal variation in body composition and lipid storage of the overwintering, subarctic copepod Neocalanus plumchrus in the Strait of Georgia, British Columbia (Canada) . Marine Ecology Progress Series , 192 : 239 – 247 . Google Scholar Crossref Search ADS WorldCat Farstey V. 2001 . Feeding and vertical distribution of the calanoid copepods Rhincalanus Nasutus Giesbrecht and Pleuromamma Indica Wolfenden in the seasonally mixed water column in the northern part of the Gulf of Aqaba . Hebrew University of Jerusalem, Jerusalem . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Freese D. , Søreide J. E., Graeve M., Niehoff B. 2017 . A year-round study on metabolic enzymes and body composition of the Arctic copepod Calanus glacialis: implications for the timing and intensity of diapause . Marine Biology , 164 : 3 . Google Scholar Crossref Search ADS WorldCat Friedland K. D. , Record N. R., Asch R. G., Kristiansen T., Saba V. S., Drinkwater K. F., Henson S. et al. 2016 . Seasonal phytoplankton blooms in the North Atlantic linked to the overwintering strategies of copepods . Elementa: Science of the Anthropocene , 4 : 99 . OpenURL Placeholder Text WorldCat García‐Reyes M. , Largier J. L. 2012 . Seasonality of coastal upwelling off central and northern California: new insights, including temporal and spatial variability . Journal of Geophysical Research: Oceans , 117 : C03028. OpenURL Placeholder Text WorldCat Gatten R. R. , Sargent J. R., Forsberg T. E. V., O’Hara S. C. M., Corner E. D. S. 1980 . On the nutrition and metabolism of zooplankton XIV. Utilization of lipid by Calanus helgolandicus during maturation and reproduction . Journal of the Marine Biological Association of the United Kingdom , 60 : 391 – 399 . Google Scholar Crossref Search ADS WorldCat Gifford D. J. 1991 . The protozoan-metazoan trophic link in pelagic ecosystems . The Journal of Protozoology , 38 : 81 – 86 . Google Scholar Crossref Search ADS WorldCat Graeve M. , Hagen W., Kattner G. 1994 . Herbivorous or omnivorous? On the significance of lipid compositions as trophic markers in Antarctic copepods . Deep Sea Research Part I: Oceanographic Research Papers , 41 : 915 – 924 . Google Scholar Crossref Search ADS WorldCat Graham W. M. , Kroutil R. M. 2001 . Size-based prey selectivity and dietary shifts in the jellyfish, Aurelia aurita . Journal of Plankton Research , 23 : 67 – 74 . Google Scholar Crossref Search ADS WorldCat Grange L. J. , Tyler P. A., Peck L. S., Cornelius N. 2004 . Long-term interannual cycles of the gametogenic ecology of the Antarctic brittle star Ophionotus victoriae. Marine Ecology Progress Series , 278 : 141 – 155 . Google Scholar Crossref Search ADS WorldCat Grange L. J. , Tyler P. A., Peck L. S. 2007 . Multi-year observations on the gametogenic ecology of the Antarctic seastar Odontaster validus . Marine Biology , 153 : 15 – 23 . Google Scholar Crossref Search ADS WorldCat Hagen W. , Auel H. 2001 . Seasonal adaptations and the role of lipids in oceanic zooplankton . Zoology , 104 : 313 – 326 . Google Scholar Crossref Search ADS PubMed WorldCat Hagen W. , Kattner G., Graeve M. 1993 . Calanoides acutus and Calanus propinquus, Antarctic copepods with different lipid storage modes via wax esters or triacylglycerols . Marine Ecology Progress Series , 97 : 135 – 142 . Google Scholar Crossref Search ADS WorldCat Hagen W. , Schnack-Schiel S. B. 1996 . Seasonal lipid dynamics in dominant Antarctic copepods: energy for overwintering or reproduction? Deep Sea Research Part I: Oceanographic Research Papers , 43 : 139 – 158 . Google Scholar Crossref Search ADS WorldCat Hallanger I. G. , Ruus A., Herzke D., Warner N. A., Evenset A., Heimstad E. S., Gabrielsen G. W., et al. 2011 . Influence of season, location, and feeding strategy on bioaccumulation of halogenated organic contaminants in Arctic marine zooplankton . Environmental Toxicology and Chemistry , 30 : 77 – 87 . Google Scholar Crossref Search ADS PubMed WorldCat Harding G. C. H. 1974 . The Food of Deep-Sea Copepods . Journal of the Marine Biological Association of the United Kingdom , 54 : 141 – 155 . Google Scholar Crossref Search ADS WorldCat Hassett R. P. 2006 . Physiological characteristics of lipid-rich ‘fat’ and lipid-poor ‘thin’ morphotypes of individual Calanus finmarchicus C5 copepodites in nearshore Gulf of Maine . Limnology and Oceanography , 51 : 997 – 1003 . Google Scholar Crossref Search ADS WorldCat Helle K. 1994 . Distribution of early juvenile Arcto-Norwegian cod (Gadus morhua L.) in relation to food abundance and watermass properties. In Cod and climate change - Proceedings of a symposium, pp. 440 – 448 . Ed. by S. Jakobsson, J and Atthorsson, OS and Beverton, RJH and Bjornsson, B and Daan, N and Frank, KT and Meincke, J and Rothschild, B and Sundby, S and Tilseth. Hirche H.-J. , Kattner G. 1993 . Egg production and lipid content of Calanus glacialis in spring: indication of a food-dependent and food-independent reproductive mode . Marine Biology , 117 : 615 – 622 . Google Scholar Crossref Search ADS WorldCat Hirche H.-J. 1996 . Diapause in the marine copepod, Calanus finmarchicus—A review . Ophelia , 44 : 129 – 143 . Google Scholar Crossref Search ADS WorldCat Hirche H.-J. 1997 . Life cycle of the copepod Calanus hyperboreus in the Greenland Sea . Marine Biology , 128 : 607 – 618 . Google Scholar Crossref Search ADS WorldCat Humes A. G. 1994 . How many copepods? Hydrobiologia , 292-293 : 1 – 7 . Google Scholar Crossref Search ADS WorldCat Jónasdóttir S. H. , Visser A. W., Richardson K., Heath M. R. 2015 . Seasonal copepod lipid pump promotes carbon sequestration in the deep North Atlantic. Proceedings of the National Academy of Sciences of the United States of America, 112: 12122 – 12126 . Jönsson K. I. , Jonsson K. I. 1997 . Capital and income breeding as alternative tactics of resource use in reproduction . Oikos , 78 : 57 – 66 . Google Scholar Crossref Search ADS WorldCat Kaartvedt S. 2000 . Life history of Calanus finmarchicus in the Norwegian Sea in relation to planktivorous fish . ICES Journal of Marine Science , 57 : 1819 – 1824 . Google Scholar Crossref Search ADS WorldCat Kattner G. , Graeve M., Hagen W. 1994 . Ontogenetic and seasonal changes in lipid and fatty acid/alcohol compositions of the dominant Antarctic copepods Calanus propinquus, Calanoides acutus and Rhincalanus gigas . Marine Biology , 118 : 637 – 644 . Google Scholar Crossref Search ADS WorldCat Kattner G. , Hagen W. 1995 . Polar herbivorous copepods—different pathways in lipid biosynthesis . ICES Journal of Marine Science , 52 : 329 – 335 . Google Scholar Crossref Search ADS WorldCat Kiørboe T. 2006 . Sex, sex-ratios, and the dynamics of pelagic copepod populations . Oecologia , 148 : 40 – 50 . Google Scholar Crossref Search ADS PubMed WorldCat Kosobokova K. N. 1999 . The reproductive cycle and life history of the Arctic copepod Calanus glacialis in the White Sea . Polar Biology , 22 : 254 – 263 . Google Scholar Crossref Search ADS WorldCat LeBlanc G. A. 1995 . Trophic-level differences in the bioconcentration of chemicals: implications in assessing environmental biomagnification . Environmental Science & Technology , 29 : 154 – 160 . Google Scholar Crossref Search ADS PubMed WorldCat Lee R. F. , Barnes A. T. 1975 . Lipids in the mesopelagic copepod, Gaussia princeps. Wax ester utilization during starvation . Comparative Biochemistry and Physiology Part B: Comparative Biochemistry , 52 : 265 – 268 . Google Scholar Crossref Search ADS WorldCat Lee R. F. , Hirota J., Barnett A. M. 1971 . Distribution and importance of wax esters in marine copepods and other zooplankton . Deep Sea Research and Oceanographic Abstracts , 18 : 1147 – 1165 . Google Scholar Crossref Search ADS WorldCat Lee R. F. , Hirota J. 1973 . Wax esters in tropical zooplankton and nekton and the geographical distribution of esters in marine copepods . Limnology and Oceanography , 18 : 227 – 239 . Google Scholar Crossref Search ADS WorldCat Lee R. F. , Hagen W., Kattner G. 2006 . Lipid storage in marine zooplankton . Marine Ecology Progress Series , 307 : 273 – 306 . Google Scholar Crossref Search ADS WorldCat Llopiz J. K. 2013 . Latitudinal and taxonomic patterns in the feeding ecologies of fish larvae: a literature synthesis . Journal of Marine Systems , 109-110 : 69 – 77 . Google Scholar Crossref Search ADS WorldCat Magnusson K. , Tiselius P. 2010 . The importance of uptake from food for the bioaccumulation of PCB and PBDE in the marine planktonic copepod Acartia clausi . Aquatic Toxicology , 98 : 374 – 380 . Google Scholar Crossref Search ADS PubMed WorldCat Maps F. , Record N. R., Pershing A. J. 2014 . A metabolic approach to dormancy in pelagic copepods helps explaining inter- and intra-specific variability in life-history strategies . Journal of Plankton Research , 36 : 18 – 30 . Google Scholar Crossref Search ADS WorldCat Mauchline J. 1998 . Chemical Composition. In The Biology of Calanoid Copepods , pp. 220 – 252 . Ed. by J. Mauchline. Academic Press, San Diego, CA . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC McGurk M. D. , Green J. M., McKone W. D., Spencer K. and Canada. 1980 . Condition indices, energy density and water and lipid content of Atlantic Herring (Clupea harengus harengus) of southeastern Newfoundland . Department of Fisheries and Oceans , Ottawa . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Nevenzel J. C. 1970 . Occurrence, function and biosynthesis of wax esters in marine organisms . Lipids , 5 : 308 – 319 . Google Scholar Crossref Search ADS PubMed WorldCat Oresland V. 1987 . Feeding of the chaetognaths Sagitta elegans and S. setosa at different seasons in Gullmarsfjorden, Sweden . Marine Ecology Progress Series , 39 : 69 – 79 . Google Scholar Crossref Search ADS WorldCat Øresland V. , Ward P. 1993 . Summer and winter diet of four carnivorous copepod species around South Georgia . Marine Ecology Progress Series , 98 : 73 – 78 . Google Scholar Crossref Search ADS WorldCat Peck L. 2018 . Antarctic marine biodiversity: adaptations, environments and responses to change. In Oceanography and Marine Biology: An Annual Review , pp. 105 – 236 . Ed. by Hawkins S. J., Evans A. J., Dale A. C., Firth L. B., Smith I. P. Taylor and Francis, Boca Raton, FL . Google Scholar Crossref Search ADS Google Scholar Google Preview WorldCat COPAC Peck L. S. , Convey P., Barnes D. K. A. 2005 . Environmental constraints on life histories in Antarctic ecosystems: tempos, timings and predictability . Biological Reviews , 81 : 75 – 109 . Google Scholar Crossref Search ADS PubMed WorldCat Pendleton D. E. , Pershing A. J., Brown M. W., Mayo C. A., Kenney R. D., Record N. R., Cole T. V. N. 2009 . Regional-scale mean copepod concentration indicates relative abundance of North Atlantic right whales . Marine Ecology Progress Series , 378 : 211 – 225 . Google Scholar Crossref Search ADS WorldCat Peterson W. 1998 . Life cycle strategies of copepods in coastal upwelling zones . Journal of Marine Systems , 15 : 313 – 326 . Google Scholar Crossref Search ADS WorldCat Pinochet A. , Garcés-Vargas J., Lara C., Olguín F. 2019 . Seasonal variability of upwelling off Central-Southern Chile . Remote Sensing , 11 : 1737 . Google Scholar Crossref Search ADS WorldCat Pond D. W. 2012 . The physical properties of lipids and their role in controlling the distribution of zooplankton in the oceans . Journal of Plankton Research , 34 : 443 – 453 . Google Scholar Crossref Search ADS WorldCat R Core Team. 2018 . R: a language and environment for statistical computing. R Core Team, Vienna, Austria. Robert D. , Murphy H. M., Jenkins G. P., Fortier L. 2014 . Poor taxonomical knowledge of larval fish prey preference is impeding our ability to assess the existence of a “critical period” driving year-class strength . ICES Journal of Marine Science , 71 : 2042 – 2052 . Google Scholar Crossref Search ADS WorldCat Rohatgi A. 2018 . WebPlotDigitizer, version 4.1. https://automeris.io/WebPlotDigitizer Rombouts I. , Beaugrand G., Ibaňez F., Gasparini S., Chiba S., Legendre L. 2009 . Global latitudinal variations in marine copepod diversity and environmental factors . Proceedings of the Royal Society B: Biological Sciences , 276 : 3053 – 3062 . Google Scholar Crossref Search ADS WorldCat Sapiano M. R. P. , Brown C. W., Schollaert Uz S., Vargas M. 2012 . Establishing a global climatology of marine phytoplankton phenological characteristics . Journal of Geophysical Research: Oceans , 117 : C08026. OpenURL Placeholder Text WorldCat Sargent J. R. 1978 . Marine wax esters . Science Progress , 65 : 437 – 458 . OpenURL Placeholder Text WorldCat Sartoris F. J. , Thomas D. N., Cornils A., Schiela S. B. S. 2010 . Buoyancy and diapause in Antarctic copepods: the role of ammonium accumulation . Limnology and Oceanography , 55 : 1860 – 1864 . Google Scholar Crossref Search ADS WorldCat Schmid M. S. , Maps F., Fortier L. 2018 . Lipid load triggers migration to diapause in Arctic Calanus copepods—insights from underwater imaging . Journal of Plankton Research , 40 : 311 – 325 . Google Scholar Crossref Search ADS WorldCat Schnack-Schiel S. B. , Niehoff B., Hagen W., Bottger-Schnack R., Cornils A., Dowidar M. M., Pasternak A. et al. 2008 . Population dynamics and life strategies of Rhincalanus nasutus (Copepoda) at the onset of the spring bloom in the Gulf of Aqaba (Red Sea) . Journal of Plankton Research , 30 : 655 – 672 . Google Scholar Crossref Search ADS WorldCat Schründer S. , Schnack-Schiel S. B., Auel H., Sartoris F. J. 2013 . Control of diapause by acidic pH and ammonium accumulation in the hemolymph of Antarctic copepods . PLoS One , 8 : e77498 . Google Scholar Crossref Search ADS PubMed WorldCat Seibel B. A. , Drazen J. C. 2007 . The rate of metabolism in marine animals: environmental constraints, ecological demands and energetic opportunities . Philosophical Transactions of the Royal Society B: Biological Sciences , 362 : 2061 – 2078 . Google Scholar Crossref Search ADS WorldCat Smith C. R. , De Leo F. C., Bernardino A. F., Sweetman A. K., Arbizu P. M. 2008 . Abyssal food limitation, ecosystem structure and climate change . Trends in Ecology & Evolution , 23 : 518 – 528 . Google Scholar Crossref Search ADS PubMed WorldCat Søreide J. E. , Leu E., Berge J., Graeve M., Falk-Petersen S. 2010 . Timing of blooms, algal food quality and Calanus glacialis reproduction and growth in a changing Arctic . Global Change Biology , 16 : 3154 – 3163 . OpenURL Placeholder Text WorldCat Springer A. , Roseneau D. 1985 . Copepod-based food webs: auklets and oceanography in the Bering Sea . Marine Ecology Progress Series , 21 : 229 – 237 . Google Scholar Crossref Search ADS WorldCat Stephens P. A. , Boyd I. L., McNamara J. M., Houston A. I. 2009 . Capital breeding and income breeding: their meaning, measurement, and worth . Ecology , 90 : 2057 – 2067 . Google Scholar Crossref Search ADS PubMed WorldCat Stoddard J. H. 1967 . Studies of the condition (fatness) of herring. Biological Station, Fisheries Research Board of Canada, St. Andrews, N.B. Tande K. S. , Hopkins C. C. E. 1981 . Ecological investigations of the zooplankton community of Balsfjorden, northern Norway: the genital system in Calanus finmarchicus and the role of gonad development in overwintering strategy . Marine Biology , 63 : 159 – 164 . Google Scholar Crossref Search ADS WorldCat Thuesen E. V. , Miller C. B., Childress J. J. 1998 . Ecophysiological interpretation of oxygen consumption rates and enzymatic activities of deep-sea copepods . Marine Ecology Progress Series , 168 : 95 – 107 . Google Scholar Crossref Search ADS WorldCat Titelman J. , Varpe Ø., Eliassen S., Fiksen Ø. 2007 . Copepod mating: chance or choice? Journal of Plankton Research , 29 : 1023 – 1030 . Google Scholar Crossref Search ADS WorldCat Turner J. T. 2004 . The importance of small planktonic copepods and their roles in pelagic marine food webs . Zoological Studies , 43 : 255 – 266 . OpenURL Placeholder Text WorldCat Turner J. T. 2015 . Zooplankton fecal pellets, marine snow, phytodetritus and the ocean’s biological pump . Progress in Oceanography , 130 : 205 – 248 . Google Scholar Crossref Search ADS WorldCat Tyler P. A. , Reeves S., Peck L., Clarke A., Powell D. 2003 . Seasonal variation in the gametogenic ecology of the Antarctic scallop Adamussium colbecki . Polar Biology , 26 : 727 – 733 . Google Scholar Crossref Search ADS WorldCat Varpe Ø. , Fiksen Ø., Slotte A. 2005 . Meta-ecosystems and biological energy transport from ocean to coast: the ecological importance of herring migration . Oecologia , 146 : 443 – 451 . Google Scholar Crossref Search ADS PubMed WorldCat Varpe Ø. , Jørgensen C., Tarling G. A., Fiksen Ø. 2009 . The adaptive value of energy storage and capital breeding in seasonal environments . Oikos , 118 : 363 – 370 . Google Scholar Crossref Search ADS WorldCat Varpe Ø. 2012 . Fitness and phenology: annual routines and zooplankton adaptations to seasonal cycles . Journal of Plankton Research , 34 : 267 – 276 . Google Scholar Crossref Search ADS WorldCat Varpe Ø. , Ejsmond M. J. 2018 . Trade-offs between storage and survival affect diapause timing in capital breeders . Evolutionary Ecology , 32 : 623 – 641 . Google Scholar Crossref Search ADS WorldCat Verheye H. M. , Hutchings L., Huggett J. A., Painting S. J. 1992 . Mesozooplankton dynamics in the Benguela ecosystem, with emphasis on the herbivorous copepods . South African Journal of Marine Science , 12 : 561 – 584 . Google Scholar Crossref Search ADS WorldCat Vidal T. , Calado A. J., Moita M. T., Cunha M. R. 2017 . Phytoplankton dynamics in relation to seasonal variability and upwelling and relaxation patterns at the mouth of Ria de Aveiro (West Iberian Margin) over a four-year period . PLoS One , 12 : e0177237 – 25 . Google Scholar Crossref Search ADS PubMed WorldCat Walter R. K. , Armenta K. J., Shearer B., Robbins I., Steinbeck J. 2018 . Coastal upwelling seasonality and variability of temperature and chlorophyll in a small coastal embayment . Continental Shelf Research , 154 : 9 – 18 . Google Scholar Crossref Search ADS WorldCat © International Council for the Exploration of the Sea 2020. All rights reserved. For permissions, please email: [email protected] This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Rühl, Saskia; Thompson, Charlie; Queirós, Ana M; Widdicombe, Stephen

doi: 10.1093/icesjms/fsaa060pmid: N/A

Abstract Exchanges of solutes and solids between the sea floor and water column are a vital component of ecosystem functioning in marine habitats around the globe. This review explores particle and solute exchange processes, the different mechanisms through which they interact at the ecosystem level, as well as their interdependencies. Solute and particle exchange processes are highly dependent on the characteristics of the environment within which they takes place. Exchange is driven directly by a number of factors, such as currents, granulometry, nutrient, and matter inputs, as well as living organisms. In turn, the occurrence of exchanges can influence adjacent environments and organisms. Major gaps in the present knowledge include the temporal and spatial variation in many of the processes driving benthic/pelagic exchange processes and the variability in the relative importance of individual processes caused by this variation. Furthermore, the accurate assessment of some anthropogenic impacts is deemed questionable due to a lack of baseline data and long-term effects of anthropogenic actions are often unknown. It is suggested that future research should be transdisciplinary and at ecosystem level wherever possible and that baseline surveys should be implemented and long-term observatories established to fill the current knowledge gaps. Introduction More than 70% of the Earth’s surface is covered by water. If the water were to be removed, marine sediments would cover more global surface area than all other ecosystems combined (Snelgrove et al., 1999). This marine benthos (sea floor) can have extremely varied geological, physical, and chemical characteristics and supports a diverse range of life forms. It also acts as an important source and sink of energy and matter, which are exchanged with the overlying water (Morris and Howarth, 1998). Thanks to new technologies, tackling formerly inaccessible areas of the ocean, it is now known that the benthos is an important asset of marine ecosystems globally, which is tightly coupled with other marine environments (e.g. Marcus and Boero, 1998; Navarrete et al., 2005). In this review, this connection of benthic and pelagic (water column) environments will be explored by assessing exchange processes between the two. A wide diversity of physically and biologically mediated benthic/pelagic solute and particle exchanges (hereafter “B/P exchanges”) exists. The potential for, and nature and magnitude of, B/P exchanges depends strongly upon the physical characteristics of the sediment, such as its grain size, cohesion, permeability, and porosity (Kalnejais et al., 2010). A sediment bed may be described as cohesive when it contains at least 10–30% clay and/or silt content, particles which are ˂63 µm in grain size; and non-cohesive otherwise (Winterwerp, 2011). Permeable sediment can be defined as having a permeability of ˃ 10−12 m2 (see Huettel et al., 2014). While cohesion mostly affects particle exchange processes, more permeable environments have larger solute exchange potentials. Sediment properties may in turn be modified through physically and biologically mediated sediment mixing and ventilation, thereby passively and actively altering exchange rates (Volkenborn et al., 2010). In many cases, the effects of biological processes are particularly influential in the absence of large-scale physical disturbances (e.g. Widdows et al., 1998a; Andersen and Pejrup, 2002; Paarlberg et al., 2005). For instance, the degree of cohesion and fluidizations of sediments may fundamentally reflect the activity of its biological community (Widdicombe and Austen, 1999). In turn, biological communities are often shaped by their physical and chemical environments as many organisms occupy specific niches (Snelgrove, 1999). In addition to biogenic and physical influences on B/P exchanges, anthropogenic (human) interventions can play an important role. The effects of anthropogenic interaction with the marine environment are often synchronous and can act synergistically, making it difficult to put preventative and counter-active measures in place (Caddy, 2000). Impacts are not only concentrated in coastal shelf areas where anthropogenic activity is prevalent but can be spread further (Martín et al., 2008). For example, the form and extent of effects of bottom trawling on benthic communities are also dependent on the respective sediment types they occur in, which also in themselves affected by this activity (Hiddink et al., 2006; Queirós et al., 2006; Hale et al., 2017). The relative impact of anthropogenic interferences compared to naturally occurring processes on B/P exchanges can thus be hard to quantify, as the two can have similar consequences (Pusceddu et al., 2005) but cause different effects on different types of organisms (e.g. meiofauna: Schratzberger et al., 2009; and macrofauna: Fang et al., 2019). In the course of this review, the complexity of particle and solute B/P exchange processes, as well as particular driver interactions, will be explored. Solute and particle exchanges will be reviewed individually, with solute exchange subsections designed to highlight the main drivers of exchange, and particulate exchange subsections structured to highlight downward and upward directed exchange processes. Interdependencies between solute- and particle-specific processes will be explored using the example of organic matter cycling, which is a biologically vital process that crucially depends on both types of exchange. Knowledge gaps in the current research will be highlighted throughout each section and finally reviewed in combination with recommendations for future research. Solutes Solutes in the marine environment can broadly be defined as substances dissolved in sea water. Throughout the water column, solutes may be transported through eddy and molecular diffusion (Boudreau, 2001), as well as convection (Webster et al., 1996). When biologically important elements such as oxygen (O2), carbon (C), and nitrogen (N) are in solution, they are readily available for processes such as respiration, photosynthesis, calcification, diagenesis, and direct nutrient uptake (all of which will be elaborated upon below), which is why their transport across the pelagic and benthic environments and exchange between the two are essential. O2 is perhaps the most biologically important solute moving across the sediment–water interface. The depth to which O2 penetrates the sediment controls the depth distribution of O2-dependent biogeochemical oxidation reactions, such as nitrification and sulphide oxidation (Rysgaard, 1994), as well as the oxidization of organic matter (OM; Cai and Sayles, 1996). On the whole, the availability of dissolved oxygen in sediment drives aerobic OM degradation rates, a reduction in the concentration of dissolved organic C, and can decrease molecular dissolved OM diversity (Seidel et al., 2015). O2-driven diagenesis (mineralization, dissolution and geo-polymerization during burial; Lindqvist, 2014) is intensified in the presence of marine organisms, which produce enzymes that catalyze those reactions (Lindqvist, 2014). In the absence of biological interactions, the penetration depth of O2 in the sediment has been shown to depend on the O2 concentration in the overlying water (Revsbech et al., 1980; Rasmussen and Jorgensen, 1992). Anthropogenic disturbance, such as trawling, can cause a reduction in dissolved O2 (Tiano et al., 2019). The displacement of the oxygenated sedimentary surface layer through trawling equipment lessens biogenic O2 consumption and causes deeper O2 penetration depths in the affected areas, thereby effectively changing the sedimentary biogeochemical environment (Tiano et al., 2019). Nutrients are another ecologically important solute group in the marine system, as their availability and cycling throughout the environment can be limiting to many organisms (e.g. Howarth, 1988). Intermittence in nutrient concentrations in the water column, and thus at the sediment–water interface, is driven, among other processes, by seasonal changes in temperature (Pomeroy and Deibel, 1986), fluvial and terrestrial input (Justic, 1995; Burnett et al., 2003; Milliman and Farnsworth, 2013), water column mixing, and sea bed resuspension. The latter is often initiated by stochastic storm events (Corte et al., 2017). Temporal patterns of denitrification and nutrient flux dynamics also depend upon the sediment type, as sandy sediments exhibit seasonal changes primarily driven by temperature and irradiation, while silty sediments are additionally influenced by aforementioned stochastic resuspension events (Seidel et al., 2015) and meteorologically induced upwelling events (MacIntyre, 1998). The resulting supply of nutrients from the benthos to the pelagic environment is a crucial factor controlling phytoplankton blooms at times of the year when the water column is not stratified in non-eutrophic systems, as the mixing of water from depth and surface layers can place nutrients from benthic sources within reach of the pelagic organisms (Barnes et al., 2015). This, in turn, fuels zooplankton productivity and can give rise to knock-on effects throughout the entire marine food web (Eloire et al., 2010). Increased pelagic productivity, on the other hand, leads to increased nutrient influx rates to the benthos from sinking OM, which is why the benthic community and its activity typically flourish in response to large seasonal plankton blooms (e.g. Queiros et al., 2015; Tait et al., 2015). Other nutrient sources to benthic sediment–water interactions include atmospheric input (Krishnamurthy et al., 2010), anthropogenic terrestrial sources (Justic, 1995; Burnett et al., 2003), dredge-spoil dumps (e.g. Harvey, Gauthier and Munro, 1998), and the addition of dead cells and faecal pellets from pelagic organisms, sinking onto the sea floor (Van Duyl et al., 1992). The relative impact of each of these depends on factors such as proximity to the coast and the extent of local pelagic primary productivity, and lateral transport fuelled by circulation patterns can alter their relative importance (e.g. Walsh, 1991; Williams and Follows, 1998). Most of the organically available nutrients near the seafloor are extracted and processed diagenetically by the benthic microbial community, or directly consumed by deposit and suspension feeding fauna, degrading and mineralizing the floccules’ contents. The latter can generally be described as the return of nitrogen (N) and phosphorous (P) to inorganic forms after having been incorporated in organic molecules, or (re-)mineralization (Williams and del Giorgio, 2005). Within the sediment, diagenesis is fuelled by the enrichment of the sediment matrix with O2 (Emerson and Hedges, 2003). The B/P exchange of not only O2 and nutrients but also all solutes is governed by a number of direct and indirect drivers (Figure 1), and the current understanding of each in the literature will be detailed throughout this section. Figure 1. Open in new tabDownload slide Flow chart of direct (red, middle) and indirect (blue, right) drivers of solute B/P exchange (green, left); arrows indicate which factors affect others and are colour-coordinated with the driver they originate from. Figure 1. Open in new tabDownload slide Flow chart of direct (red, middle) and indirect (blue, right) drivers of solute B/P exchange (green, left); arrows indicate which factors affect others and are colour-coordinated with the driver they originate from. It is difficult to definitively determine the relative importance of the different driver groups and important factors within each on B/P, as they can be highly variable across spatial and temporal scales. Seasonal variation, for example can cause shifts in the relative importance of biological and physical influences (Howarth et al., 1993; Schlüter et al., 2000); biogenically induced spatial variation in sediment properties can cause differences in the main drivers of solute B/P exchange on both small (Wethey and Woodin, 2005) and large (Fang et al., 2019) spatial scales. This variability constitutes a knowledge gap, which has to be filled on a situational basis, specific to the system, location, and time period of each study within which such processes are investigated. For the purposes of this review, the main drivers of solute B/P exchange are therefore elaborated upon in no particular order. Diffusive flux Water close to the sediment surface within the benthic boundary layer is directly affected by friction at the seabed, which promotes solute transport via diffusion. Cohesive sediments, with high clay content, tend to be more difficult to percolate due to a generally smaller degree of permeability, thus impeding the flux of solutes (Yang and Aplin, 2010; though this is not necessarily true for cohesive environments with low clay content, see, e.g. Winterwerp and Kesteren, 2004). In such conditions, molecular diffusion of pore-water solutes across the sediment–water interface prevails, leading to more gradual solute fluxes (Berner, 1980; Forster et al., 1999) in the form of ion transfer between pore water and near-bottom water or as a result of the reactivity of solid surfaces (Kalnejais, Martin and Bothner, 2010). Other physical environmental variables, such as pressure differentials driven by tides, have been shown to lead to short-term temporal variability of diffusive fluxes (Van Der Kamp and Gale, 1983). The potential depth of diffusive processes is, theoretically, only limited by time. In some cases, however, diffusive distances can be altered, driven, and extended through an increase in sediment permeability, promoted by benthic biological activity. Sedimentary O2 uptake, for instance is only a function of physical penetration depth, which is determined by time in the absence of biological activity and OM (Revsbech et al., 1980). What is hitherto unknown is whether there are ways in which biological or anthropogenic interactions may be directly inhibitive of solute diffusion across the sediment–water interface. As diffusion does not necessarily occur in isolation from other drivers of solute exchange, a differentiation between relative contributions of each driver would be of interest to correctly quantify each pathway. However, while the balance between, for example diffusive and advective solute B/P exchange may be calculated in theory (Anderson and Cherry, 1979; Taigbenu and Liggett, 1986), in situ measurements that take both into account and clearly differentiate between their respective contributions have so far not been successful. Advection and physical resuspension Abiotically driven fluctuations into (and out of) the sediment matrix can also occur through mechanically driven water transfer into and out of the sediment pores. With increasing shear stress and turbulence, benthic boundary layer thickness typically decreases (though there are some exceptions), and with it, the resistance of solute transfers into and out of the sediment (Lohse et al., 1996). This decline continues into the top sediment layers (Ahmerkamp et al., 2017). In turbulent conditions, under strong enough shear stress or in the presence of sediment surface obstacles, solute transport is prevalent through advection and physical resuspension. Obstacles can include protruding solid objects (rocks, shells, etc.), man-made structures, biogenic sediment structures (e.g. polychaete tubes), or simply a three-dimensional bedform, all of which lead to pressure differentials that drive water through the sediment and significantly enhance the exchange of solutes (Huettel and Gust, 1992; Ziebis, Huettel and Forster, 1996; Hutchinson and Webster, 1998). The flushing action from advective processes can winnow smaller particles from the sediment matrix, leading to an overall coarser environment that can be percolated more easily (Malarkey et al., 2015), and the less cohesive and more permeable the seabed is, the more likely is the occurrence of active ejections of solutes into the water column through physically driven advective currents (Lohse et al., 1996; Cook et al., 2007). Resuspension events, driven by either biological activity or abiotic interactions, can enhance solute exchange processes through an increase in the sediment surface area availability for dissolution through the placement of particulates in the water column, re-oxygenation of formerly diagenized elements, and the direct flushing out of interstitial water (Morse, 1994; Morin and Morse, 1999; Saulnier and Mucci, 2000; Kalnejais et al., 2010). Turbulent hydrodynamic forces close to the sea bed thus catalyze the oxygenation of the surface sediment layers through partial resuspension as well as flushing action (Malan and McLachlan, 1991; Couceiro et al., 2013). And B/P solute exchange through physical processes, such as advection and resuspension, further contributes to the breaking down of OM and subsequent supply of biologically important solutes (Franke et al., 2006). In intertidal sandy areas, for example, which typically contain low concentrations of particulate OM due to seasonal hydrodynamic removal (POM; Rusch et al., 2000), pore-water nutrients may be supplemented through advective flushing (Seidel et al., 2015). Clearly, although there is already a large body of literature covering physically driven solute exchange processes, there are still areas requiring further exploration. Temporal variability in advective transport, for instance is poorly understood and has therefore so far not been taken into account in most studies (Cook et al., 2007). As the hydrographic drivers of advection and resuspension may be consistent (e.g. currents), and/or regularly occurring (e.g. tidal flow), and/or stochastic in nature (e.g. storm events), even in situ measurements only capture a snapshot of events, and the potential overlap between time scales impedes our ability to differentiate between them. Long-term monitoring of physically driven B/P solute exchanges may offer a solution to this, though so far this has not been undertaken. The extent to which boundary layer flow dynamics impact physically driven solute B/P exchange has also yet to be definitively quantified, especially in an in situ context, including physical and biological interactions. Bioirrigation and biological particle mixing Biological mediation of solute exchange across the sediment–water interface is constant and inherent to sedimentary life, but in environments in which physically mediated transport is minimal, processes such as faunal flushing of pore waters can determine the rate and characteristics of B/P exchange of solutes (Mermillod-Blondin and Rosenberg, 2006; Volkenborn et al., 2010). In addition, the sediment depth to which solutes are transported biologically can be multiple times that which may be reached through purely physical means (Volkenborn et al., 2010). The biological exchange of solutes can take the form of bioirrigation, the active displacement of liquid and solutes by benthic organisms (Volkenborn et al., 2007) linked to respiration, metabolite excretion, and other individual-based processes; or bio-advection, the induction of additional pore water through burrowing organisms’ physical activity into the surrounding sediment (Volkenborn et al., 2012). Biologically mediated exchange rates strongly depend on the characteristics of the associated faunal and microbial community (see e.g. Waldbusser et al., 2004). Both bioirrigation and bio-advection are at least equally as important as, and often largely exceed, the rates of molecular diffusion in the upper sediment layers of biogenic environments (Berg et al., 2001). The large spatial extent to which the hydraulic forces generated by bioadvectors and bioirrigators propagate through the sediment can lead to effects, which far exceed the immediate vicinity of their burrows (Wethey and Woodin, 2005). This can in some instances have significant effects at the landscape scale (Fang et al., 2019), though more often it leads to small-scale spatial variation with hot spots of altered oxygenation nutrient and carbon concentrations in the immediate vicinity of the bioirrigative activity. The release of O2 from root systems in submerged macrophytes can even create three-dimensional spatial variability in variable diffusion potential and solute distribution (Sand-Jensen et al., 1982). Pore-water O2 content in particular is typically increased through bio-advection (N Volkenborn et al., 2010; Volkenborn et al., 2012) as many burrowing animals actively oxygenate the surrounding sediment by ventilating their burrows with bottom water (Volkenborn et al., 2007). Due to this, the thickness and volume of the sedimentary oxidizing phase are largely extended, thus ameliorating conditions and promoting the occurrence of other aerobic life forms (Mermillod-Blondin and Rosenberg, 2006; Glud, 2008). This can in some cases lead to seasonal variations in O2 availability linked to organisms’ own seasonal life-cycle processes (Glud et al., 2003). Significant variation is also observed between sediment types (Hicks et al., 2017). Through the particle movement and disruption of sediment layering, biogenic particle mixing (bioturbation) strengthens B/P coupling as it increases the fluxes of nutrients, metals, C, O2, and other micro-particles, which would otherwise remain buried (Caliman et al., 2007; Hale et al., 2017). At the local scale, the presence of infaunal bioturbators has been shown to increase natural denitrification rates by at least 160% (Gilbert et al., 1998). Generally, N-mineralization rates are faster in more permeable substrates and may be enhanced by macrofauna influence, irrespective of organic enrichments, due to the O2 enrichment (Hansen and Kristensen, 1998; Huettel et al., 2014). The associated modified supply of nutrients can also strongly affect microbial community structure (Yingst and Rhoads, 1980). This can be traced back to a combination of factors, one of which is the input of macrofaunal metabolic waste products, which provides additional sources of nutrients to microbial communities (e.g. Reichardt, 1988), thereby adding to the overall flux and cycling of solutes, and their bio-catalyzing effects on the microbial community (e.g. Yazdani Foshtomi et al., 2015). The polysaccharide protein lining the burrows of many invertebrates has a filtering effect on the water flushing across and, through it, affects exchange processes by preferentially selecting against anionic solutes due to their own net negative charge (Aller, 1983). Burrowing macrofauna can in some cases actively culture the microbial community associated with their burrows, which then in turn affects the rates and direction of solute exchange within the burrows (Kristensen, 1988). Fishing pressure can passively affect C and nutrient fluxes mediated by benthic macrofauna by altering the community composition, though these effects are mediated by sediment type and the kind of fishing gear deployed (Hale et al., 2017). Changes in benthic community can also be induced through the installation of offshore wind farms (Coates et al., 2014) and other solid substrates or through dredging (e.g. Thrush et al., 1995). Sources of pollution can affect benthic community diversity (e.g. Kingston, 1992) and thereby also passively lower biogenic B/P solute exchange rates. Due to many organisms’ temporally variable behaviours, rates of biologically mediated solute transport can vary on scales of minutes to seasons (e.g. Schlüter et al., 2000). Despite this seasonality being a well-studied phenomenon, there is an important consideration that has thus far not been investigated: The assumption and assessment that in some areas physical pressures are strong enough to drown out the effects of biological processes (as assumed in e.g. Andersen et al., 2002; Paarlberg et al., 2005) may not be true at all times as the balance may swing the other way during biologically active seasons. This is a crucial knowledge gap that warrants further research. Spatial variability too should be considered more often when assessing the relative importance of physical versus biological drivers of B/P exchange, as small-scale patchiness and large-scale B/P exchange budgets may differ. Particles In contrast to solutes, particles are not transported uniformly as they occur in a variety of materials, sizes, shapes, and concentrations. Particle exchange between benthic and pelagic environments may be driven by water flow, occurring regularly (such as through currents or tides); stochastically (such as through storm events and faunal activity); or via direct disturbance of the sea bed through biological activity or anthropogenic interference. Biologically and physically mediated particle transport processes often occur simultaneously and non-independently from one another, on separate or concurrent spatial and temporal scales. Within the sediment, particle reworking occurs mainly through sources of biotic and abiotic mixing rather than resuspension and deposition. The main drivers of exchange between the seabed and the water column can be grouped into upward transport from the benthos to the pelagic environment, in the form of resuspension, and downward transport from the pelagic environment to the benthos through deposition (Figure 2). These two routes include various biological, physical, and anthropogenic pathways, which will be elucidated in this section. Figure 2. Open in new tabDownload slide Flow chart of direct (red, middle) and indirect (blue, right) drivers of particle B/P exchange; arrows indicate which factors affect others and are colour-coordinated with the driver they originate from. Figure 2. Open in new tabDownload slide Flow chart of direct (red, middle) and indirect (blue, right) drivers of particle B/P exchange; arrows indicate which factors affect others and are colour-coordinated with the driver they originate from. As previously mentioned, the relative importance of individual drivers of B/P exchange is context dependent. The occurrence of large phytoplankton blooms (e.g. Zhang et al., 2015) or dredge-spoil dumps (e.g. Moon et al., 1994), for example leads to an abundance of suspended material, the sinking of which is likely to locally dominate particle exchange processes. In storm-heavy seasons, or during the occurrence of extreme stochastic storm events, on the other hand, upward particle fluxes are likely to be dominant (e.g. Madsen et al., 1993). Outside of such extreme events, the relative importance of physical and biological drivers of B/P exchange is dependent on location (e.g. Dellapenna et al., 1998). This situation and location dependence of the relative importance of B/P particle exchange drivers constitutes yet another gap in our knowledge of these processes. Past studies may be used to estimate each driver’s importance to warrant its inclusion in future studies, though this assessment has to be made in each instance, taking into account the scale, location, and timing of the sampling effort, as well as the occurrence of extreme events close to the time of sampling (Hewitt et al., 2007). Because of this complexity, and for the sake of simplicity, these drivers of particle exchange are reviewed subsequently moving focus from the water column and towards the sediment, without necessarily reflecting their relative importance. Downward flux and deposition Throughout the water column, particles stay in suspension when the ascending vertical components of turbulent eddy velocity fluctuation are greater than the corresponding particle settling velocity (Komar, 1976a, b). Physical and chemical barriers in the water column, for instance in the form of haloclines and thermoclines, can change and inhibit the rates at which matter fluctuates from the water column to the benthos and vice versa (e.g. Biggs and Wetzel, 1968; Qiao et al., 2011). While dissolved matter can still readily diffuse across the thermocline (e.g. Emerson et al., 1997), particulate matter up to a critical negative buoyancy threshold is unlikely to cross a thermodynamic barrier. In the majority of cases, the deposition of particles occurs in combination with other processes; turbulence and upward-mixing can make the settling process considerably unpredictable (Winterwerp and Kesteren, 2004). Mass settling flux may thus be defined as a product of matter concentration and settling velocity (Manning and Bass, 2006). The latter is mainly affected by the size and density in which OM flocs occur (Maa and Kwon, 2007) while the former depends on the rates at which particles are supplied through resuspension or release within the water column. In cohesive sediment settling conditions, high concentrations of suspended particles may flocculate while in suspension (Einstein and Krone, 1962; Stolzenbach and Elimelech, 1994). Flocculation is a constant yet dynamic balance of aggregation and disaggregation (Tsai et al., 1987) driven by physical or chemical attraction, and particle polydispersity (Sun et al., 2018). The typical primary source of cohesion and hence flocculation is the effect of salinity on charged clay particles through mass-attractive London-van der Waals forces and electrostatic bonding, though this may not be the most important factor driving flocculation in a biological context (Parsons et al., 2016). Flocculated particles are relatively large in size and tend to settle more readily than primary particles, depending on their size and density, but may be broken up again easily by applied shear stress (Winterwerp, 2011). Regardless of particle size or nature, materials can be moved around the water column through turbulent water flow and trapped in biological (e.g. Gambi et al., 1990) or man-made (e.g. Simons and Şentürk, 1992) near-bottom structures. Lateral transport throughout water bodies can be hard to track, and only some studies attempt to trace the origins of suspended matter collected in sediment traps (e.g. Narita et al., 1990). There is much to discover yet about the sources of suspended particulates and the pathways they take through the water column. Biological drivers of particle deposition can act both actively and passively. Some zooplankton groups, such as Copepods, migrate vertically through the water column on a diurnal basis. The transport of OM through diel vertical migration constitutes an active downward transport, as organisms come towards the upper water layers to feed at night and return to deeper water where the OM is returned to the system in the form of excretions, or as decaying carcases (Packard and Gómez, 2013). The presence of OM and microorganisms suspended in the water column (generally termed “marine snow”) can enhance benthic community metabolism rates and nutrient mineralization (Van Duyl et al., 1992). Marine snow aggregates can include any combination of dead and living matter of highly variable spatial complexity, density, and consequently, sinking rate (Alldredge and Gotschalk, 1988). It serves as a microhabitat and food source to pelagic organisms during its sinking (Lundgaard et al., 2017) and is a source of OM to benthic organisms (e.g. Townsend et al., 1992). In low turbulence, fluff-like OM, which is not immediately incorporated into the sediment matrix, may form a layer that rests on the sediment surface along with fine sediment particles (termed nepheloid layer; e.g. Durrieu de Madron et al., 2017). Within this layer, particulates may be transported laterally across large distances and even exported off the continental shelf (Inthorn et al., 2006). Particle residence times within the nepheloid layer can be vast and warrant further study. Deposition of particulate matter on the seafloor is catalyzed by roughness elements, which result in interfacial flow dynamics and cause descending vertical sweeps (Huettel et al., 1996). Biogenic structures, such as bivalve byssal structures and seagrasss blades, can trap suspended particles, reduce near-bed water velocity, and increase turbulence in the benthic boundary layer (e.g. Widdows et al., 1998b). In addition, filter feeders can actively move water and the particles suspended in it, towards the sea floor, causing increased particle fluxes towards the benthos, preventing subsequent resuspension through ingestion, trapping in structures (such as tubes and gills), and pelletization of the descended matter (e.g. Widdows et al., 1998b; Denis et al., 2007). Selective sediment particle processing, through the actions of biodiffusing bivalves, for example can lead to long-lasting changes in granulometry over large spatial scales, thereby changing the environment and creating specific habitats for other organisms (Montserrat et al., 2009). Around mussel beds, biodeposition is further catalyzed and accelerated through the production of pseudofaeces, which leads to an increase in the annual deposition of sediment, C, and nutrients (Kautsky and Evans, 1987). Macroalgae and seagrasses have been shown to shield the sea bed from turbulence and lower water velocities, thereby increasing net deposition rates (Fonseca et al., 1982; Gambi et al., 1990). The rate at which this filtering of suspended material flowing through the fronds occurs depends strongly upon the morphology of the macrophytes (Hendrick et al., 2016). Obstacle-induced flow turbulence can effectively filter suspended particulate matter from the water column by driving parts of the flow through the sediment matrix, thus leading to their deposition within the sediment (Hutchinson and Webster, 1998). B/P exchange may further be affected by animals that increase sediment cohesion by building protruding tubes and byssal mats. These act similarly to sea grass and algal fronds by altering the flow and trapping sediments when they occur in high densities. Lanice conchilega presence, for example can lead to a reduction in erosion potential when occurring in high enough densities (Denis et al., 2007; Borsje et al., 2014). The addition of small particles to the sediment matrix through active or passive filtering may lead to a change in sediment granulometry and, effectively, cohesion (e.g. Widdows et al., 2000; Volkenborn et al., 2007). During the deposition of already cohesive sediments, though particles of all sizes may be deposited (Lau and Krishnappan, 1994), a sorting process can occur, thus leading to vertical and horizontal particle size gradients (Mehta, 1988). The availability of depositable particulate material in the water column may also be affected by anthropogenic structures and actions, including dredge-spoil dumping (Moon et al., 1994; Pilskaln et al., 1998; Mikkelsen and Pejrup, 2000) and the installation of offshore wind farms (Baeye et al., 2011; Coates et al., 2014; Dannheim et al., 2019). Although the former constitutes a rapid and intense input of non-native particulate matter to the water column, this does not always affect the benthic community or local sediment properties directly (Smith and Rule, 2001). It can, however, introduce additional organic carbon and new species to the dredged site (Morton, 1977; Wildish and Thomas, 1985), which is likely to have knock-on effects on the biogeochemical composition of the affected environments and B/P exchange potentials. Although some monitoring studies have investigated short-to-medium term effects of dredge-spoil dumping on drivers of B/P exchange, few of these studies include an adequate assessment of the benthic environment prior to the commencement of the dumping and the number of long-term monitoring studies to date is insufficient to draw meaningful conclusions. Other activities, such as active bottom fishing practices (dredging, trawling), can also cause increases in SPM. For instance, trawling can increase SPM concentrations up to six times that of the background levels (Tiano et al., 2019). In the case of offshore wind farms, SPM plumes up to five times the background level in concentration have been shown to be generated through tidal resuspension of fine-grained materials accumulated and produced by epifauna associated with the wind farms’ solid structures (Baeye and Fettweis, 2015). The changes in granulometry and OM content in the sediment (Coates et al., 2014) are mostly attributable to the fauna’s filtering activity and the production of faeces and pseudofaeces, which can lead to a shift in microbenthic community structure and diversity. In addition, the solid structures constituting the wind turbine’s foundations introduce roughness elements to the water column, thereby creating eddies, vortexes, and turbulent flow dynamics and increasing the probability of resuspension (Grashorn and Stanev, 2016). Considering the extensive coverage of offshore wind farms in some areas, such as throughout the North Sea, this change in circulation, seafloor community, and sediment properties may constitute shifts in B/P exchange pathways at large spatial scales. In contrast to several well-studied offshore wind farms impacts, such as seabird collisions, settlement of encrusting fauna and flora, and electromagnetic disturbances, not much research has been carried out to test their effects on B/P exchange processes (Dannheim et al., 2019). Furthermore, the investigation of anthropogenic impacts often happens in retrospect and the addition of more baseline studies would undoubtedly add much to our understanding of anthropogenic impacts on particle deposition. Upward flux and resuspension Particle deposition is rarely final, as particulates can be eroded away from the sediment surface. Generally speaking, the erosion of non-cohesive sediments is constant with applied shear stress and a product of fluid stresses and grain stresses only affected by the excess shear stress, bed roughness, grain size and orientation, particle sorting and packing, and bed configuration (Julien, 2010). On an exclusively physical basis, low-level forces applied to the sediment lead to rolling or sliding of particles along its surface, medium levels prompt a hopping motion called saltation, and strong forces cause particles to be drawn from the bulk sediment into complete suspension. In turbulent environments, particles exchange momentum with the surrounding fluids and are thereby swept across or ejected from the sediment surface (Gordon, 1974; Kassem et al., 2015). Physical erosion patterns in cohesive environments depend strongly upon the way in which the bed was originally formed (Ariathurai and Arulanandan, 1978). Erosion processes in cohesive environments are depth-limited, and erosion rates are reduced in deeper layers, due to the consolidation of particles with depth (Aberle et al., 2004). There are three different types of physical erosion (Amos et al., 1992, 1997), and all three may be displayed in parallel in cohesive sediments, making the process notoriously hard to model. An additional factor that complicates our understanding of the erosion process is the interference of biotic elements. The extracellular polymeric substances (EPS) produced by marine biofilms, for example reduce the sediment surface roughness and frictional drag, thereby increasing cohesion (Sutherland et al., 1998). EPS distribution throughout the sediment is one of the key components controlling bed form dynamics where it appears in high enough concentrations (Malarkey et al., 2015). There are other biological mechanisms affecting sediment erosion and resuspension such as animal tracking, grazing, (Nowell et al., 1981; Borsje et al. 2008; Kristensen et al., 2012), and faecal pellet production (Andersen and Pejrup, 2002) affecting bed roughness as well as resuspension potentials. Benthic organisms can also drive transport that counters gravimetric deposition by actively ejecting OM and sediment grains into the water column during feeding and other activities, as well as their gametes and larvae to initiate pelagic stages in their development (e.g. the polychaete burrowers Nereis virens; Bass and Brafield, 1972). Other organisms known as ecosystem engineers modify, maintain, and create habitats by causing physical state changes in biotic or abiotic materials, thereby modulating resource availabilities directly and/or indirectly (e.g. reef-building bivalves and macrophytes; Jones et al., 1994). The extent to which different areas of the ecosystem in question are impacted depends upon the strength and nature of the respective engineering species (Bouma et al., 2009; Meadows et al., 2012). They may, for example alter their environment and change flow dynamics around the sea bed, thereby altering erosion and deposition rates in various ways (Coleman and Williams, 2002) and thus dictating the sediment type present in an area (Ginsburg and Lowenstam, 1958). Increases in bulk sediment grain size and permeability caused by the bioengineers then promote altered B/P exchange rates (Ziebis et al., 1996). Erosion thresholds may also be affected, in some cases seasonally varying between increase and decrease (Grant and Daborn, 1994; Paarlberg et al., 2005). These and other biologically mediated particle movements can affect particle distributions from micro to landscape scale (Van Hoey et al., 2008; Montserrat et al., 2009). Bioturbation (the biogenic movement of particulate matter throughout the sediment matrix) can play an important role in localized particle displacement (Berg et al., 2001) as well as landscape-scaled effects on particle distributions by affecting sedimentary structure, biogeochemical gradients and fluxes, and the composition of associated communities of auto- and heterotrophs (Van Hoey et al., 2008; Bouma et al., 2009; Montserrat et al., 2009). Each bioturbating species may affect particle exchanges differently, depending on their functional traits, mediated by species performance in response to the environment in which they occur (e.g. Mermillod-Blondin et al., 2004; Solan et al., 2004; Maire et al., 2006; Braeckman et al., 201), sediment characteristics (Bernard et al., 2019), and temporal patterns such as seasonal cycles (Queirós et al., 2015). The main impacts that bioturbation activity has on upward B/P exchange processes are (i) that it generally destabilizes the sediment, lowering critical erosion and resuspension thresholds in the process (Widdows et al., 1998c; De Deckere et al., 2001), and (ii) the biogenic physical ejection of particulate matter into the water column (Davis, 1993). Co-occurrence of bio-stabilizing and destabilizing organisms is known to have variable effects on sediment matrix properties (Queirós et al., 2011). Such duality may even exist within the effects of a single species, such as has been shown in the deposit-feeder Peringia ulvae, which destabilizes sediment surfaces through grazing while simultaneously excreting pellets with increased settling velocity compared to the original sediment, thereby having both destabilizing and stabilizing effects (Andersen and Pejrup, 2002). In some cases, an organisms’ effect on sediment erosion thresholds may even reverse in sync with seasonal environmental changes, leading to alternating stabilization and destabilization of the surrounding sediment (e.g. Grant and Daborn, 1994). Overall, the magnitude at which biological processes affect sediment transport and solute exchange is tightly dependent upon the density of active organisms and the magnitude of their effects relative to that of ecosystem attributes or processes also affecting the transport of sediment and solutes (Queirós et al., 2011; Erik Kristensen et al., 2012). The net effect of co-occurring bio-stabilizing and destabilizing benthos, and how this balance may shift on different temporal and spatial scales, has thus far only been investigated in small, location-specific studies and should be investigated at the ecosystem level. Once buried, particles may be stored and consolidated or recycled (Graf and Rosenberg, 1997). Within the benthic matrix, the complex materials that are not permanently buried are broken down chemically via oxidation and biologically by benthos and bacteria, allowing them to re-enter the cycling of elements. In permeable sediments, even living microphytes may be advectively flushed into deeper sediment layers and trapped there, leaving them to be mineralized more swiftly than they would be at the sediment surface when they die, thereby fuelling the recycling of nutrients and C (Ehrenhauss et al., 2004). Advective flushing of particulate OM throughout permeable sediment distributes it evenly, thereby alleviating concentrated hot spots and spreading the OM to a larger microbial community (Franke et al., 2006). Diagenetic reactions vary in speed and, consequently, affect the environment on different scales: very slow reactions occur mostly at depth and are of importance at geological time scales, while rapid ones define the biogeochemical conditions of the benthic boundary layer without having interfered in the sediment matrix at any significant depth (Aller, 2014). The major roles that biological processes play in mineralization do not only extend to the direct impacts of microbes, which catalyze and drive the process itself but also the effects of larger organisms, which modify OM burial rates and contribute to its break-down through grazing (Tait et al., 2015; Queirós et al., 2019). The translocation of particles and potential homogenization of surface sediment layers, as well as the introduction of fresh O2 and OM to deeper layers by bioturbators, bioirrigators, and even benthivores, is a crucial determinant of diagenetic processes (Lindqvist, 2014). Direct anthropogenic causes of particle resuspension include dredging, trawling, mining, anchoring, and many others. Repeated dredging can lead to long-term modification of local sediment properties and particle and solute transport rates at the dredged site (Moon et al., 1994; Pilskaln et al., 1998; Mikkelsen and Pejrup, 2000), and the use of trawls and similar types of mobile fishing gear can have comparable effects (e.g. Palanques et al., 2001; Jennings and Kaiser, 2006). The removal of fine-grained particles from continental shelves through anthropogenic resuspension on a global scale is estimated to be up to six times as large as it would be through purely natural causes of resuspension, closely matching the input of fine-grained material from riverine sources (Oberle et al., 2016). On a local level, however, this may not be the case (e.g. Schoellhamer, 2002; Ferré et al., 2008). Mobile fishing gear can furthermore lead to the removal or disruption of micro- and macro-phytic communities that would otherwise inhibit resuspension, as well as modification of the benthic macrofauna community composition (Hiddink et al., 2006; Hiddink et al., 2006), and burial of sediment surface chlorophyll a content (Tiano et al., 2019). Biogeochemical impacts of trawling are more pronounced in naturally muddy than in sandy environments (Sciberras et al., 2016), although some sandy sediments are likely to occur due to long-term granulometry changes resulting from chronic bottom trawling pressure (Hiddink et al., 2006). Long-term biogeochemical changes in seafloor habitats associated with anthropogenic interactions, and associated shifts in B/P exchange processes remain, thus far, largely unknown. This is, among other reasons, due to a lack of data on baseline conditions collected prior to anthropogenic intervention. Interactions and interdependencies Most of the B–P coupling processes described in this review are difficult to consider individually, as they either interact very closely with others or have a wide range of effects and dependencies, making them hard to assign to any one section. Each is part of a feedback mechanism and interacting with others, thereby producing the overall effect on sediment and water column structures, which results in altered rates of sediment and solute transport (Borsje et al., 2008). The combination of interacting processes and the scales at which they affect exchanges between the benthic and pelagic zones varies in accordance with the respective physical and biological environmental conditions, the “ecological context” (Queirós et al., 2011). Most biologically important processes are dependent on both solute and particle B/P exchanges and interactions. One example of this is the cycling of OM , which benthic heterotrophs mediate. Most OM in the marine environment originates from primary producers such as phytoplankton, seaweeds, and other macrophytes, which require light and nutrients in solution to grow, the latter being especially important during times and in locations of nutrient depletion (e.g. Davis et al., 2019). During phytoplankton growth cycles, both dissolved OM (DOM) and particulate OM (POM) specimens are produced and introduced to the environment surrounding the plankton (Biddanda and Benner, 1997). Each of these OM compounds may be utilized differently, as detailed in the previous sections of this review. While POM may be consumed by secondary producers and then exported towards the benthos, either passively through incorporation in faecal pellets and marine snow floccules or actively through the vertical migration of the consumers, DOM may stay in suspension. Depending on the hydrological circumstances, the DOM may be fully utilized and degraded by the microbial community within the water column (Mari et al., 2007). Throughout this process, DOM and POM are in constant interaction through a variety of pathways, which are complex enough to warrant entire review papers by themselves (e.g. Mecozzi et al., 2008; He et al., 2016). Once the OM reaches the sea floor, however, it is utilized by macro- and micro-fauna and/or mineralized by the benthic microbial community (Gooday and Turley, 1990). Both pathways are linked and require an oxidizing environment to function, which is where B/P exchange of dissolved O2 plays an important role (Snelgrove et al., 2018). These and other links exist within the OM cycling process, which highlights the connectivity between solute and particle B/P exchange pathways of C, O2, nutrients, and many more . Due to the complexity of the marine system and associated observation or experimentation, there are still many questions in want of an answer, offering a guiding direction for future research. Future direction Historically, the exchange of particles and solutes, which were seen as two separate pools of resources, was studied one-dimensionally and often in isolation from other ecosystem processes. This review highlights the shortcomings of this treatment of solutes and particles as separate entities instead of inseparably interwoven parts of the same exchange pathways (see e.g. Kristensen et al., 2012). It should be noted that in some fields, such as diagenetic research, the assumption of an integrated solute/particle framework has been the status-quo for decades (Berner, 1980), but this has not been the case in many fields and, especially, in benthic ecology. These differences in approach could in many instances be attributable to a lack of interdisciplinary collaborations that require bridging in future work. A separate consideration of solutes and particles may be necessary in the exploration of specific transport mechanisms, but as B/P processes are typically affected by many types of exchanges simultaneously, such one-dimensional studies can only ever represent basic foundational elements on which a higher understanding is built. Rediscovering the ecological complexity and applying it in areas other than diagenetic research will thus lead to a better holistic understanding and predictive ability, regarding both drivers and consequences of B/P exchanges. The insight that observations at the ecosystem level are too complex to be approached in the way most empirical ecological studies have done in the past is nothing new (Lawton, 1999), and a change in perspective has already been suggested (Thrush et al., 2009). Detailed guidelines have been suggested to aid scientists in their study design to allow the extrapolation of empirical study results to broader temporal and spatial scales (Hewitt et al., 2007). This includes advice such as consideration of contextual natural history to estimate expectable heterogeneity, integration of correlative and manipulative study elements, inclusion of iterative measurements between integrative studies, use of continuous explanatory variables during the analysis stage, and finally, the integration of in situ data and model outputs (Hewitt et al., 2007). Time series data have been assessed as one of the most useful tools to provide broad scale temporal context to ecosystem processes (Thrush et al., 1996) such as B/P exchange. Our review highlights that, although the awareness of a need for ecosystem-level approaches clearly exists, and individual B/P exchange processes are often well-studied, not all pathways have been explored equally well in the past and the multidimensional, transdisciplinary approach is still not used as the foundation of B/P exchange research, at large. Some gaps, such as the lack of objective rank-ability of the respective relative importance of drivers of solute and particle B/P exchanges, require exactly the kind of temporal and spatial ecological context described in the previous paragraph. Information on individual driver processes cannot be balanced or compared with one another without coherent scale and contextual information. Furthermore, while some studies hint at parts of different exchange pathways across the sediment–water interface (e.g. Berner, 1980; Glud, 2008; Aller, 2014), there is generally a distinct lack of information regarding the exchanges themselves, and their importance in the greater ecosystem context, as noted in recent work (e.g. Middelburg, 2017). The consequence of this shift in perception is that when dissecting any B/P exchange pathway into its individual processes, it becomes apparent that often not all processes involved are well known well enough to allow for the accurate quantification of the entire pathway. Thus, even when consideration of the environmental spatial and temporal context permits a classification of drivers of exchange by relative importance, not all may be known in enough detail to be of use. Examples of parameters into which more research should be invested are, for example the effects of biological and anthropogenic actions of the diffusion of solutes other than O2, in situ observations of interactions of boundary layer dynamics with physical drivers of B/P exchange, potential seasonal dominance of biological drivers of B/P exchange over physical ones, lateral particulate matter transport, and residence times within the nepheloid layer. Embracing the ecosystem as a whole, regardless of the discipline in which individual pieces of research were undertaken, is a vital step towards improved benthic–pelagic understanding (Widdows et al., 2000; Kristensen, 2001; Griffiths et al., 2017) and an in-depth understanding of individual drivers and processes is key to this. However, to integrate studies from various fields as is often necessary when investigating ecosystem-level pathways, such as B/P exchanges, some caution must be exercised. Middelburg (2017) summarizes the different approaches of various disciplines well on the example of organic carbon cycling by pointing out areas of disagreement versus overlap, and accumulating elements from each discipline to form a complete picture of current knowledge on the topic. Collaborative research efforts must move past multidisciplinary approaches in which individuals or teams from different disciplines independently research the same environment, only to later collate their findings, to truly transdisciplinary working practices that take elements of the various disciplines into account from the start. The ideal next step in gaining a deeper understanding of B/P exchange in coastal marine ecosystems will be to fully acknowledge the complexity and interdependencies of the processes involved in individual pathways. This will lead towards a more precise measure of real-life ecosystem-scaled processes, such as elemental cycling, gas exchange, quantification and subsequent mitigation of anthropogenic influences, and much more. Measuring this complexity in real systems will doubtlessly be a challenge, but it could also be the stepping stone to a deeper understanding of the marine environment at local and global scales, providing us with the means to better study, conserve, and protect it. With ongoing environmental change, be it anthropogenic or natural, we will thus be able to make more accurate assessments of the state of the marine ecosystem functioning and take appropriate actions to conserve it. Funding This work was supported by the Natural Environmental Research Council (grant number NE/L002531/1). References Aberle J. , Nikora V., Walters R. 2004 . Effects of bed material properties on cohesive sediment erosion . Marine Geology , 207 : 83 – 93 . Google Scholar Crossref Search ADS WorldCat Ahmerkamp S. , Winter C., Krämer K., Beer D. d., Janssen F., Friedrich J., Kuypers M. M. M. et al. 2017 . Regulation of benthic oxygen fluxes in permeable sediments of the coastal ocean . Limnology and Oceanography , 62 : 1935 – 1954 . Google Scholar Crossref Search ADS WorldCat Alldredge A. L. , Gotschalk C. 1988 . In situ settling behavior of marine snow . Limnology and Oceanography , 33 : 339 – 351 . Google Scholar Crossref Search ADS WorldCat Aller R. C. 1983 . The importance of the diffusive permeability of animal burrow linings in determining marine sediment chemistry . Journal of Marine Research , 41 : 299 – 322 . Google Scholar Crossref Search ADS WorldCat Aller R. C. 2014 . Sedimentary diagenesis, depositional environments, and benthic fluxes . In The Oceans and Marine Geochemistry , 2nd edn, pp. 293 – 334 . Elsevier Ltd, Oxford, UK. doi: 10.1016/B978-0-08-095975-7.00611-2. Google Scholar OpenURL Placeholder Text WorldCat Amos C. L. , Grant J., Daborn G. R., Black K. 1992 . Sea carousel—a benthic, annular flume . Estuarine, Coastal and Shelf Science , 34 : 557 – 577 . Google Scholar Crossref Search ADS WorldCat Amos C. L. , Feeney T., Sutherland T. F., Luternauer J. L. 1997 . The stability of fine-grained sediments from the Fraser River delta . Estuarine, Coastal and Shelf Science , 45 : 507 – 524 . Google Scholar Crossref Search ADS WorldCat Andersen T. J. , Jensen K. T., Lund-Hansen L., Mouritsen K. N., Pejrup M. 2002 . Enhanced erodibility of fine-grained marine sediments by Hydrobia ulvae . Journal of Sea Research , 48 : 51 – 58 . Google Scholar Crossref Search ADS WorldCat Andersen T. J. , Pejrup M. 2002 . Biological mediation of the settling velocity of bed material eroded from an intertidal mudflat, the Danish Wadden Sea . Estuarine, Coastal and Shelf Science , 54 : 737 – 745 . Google Scholar Crossref Search ADS WorldCat Anderson M. P. , Cherry J. A. 1979 . Using models to simulate the movement of contaminants through groundwater flow systems . Critical Reviews in Environmental Control , 9 : 97 – 156 . Google Scholar Crossref Search ADS WorldCat Ariathurai R. , Arulanandan K. 1978 . Erosion rates of cohesive soils . Journal of the Hydraulics Division , 104 : 279 – 283 . Google Scholar OpenURL Placeholder Text WorldCat Baeye M. , Fettweis M., Voulgaris G., Van Lancker V. 2011 . Sediment mobility in response to tidal and wind-driven flows along the Belgian inner shelf, southern North Sea . Ocean Dynamics , 61 : 611 – 622 . Google Scholar Crossref Search ADS WorldCat Baeye M. , Fettweis M. 2015 . In situ observations of suspended particulate matter plumes at an offshore wind farm, southern North Sea . Geo-Marine Letters , 35 : 247 – 255 . Google Scholar Crossref Search ADS WorldCat Barnes M. K. , Tilstone G. H., Suggett D. J., Widdicombe C. E., Bruun J., Martinez-Vicente V., Smyth T. J. et al. 2015 . Temporal variability in total, micro- and nano-phytoplankton primary production at a coastal site in the Western English Channel . Progress in Oceanography , 137 : 470 – 483 . Google Scholar Crossref Search ADS WorldCat Bass N. R. , Brafield A. E. 1972 . The life-cycle of the Polychaete Nereis virens . Journal of the Marine Biological Association of the United Kingdom , 52 : 701 – 726 . Google Scholar Crossref Search ADS WorldCat Berg P. , Rysgaard S., Funch P., Sejr M. K. 2001 . Effects of bioturbation on solutes and solids in marine sediments . Aquatic Microbial Ecology , 26 : 81 – 94 . Google Scholar Crossref Search ADS WorldCat Bernard G. , Gammal J., Järnström M., Norkko J., Norkko A. 2019 . Quantifying bioturbation across coastal seascapes: habitat characteristics modify effects of macrofaunal communities . Journal of Sea Research , 152 : 101766 . Google Scholar Crossref Search ADS WorldCat Berner R. A. 1980 . Early Diagenesis: A Theoretical Approach. Princeton University Press, Princeton, NJ . Biddanda B. , Benner R. 1997 . Carbon, nitrogen, and carbohydrate fluxes during the production of particulate and dissolved organic matter by marine phytoplankton. Limnology and Oceanography, 42 : 506 – 518 . Biggs R. B. , Wetzel C. D. 1968 . Concentration of particulate carbohydrate at the halocline in Chesapeake Bay . Limnology and Oceanography , 13 : 169 – 171 . Google Scholar Crossref Search ADS WorldCat Borsje B. W. , Bouma T. J., Rabaut M., Herman P. M. J., Hulscher S. J. M. H. 2014 . Formation and erosion of biogeomorphological structures: a model study on the tube-building polychaete Lanice conchilega . Limnology and Oceanography , 59 : 1297 – 1309 . Google Scholar Crossref Search ADS WorldCat Borsje B. W. , de Vries M. B., Hulscher S. J. M. H., de Boer G. J. 2008 . Modeling large-scale cohesive sediment transport affected by small-scale biological activity . Estuarine, Coastal and Shelf Science , 78 : 468 – 413 . Google Scholar Crossref Search ADS WorldCat Bouma T. J. , Olenin S., Reise K., Ysebaert T. 2009 . Ecosystem engineering and biodiversity in coastal sediments: posing hypotheses . Helgoland Marine Research , 63 : 95 – 106 . Google Scholar Crossref Search ADS WorldCat Boudreau B. P. , Jorgensen B. B. eds. 2001 . The benthic boundary layer: Transport processes and biogeochemistry. Oxford University Press, Oxford, UK . Braeckman U. , Provoost P., Gribsholt B., Van Gansbeke D., Middelburg J. J., Soetaert K., Vincx M. et al. 2010 . Role of macrofauna functional traits and density in biogeochemical fluxes and bioturbation . Marine Ecology Progress Series , 399 : 173 – 186 . Google Scholar Crossref Search ADS WorldCat Burnett W. C. , Bokuniewicz H., Huettel M., Moore W. S., Taniguchi M. 2003 . Groundwater and pore water inputs to the coastal zone . Biogeochemsitry , 66 : 3 – 33 . Google Scholar Crossref Search ADS WorldCat Caddy J. F. 2000 . Marine catchment basin effects versus impacts of fisheries on semi-enclosed seas . ICES Journal of Marine Science. Narnia , 57 : 628 – 640 . Google Scholar Crossref Search ADS WorldCat Cai W. , Sayles F. L. 1996 . Oxygen penetration depths and fluxes in marine sediments . Marine Chemistry , 52 : 123 – 131 . Google Scholar Crossref Search ADS WorldCat Caliman A. , Leal J. J. F., Esteves F. A., Carneiro L. S., Bozelli R. L., Farjalla V. F. 2007 . Functional bioturbator diversity enhances benthic—pelagic processes and properties in experimental microcosms . Journal of the North American Benthological Society , 26 : 450 – 459 . Google Scholar Crossref Search ADS WorldCat Coates D. A. , Deschutter Y., Vincx M., Vanaverbeke J. 2014 . Enrichment and shifts in macrobenthic assemblages in an offshore wind farm area in the Belgian part of the North Sea . Marine Environmental Research , 95 : 1 – 12 . Google Scholar Crossref Search ADS PubMed WorldCat Coleman F. C. , Williams S. L. 2002 . Overexploiting marine ecosystem engineers: potential consequences for biodiversity . Trends in Ecology and Evolution , 17 : 40 – 44 . Google Scholar Crossref Search ADS WorldCat Cook P. L. M. , Wenzhöfer F., Glud R. N., Janssen F., Huettel M. 2007 . Benthic solute exchange and carbon mineralization in two shallow subtidal sandy sediments: effect of advective pore-water exchange . Limnology and Oceanography , 52 : 1943 – 1963 . Google Scholar Crossref Search ADS WorldCat Corte G. N. , Schlacher T. A., Checon H. H., Barboza C. A. M., Siegle E., Coelman R. A., Amaral A. C. Z. et al. 2017 . Storm effects on intertidal invertebrates: increased beta diversity of few individuals and species . PeerJ , 5 : e3360 – 18 . Google Scholar Crossref Search ADS PubMed WorldCat Couceiro F. , Fones G. R., Thompson C. E. L., Statham P. J., Sivyer D. B., Parker R., Kelly-Gerreyn B. A. et al. 2013 . Impact of resuspension of cohesive sediments at the Oyster Grounds (North Sea) on nutrient exchange across the sediment-water interface . Biogeochemistry , 113 : 37 – 52 . Google Scholar Crossref Search ADS WorldCat Dannheim J. et al. 2019 . Wildlife and Wind Farms, Conflicts and Solutions (Volume 3: Offshore: Potential Effects). Ed. by Perrow M.. Pelagic Publishing , Exeter . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Davis C. E. , Blackbird S., Wolff G., Woodward M., Mahaffey C. 2019 . Seasonal organic matter dynamics in a temperate shelf sea . Progress in Oceanography , 177 : 1 – 12 . Google Scholar Crossref Search ADS WorldCat Davis W. R. 1993 . The role of bioturbation in sediment resuspension and its interaction with physical shearing . Journal of Experimental Marine Biology and Ecology , 171 : 187 – 200 . Google Scholar Crossref Search ADS WorldCat De Deckere E. M. G. T. , Tolhurst T. J., De Brouwer J. F. C. 2001 . Destabilization of cohesive intertidal sediments by infauna . Estuarine, Coastal and Shelf Science , 53 : 665 – 669 . Google Scholar Crossref Search ADS WorldCat Dellapenna T. M. , Kuehl S. A., Schaffner L. C. 1998 . Sea-bed mixing and particle residence times in biologically and physically dominated estuarine systems: a comparison of lower Chesapeake Bay and the York River subestuary . Estuarine, Coastal and Shelf Science , 46 : 777 – 795 . Google Scholar Crossref Search ADS WorldCat Denis L. , Desroy N., Ropert M. 2007 . Ambient flow velocity and resulting clearance rates of the terebellid polychaete Lanice conchilega (Pallas, 1766) . Journal of Sea Research , 58 : 209 – 219 . Google Scholar Crossref Search ADS WorldCat Durrieu de Madron X. , Ramondenc S., Berline L., Houpert L., Bosse A., Martini S., Guidi L. et al. 2017 . Deep sediment resuspension and thick nepheloid layer generation by open-ocean convection . Journal of Geophysical Research: Oceans , 122 : 2291 – 2318 . Google Scholar Crossref Search ADS WorldCat Ehrenhauss S. , Witte U., Bühring S. I., Huettel M. 2004 . Effect of advective pore water transport on distribution and degradation of diatoms in permeable North Sea sediments . Marine Ecology Progress Series , 271 : 99 – 111 . Google Scholar Crossref Search ADS WorldCat Einstein H. A. , Krone R. B. 1962 . Experiments to determine modes of cohesive sediment transport in salt water . Journal of Geophysical Research , 67 : 1451 – 1461 . Google Scholar Crossref Search ADS WorldCat Eloire D. , Somerfield P. J., Conway D. V. P., Halsband-Lenk C., Harris R., Bonnet D. 2010 . Temporal variability and community composition of zooplankton at station L4 in the Western Channel: 20 years of sampling . Journal of Plankton Research , 32 : 657 – 623 . Google Scholar Crossref Search ADS WorldCat Emerson S. , Quay P., Karl D., Winn C., Tupas L., Landry M. 1997 . Experimental determination of the organic carbon flux from open-ocean surface waters . Nature , 389 : 951 – 954 . Google Scholar Crossref Search ADS WorldCat Emerson S. , Hedges J. 2003 . Sediment diagenesis and benthic flux . Treatise on Geochemistry , 6 : 293 – 319 . Google Scholar Crossref Search ADS WorldCat Fang X. , Mestdagh S., Ysebaert T., Moens T., Soetaert K., Van Colen C. 2019 . Spatio-temporal variation in sediment ecosystem processes and roles of key biota in the Scheldt estuary . Estuarine, Coastal and Shelf Science , 222 : 21 – 31 . Google Scholar Crossref Search ADS WorldCat Ferré B. , Durrieu de Madron X., Estournel C., Ulses C., Le Corre G. 2008 . Impact of natural (waves and currents) and anthropogenic (trawl) resuspension on the export of particulate matter to the open ocean: application to the Gulf of Lion (NW Mediterranean) . Continental Shelf Research , 28 : 2071 – 2091 . Google Scholar Crossref Search ADS WorldCat Fonseca M. S. , Fisher J. S., Zieman J. C., Thayer G. W. 1982 . Influence of the seagrass, Zostera marina L., on current flow . Estuarine, Coastal and Shelf Science , 15 : 351 – 364 . Google Scholar Crossref Search ADS WorldCat Forster S. , Glud R. N., Gundersen J. K., Huettel M. 1999 . In situ study of bromide tracer and oxygen flux in coastal sediments . Estuarine Coastal and Shelf Science , 49 : 813 – 827 . Google Scholar Crossref Search ADS WorldCat Franke U. , Polerecky L., Precht E., Huettel M. 2006 . Wave tank study of particulate organic matter degradation in permeable sediments . Limnology and Oceanography , 51 : 1084 – 1096 . Google Scholar Crossref Search ADS WorldCat Gambi M. C. , Nowell A. R. M., Jumars P. A. 1990 . Flume observations on flow dynamics in Zostera marina (eelgrass) beds . Marine Ecology Progress Series , 61 : 159 – 169 . Google Scholar Crossref Search ADS WorldCat Gilbert F. , Stora G., Bonin P. 1998 . Influence of bioturbation on denitrification activity in Mediterranean coastal sediments: an in situ experimental approach . Marine Ecology Progress Series , 163 : 99 – 107 . Google Scholar Crossref Search ADS WorldCat Ginsburg R. N. , Lowenstam H. A. 1958 . The influence of marine bottom communities on the depositional environment of sediments . The Journal of Geology , 66 : 310 – 318 . Google Scholar Crossref Search ADS WorldCat Glud R. N. , Gundersen J. K., Røy H., Jørgensen B. B. 2003 . Seasonal dynamics of benthic O2 uptake in a semienclosed bay: importance of diffusion and faunal activity . Limnology and Oceanography , 48 : 1265 – 1276 . Google Scholar Crossref Search ADS WorldCat Glud R. N. 2008 . Oxygen dynamics of marine sediments . Marine Biology Research , 4 : p 243 – 289 . Google Scholar Crossref Search ADS WorldCat Gooday A. J. , Turley C. M. 1990 . Responses by benthic organisms to inputs of organic material to the ocean floor: a review . Philosophical Transactions of the Royal Society A , 331 : 119 – 138 . Google Scholar OpenURL Placeholder Text WorldCat Gordon C. M. 1974 . Intermittent momentum transport in a geophysical boundary layer . Nature , 248 : 392 – 394 . Google Scholar Crossref Search ADS WorldCat Graf G. , Rosenberg R. 1997 . Bioresuspension and biodeposition: a review . Journal of Marine Systems , 11 : 269 – 278 . Google Scholar Crossref Search ADS WorldCat Grant J. , Daborn G. 1994 . The effects of boiturbation on sediment transport on an intertidal mudflat . Netherlands Journal of Sea Research , 32 : 63 – 72 . Google Scholar Crossref Search ADS WorldCat Grashorn S. , Stanev E. V. 2016 . Kármán vortex and turbulent wake generation by wind park piles . Ocean Dynamics , 66 : 1543 – 1557 . Google Scholar Crossref Search ADS WorldCat Griffiths J. R. , Kadin M., Nascimento F. J. A., Tamelander T., Törnroos A., Bonaglia S., Bonsdorff E. et al. 2017 . The importance of benthic—pelagic coupling for marine ecosystem functioning in a changing world . Global Change Biology , 23 : 2179 – 2196 . Google Scholar Crossref Search ADS PubMed WorldCat Hale R. , Godbold J. A., Sciberras M., Dwight J., Wood C., Hiddink J. G., Solan M. et al. 2017 . Mediation of macronutrients and carbon by post- disturbance shelf sea sediment communities . Biogeochemistry , 135 : 121 – 133 . Google Scholar Crossref Search ADS PubMed WorldCat Hansen K. , Kristensen E. 1998 . The impact of the polychaete Nereis diversicolor and enrichment with macroalgal (Chaetomorpha linum) detritus on benthic metabolism and nutrient dynamics in organic-poor and organic-rich sediment . Journal of Experimental Marine Biology and Ecology , 231 : 201 – 223 . Google Scholar Crossref Search ADS WorldCat Harvey M. , Gauthier D., Munro J. 1998 . Temporal changes in the composition and abundance of the macro-benthic invertebrate communities at dredged material disposal sites in the Anse h Beaufils, Baie des Chaleurs, Eastern Canada . Marine Pollution Bulletin , 36 : 41 – 55 . Google Scholar Crossref Search ADS WorldCat He W. , Chen M., Schlautman M. A., Hur J. 2016 . Dynamic exchanges between DOM and POM pools in coastal and inland aquatic ecosystems: a review . Science of the Total Environment , 551-552 : 415 – 428 . Google Scholar Crossref Search ADS PubMed WorldCat Hendrick V. J. , Hutchison Z. L., Last K. S. 2016 . Sediment Burial Intolerance of Marine Macroinvertebrates . PLoS One , 11 : e0149114 . Google Scholar Crossref Search ADS PubMed WorldCat Hewitt J. E. , Thrush S. F., Dayton P. K., Bonsdorff E. 2007 . The effect of spatial and temporal heterogeneity on the design and analysis of empirical studies of scale-dependent systems . The American Naturalist , 169 : 398 – 408 . Google Scholar Crossref Search ADS PubMed WorldCat Hicks N. , Ubbara G. R., Silburn B., Smith H. E. K., Kröger S., Parker E. R., Sivyer D. et al. 2017 . Oxygen dynamics in shelf seas sediments incorporating seasonal variability . Biogeochemistry , 135 : 35 – 13 . Google Scholar Crossref Search ADS PubMed WorldCat Hiddink J. G. , Jennings S., Kaiser M. J., Queirós A. M., Duplisea D. E., Piet G. J. 2006 . Cumulative impacts of seabed trawl disturbance on benthic biomass, production, and species richness in different habitats . Canadian Journal of Fisheries and Aquatic Sciences , 63 : 721 – 736 . Google Scholar Crossref Search ADS WorldCat Hiddink J. G. , Jennings S., Kaiser M. J. 2006 . Indicators of the ecological impact of bottom-trawl disturbance on seabed communities . Ecosystems , 9 : 1190 – 1199 . Google Scholar Crossref Search ADS WorldCat Howarth M. J. , Dyer, K. R., Joint, I. R., Hydes, D. J., Purdie, D. A., Edmunds, H., Jones, J. E. et al. 1993 . Seasonal cycles and their spatial variability . Philosophical Transactions of the Royal Society A , 343 : 383 – 403 . Google Scholar OpenURL Placeholder Text WorldCat Howarth R. W. 1988 . Nutrient limitation of net primary production in marine ecosystems . Annual Review of Ecology and Systematics , 19 : 89 – 110 . Google Scholar Crossref Search ADS WorldCat Huettel A. , Ziebis W., Forster S. 1996 . Flow-induced uptake of particulate matter in permeable sediments . Limnology and Oceanography , 41 : 309 – 322 . Google Scholar Crossref Search ADS WorldCat Huettel M. , Berg P., Kostka J. E. 2014 . Benthic exchange and biogeochemical cycling in permeable sediments . Annual Review of Marine Science , 6 : 23 – 51 . Google Scholar Crossref Search ADS PubMed WorldCat Huettel M. , Gust G. 1992 . Impact of bioroughness on interfacial solute exchange in permeable sediments . Marine Ecology Progress Series , 89 : 253 – 267 . Google Scholar Crossref Search ADS WorldCat Hutchinson P. A. , Webster I. T. 1998 . Solute uptake in aquatic sediments due to current-obstacle interactions . Journal of Environmental Engineering , 124 : 419 – 426 . Google Scholar Crossref Search ADS WorldCat Inthorn M. , Wagner T., Scheeder G., Zabel M. 2006 . Lateral transport controls distribution, quality, and burial of organic matter along continental slopes in high-productivity areas . Geology , 34 : 205 – 208 . Google Scholar Crossref Search ADS WorldCat Jones C. G. , Lawton J. H., Shachak M. 1994 . Organisms as ecosystem organisms engineers . Oikos , 69 : 373 – 386 . Google Scholar Crossref Search ADS WorldCat Julien P. Y. 2010 Erosion and Sedimentation . Cambridge University Press, Cambridge, UK . Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Justic D. 1995 . Changes in nutrient structure of river-dominated coastal waters: stoichiometric nutrient balance and its consequences . Estuarine, Coastal and Shelf Science , 1 : 339 – 356 . Google Scholar Crossref Search ADS WorldCat Kalnejais L. H. , Martin W. R., Bothner M. H. 2010 . The release of dissolved nutrients and metals from coastal sediments due to resuspension . Marine Chemistry , 121 : 224 – 235 . Google Scholar Crossref Search ADS WorldCat Kassem H. , Thompson C. E. L., Amos C. L., Townend I. H. 2015 . Wave-induced coherent turbulence structures and sediment resuspension in the nearshore of a prototype-scale sandy barrier beach . Continental Shelf Research , 109 : 78 – 94 . Google Scholar Crossref Search ADS WorldCat Kautsky N. , Evans S. 1987 . Role of biodeposition by Mytilus edulis in the circulation of matter and nutrients in a Baltic coastal ecosystem . Marine Ecology Progress Series , 38 : 201 – 212 . Google Scholar Crossref Search ADS WorldCat Kingston P. F. 1992 . Impact of offshore oil production installations on the benthos of the North Sea . ICES Journal of Marine Science , 49 : 45 – 53 . Google Scholar Crossref Search ADS WorldCat Komar P. D. 1976 a. Boundary layer flow under steady unidirectional currents. In Marine Sediment Transport and Environmental Management , pp. 91 – 106 . Ed. by Stanley, D. J., and Swift, D. J. P. Wiley Ltd, Corvallis . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Komar P. D. 1976 b The transport of cohesionless sediments on continental shelves. In Marine Sediment Transport and Environmental Management , pp. 107 – 125 . Ed. by Stanley, D. J., and Swift, D. J. P. Wiley Ltd, Corvallis . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Krishnamurthy A. , Moore J. K., Mahowald N., Luo C., Zender C. S. 2010 . Impacts of atmospheric nutrient inputs on marine biogeochemistry . Journal of Geophysical Research , 115 : 1 – 13 . Google Scholar Crossref Search ADS WorldCat Kristensen E. 1988 . Benthic fauna and biogeochemical processes in marine sediments: microbial activities and fluxes . In Nitrogen Cycling in Coastal Marine Environments, pp. 275–300. Ed. by Blackburn, T. H. and Sorensen, I . John Wiley & Sons Ltd, USA. Google Scholar OpenURL Placeholder Text WorldCat Kristensen E. 2001 . Impact of polychaetes (Nereis spp. and Arenicola marina) on carbon biogeochemistry in coastal marine sediments . Geochemical Transactions , 2 : 92 . Google Scholar Crossref Search ADS PubMed WorldCat Kristensen E. , Penha-Lopes G., Delefosse M., Valdemarsen T., Quintana C. O., Banta G. T. 2012 . What is bioturbation? The need for a precise definition for fauna in aquatic sciences . Marine Ecology Progress Series , 446 : 285 – 302 . Google Scholar Crossref Search ADS WorldCat Lau Y. L. , Krishnappan B. G. 1994 . Does reentrainment occur during cohesive sediment settling? Journal of Hydraulic Engineering , 120 : 236 – 245 . Google Scholar Crossref Search ADS WorldCat Lawton J. H. 1999 . Are there general laws in ecology? Introduction and definitions . Oikos , 84 : 177 – 192 . Google Scholar Crossref Search ADS WorldCat Lindqvist S. 2014 . Transport by Benthic Macrofauna: Functional Classification and Biogeochemical Response , 1st edn. Ed. by Trychteam A.. Department of Chemistry and Molecular Biology , Bohus . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Lohse L. , Epping E. H. G., Helder W., van Raaphorst W. 1996 . Oxygen pore water profiles in continental shelf sediments of the North Sea: turbulent versus molecular diffusion . Marine Ecology Progress Series , 145 : 63 – 75 . Google Scholar Crossref Search ADS WorldCat Lundgaard A. S. B. , Treusch A. H., Stief P., Thamdrup B., Glud R. N. 2017 . Nitrogen cycling and bacterial community structure of sinking and aging diatom aggregates . Aquatic Microbial Ecology , 79 : 85 – 99 . Google Scholar Crossref Search ADS WorldCat Maa J. P. , Kwon J. 2007 . Using ADV for cohesive sediment settling velocity measurements . Estuarine Coastal and Shelf Science , 73 : 351 – 354 . Google Scholar Crossref Search ADS WorldCat MacIntyre S. 1998 . Turbulent mixing and resource supply to phytoplankton . Physical Processes in Lakes and Oceans , 54 : 561 – 590 . Google Scholar Crossref Search ADS WorldCat Madsen O. S. , Wright L. D., Boon J. D., Chisholm T. A. 1993 . Wind stress, bed roughness and sediment suspension on the inner shelf during an extreme storm event . Continental Shelf Research , 13 : 1303 – 1324 . Google Scholar Crossref Search ADS WorldCat Maire O. , Duchêne J. C., Rosenberg R., de Mendonça J. B., Grémare A. 2006 . Effects of food availability on sediment reworking in Abra ovata and A. nitida . Marine Ecology Progress Series , 319 : 135 – 153 . Google Scholar Crossref Search ADS WorldCat Malan D. E. , McLachlan A. 1991 . In situ benthic oxygen fluxes in a nearshore coastal marine system: a new approach to quantify the effect of wave action . Marine Ecology Progress Series , 73 : 69 – 81 . Google Scholar Crossref Search ADS WorldCat Malarkey J. , Baas J. H., Hope J. A., Aspden R. J., Parsons D. R., Peakall J., Paterson D. M. et al. 2015 . The pervasive role of biological cohesion in bedform development . Nature Communications , 6 : 1 – 6 . Google Scholar Crossref Search ADS WorldCat Manning A. J. , Bass S. J. 2006 . Variability in cohesive sediment settling fluxes: observations under different estuarine tidal conditions . Marine Geology , 235 : 177 – 192 . Google Scholar Crossref Search ADS WorldCat Marcus N. H. , Boero F. 1998 . Minireview: The importance of benthic-pelagic coupling and the forgotten role of life cycles in coastal aquatic systems . Limnology and Oceanography , 43 : 763 – 768 . Google Scholar Crossref Search ADS WorldCat Mari X. , Rochelle-Newall E., Torréton J.-P., Pringault O., Jouon A., Migon C. 2007 . Water residence time: a regulatory factor of the DOM to POM transfer efficiency . Limnology and Oceanography , 52 : 808 – 819 . Google Scholar Crossref Search ADS WorldCat Martín J. , Puig P., Palanques A., Masqué P., García-Orellana J. 2008 . Effect of commercial trawling on the deep sedimentation in a Mediterranean submarine canyon . Marine Geology , 252 : 150 – 155 . Google Scholar Crossref Search ADS WorldCat Meadows P. S. , Meadows A., Murray J. M. H. 2012 . Geomorphology Biological modifiers of marine benthic seascapes: their role as ecosystem engineers . Geomorphology 157–158 : 31 – 48 . Google Scholar Crossref Search ADS WorldCat Mecozzi M. , Pietroletti M., Conti M. E. 2008 . The investigation of compositional and structural characteristics of natural marine organic matter: a review . International Journal of Environment and Pollution , 32 : 527 – 549 . Google Scholar Crossref Search ADS WorldCat Mehta A. J. 1988 . Laboratory studies on cohesive sediment deposition and erosion. In Physical Processes in Estuaries , pp. 427 – 445 . Springer , Berlin . doi: 10.1007/978-3-642-73691-9_21. Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Mermillod-Blondin F. , Rosenberg R., François-Carcaillet F., Norling K., Mauclaire L. 2004 . Influence of bioturbation by three benthic infaunal species on microbial communities and biogeochemical processes in marine sediment . Aquatic Microbial Ecology , 36 : 271 – 284 . Google Scholar Crossref Search ADS WorldCat Mermillod-Blondin F. , Rosenberg R. 2006 . Ecosystem engineering: the impact of bioturbation on biogeochemical processes in marine and freshwater benthic habitats . Aquatic Science , 68 : 434 – 442 . Google Scholar Crossref Search ADS WorldCat Middelburg J. J. 2017 . To the bottom of carbon processing at the seafloor: towards integration of geological, geochemical and ecological concepts (Vladimir Ivanovich Vernadsky Medal Lecture), Geophysical Research Abstracts, 19: 2283 . Mikkelsen O. A. , Pejrup M. 2000 . In situ particle size spectra and density of particle aggregates in a dredging plume . Marine Geology , 170 : 443 – 459 . Google Scholar Crossref Search ADS WorldCat Milliman J. D. , Farnsworth K. L. eds. 2013 . River discharge to the coastal ocean: a global synthesis. Cambridge University Press, Cambridge, UK . Montserrat F. , Van Colen C., Provoost P., Milla M., Ponti M., Van den Meersche K., Ysebaert T. et al. 2009 . Sediment segregation by biodiffusing bivalves . Estuarine, Coastal and Shelf Science , 83 : 379 – 391 . Google Scholar Crossref Search ADS WorldCat Moon V. , de Lange, W., Warren, S., and Healy, T. 1994 . Post-disposal behaviour of sandy dredged material at an open-water, inner shelf disposal site . Journal of Coastal Research , 10 : 651 – 662 . Google Scholar OpenURL Placeholder Text WorldCat Morin J. , Morse J. W. 1999 . Ammonium release from resuspended sediments in the Laguna Madre estuary . Marine Chemistry , 65 : 97 – 110 . Google Scholar Crossref Search ADS WorldCat Morris A. W. , Howarth M. J. 1998 . Bed stress induced sediment resuspension (SERE 88/89) . Continental Shelf Research , 18 : 1203 – 1213 . 5. Google Scholar Crossref Search ADS WorldCat Morse J. W. 1994 . Interactions of trace metals with authigenic sulfide minerals: implications for their bioavailability . Marine Chemistry , 46 : 1 – 6 . Google Scholar Crossref Search ADS WorldCat Morton J. W. 1977 . Ecological Effects of Dredging and Dredge Spoil Disposal: A Literature Review . U.S. Fish and Wildlife Service, Virginia, USA . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Narita H. , Harada K., Tsunogai S. 1990 . Lateral transport of sediment particles in the Okinawa Trough determined by natural radionuclides . Geochemical Journal , 24 : 207 – 216 . Google Scholar Crossref Search ADS WorldCat Navarrete S. A. , Wieters E. A., Broitman B. R., Castilla J. C. 2005 . Scales of benthic—pelagic coupling and the intensity of species interactions: from recruitment limitation to top-down control . Proceedings of the National Academy of Sciences of the United States of America , 102 : 18046 – 18051 . Google Scholar Crossref Search ADS PubMed WorldCat Nowell A. R. , Jumars P. A., Eckman J. E. 1981 . Effects of biological activity on the entrainment of marine sediments . Marine Geology , 42 : 133 – 153 . Google Scholar Crossref Search ADS WorldCat Oberle F. K. J. , Storlazzi C. D., Hanebuth T. J. J. 2016 . What a drag: quantifying the global impact of chronic bottom trawling on continental shelf sediment . Journal of Marine Systems , 159 : 109 – 119 . Google Scholar Crossref Search ADS WorldCat Paarlberg A. J. , Knaapen M. A. F., de Vries M. B., Hulscher S. J. M. H., Wang Z. B. 2005 . Biological influences on morphology and bed composition of an intertidal flat . Estuarine, Coastal and Shelf Science , 64 : 577 – 590 . Google Scholar Crossref Search ADS WorldCat Packard T. T. , Gómez M. 2013 . Modeling vertical carbon flux from zooplankton respiration . Progress in Oceanography , 110 : 59 – 68 . Google Scholar Crossref Search ADS WorldCat Palanques a. , Guillén J., Puig P. 2001 . Impact of bottom trawling on water turbidity and muddy sediment of an unfished continental shelf . Limnology and Oceanography , 46 : 1100 – 1110 . Google Scholar Crossref Search ADS WorldCat Parsons D. R. , Schindler R. J., Hope J. A., Malarkey J., Baas J. H., Peakall J., Manning A. J. et al. 2016 . The role of biophysical cohesion on subaqueous bed form size . Geophysical Research Letters , 43 : 1566 – 1573 . Google Scholar Crossref Search ADS PubMed WorldCat Pilskaln C. H. , Churchill J. H., Mayer L. M. 1998 . Resuspension of sediment by bottom trawling in the Gulf of Maine and potential geochemical consequences . Conservation Biology , 12 : 1223 – 1229 . Google Scholar Crossref Search ADS WorldCat Pomeroy L. R. , Deibel D. O. N. 1986 . Temperature regulation of bacterial activity during the spring bloom in Newfoundland Coastal Waters . Science Reports , 233 : 359 – 361 . Google Scholar OpenURL Placeholder Text WorldCat Pusceddu A. , Grémare A., Escoubeyrou K., Amouroux J. M., Fiordelmondo C., Danovaro R. 2005 . Impact of natural (storm) and anthropogenic (trawling) sediment resuspension on particulate organic matter in coastal environments . Continental Shelf Research , 25 : 2506 – 2520 . Google Scholar Crossref Search ADS WorldCat Qiao L. L. , Wang Y. Z., Li G. X., Deng S. G., Liu Y., Mu L. 2011 . Distribution of suspended particulate matter in the northern Bohai Bay in summer and its relation with thermocline . Estuarine, Coastal and Shelf Science , 93 : 212 – 219 . Google Scholar Crossref Search ADS WorldCat Queirós A. M. , Stephens N., Widdicombe S., Tait K., McCoy S. J., Ingels J., Rühl S., et al. 2019 . Connected macroalgal-sediment systems: blue carbon and food webs in the deep coastal ocean . Ecological Monographs , 89 : 1 – 21 . Google Scholar Crossref Search ADS WorldCat Queiros A. M. , Taylor, P., Cowles, A., Reynolds, A., Widdicombe, S., and Stahl, H. 2015 . Optical assessment of impact and recovery of sedimentary pH profiles in ocean acidification and carbon capture and storage research . International Journal of Greenhouse Gas Control , 38 : 110 – 120 . Google Scholar Crossref Search ADS WorldCat Queirós A. M. , Hiddink J. G., Kaiser M. J., Hinz H. 2006 . Effects of chronic bottom trawling disturbance on benthic biomass, production and size spectra in different habitats . Journal of Experimental Marine Biology and Ecology , 335 : 91 – 103 . Google Scholar Crossref Search ADS WorldCat Queirós A. M. et al. 2011 . Context dependence of marine ecosystem engineer invasion impacts on benthic ecosystem functioning . Biological Invasions , 13 : 1059 – 1075 . Google Scholar Crossref Search ADS WorldCat Queirós A. M. , Stephens N., Cook R., Ravaglioli C., Nunes J., Dashfield S., Harris C. et al. 2015 . Can benthic community structure be used to predict the process of bioturbation in real ecosystems? Progress in Oceanography , 137 : 559 – 569 . Google Scholar Crossref Search ADS WorldCat Rasmussen H. , Jorgensen B. B. 1992 . Microelectrode studies of seasonal oxygen uptake in a coastal sediment: role of molecular diffusion . Marine Ecology Progress Series , 81 : 289 – 303 . Google Scholar Crossref Search ADS WorldCat Reichardt W. 1988 . Impact of bioturbation by Arenicola marina on microbiological parameters in intertidal sediments . Marine Ecology Progress Series , 44 : 149 – 158 . Google Scholar Crossref Search ADS WorldCat Revsbech N. P. , Jorgensen B. B., Blackburn T. H. 1980 . Oxygen in the sea bottom measured with a microelectrode . Science , 207 : 1355 – 1356 . Google Scholar Crossref Search ADS WorldCat Rusch A. , Huettel M., Forster S. 2000 . Particulate organic matter in permeable marine sands—dynamics in time and depth . Estuarine Coastal and Shelf Science , 51 : 399 – 414 . Google Scholar Crossref Search ADS WorldCat Rysgaard S. 1994 . Oxygen regulation of nitrification and denitrification in sediments. Limnology and Oceanography, 39 : 1643 – 1652 . Saulnier I. , Mucci A. 2000 . Trace metal remobilization following the resuspension of estuarine sediments: Saguenay Fjord, Canada . Applied Geochemistry , 15 : 191 – 222 . Google Scholar Crossref Search ADS WorldCat Schlüter M. , Sauter E., Hansen H.-P., Suess E. 2000 . Seasonal variations of bioirrigation in coastal sediments: modelling of field data . Geochimica et Cosmochimica Acta , 64 : 821 – 834 . Google Scholar Crossref Search ADS WorldCat Schoellhamer D. H. 2002 . Comparison of the basin-scale effect of dredging operations and natural estuarine processes on suspended sediment concentration . Estuaries , 25 : 488 – 495 . Google Scholar Crossref Search ADS WorldCat Schratzberger M. , Lampadariou N., Somerfield P. J., Vandepitte L., Vanden Berghe E. 2009 . The impact of seabed disturbance on nematode communities: linking field and laboratory observations . Marine Biology , 156 : 709 – 724 . Google Scholar Crossref Search ADS WorldCat Sciberras M. , Parker R., Powell C., Robertson C., Kröger S., Bolam S., Geert Hiddink J. et al. 2016 . Impacts of bottom fishing on the sediment infaunal community and biogeochemistry of cohesive and non-cohesive sediments . Limnology and Oceanography , 61 : 2076 – 2089 . Google Scholar Crossref Search ADS WorldCat Seidel M. , Beck M., Greskowiak J., Riedel T., Waska H., Suryaputra I. N. A., Schnetger B. et al. 2015 . Benthic-pelagic coupling of nutrients and dissolved organic matter composition in an intertidal sandy beach . Marine Chemistry , 176 : 150 – 163 . Google Scholar Crossref Search ADS WorldCat Simons D. B. , Şentürk F. 1992 . Sediment Transport Technology: Water and Sediment Dynamics . Water Resources Publications, Virginia, USA . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Smith S. D. A. , Rule M. J. 2001 The effects of dredge-spoil dumping on a shallow water soft-sediment community in the Solitary Islands Marine Park, NSW, Australia . Marine Pollution Bulletin , 42 : 1040 – 1048 . Google Scholar Crossref Search ADS PubMed WorldCat Snelgrove P. V. R. , Austen, M. C, Hawkins, S. J., Iliffe, T. M., Kneib, R. T., Levin, L. A., Weslawski, J. M., et al. 1999 . Vulnerability of marine sedimentary ecosystem services to human activities. In Sustaining Biodiversity and Ecosystem Services in Soils and Sediments. SCOPE 64 , pp. 161 – 190 . Ed. by D. Wall. Island Press , London . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Snelgrove P. V. R. 1999 . Getting to the bottom of marine biodiversity: sedimentary habitats . Bioscience , 49 : 129 – 138 . Google Scholar Crossref Search ADS WorldCat Snelgrove P. V. R. et al. 2018 . Global carbon cycling on a heterogeneous seafloor . Trends in Ecology and Evolution , 33 : 96 – 105 . Google Scholar Crossref Search ADS PubMed WorldCat Solan M. , Wigham B. D., Hudson I. R., Kennedy R., Coulon C. H., Norling K., Nilsson H. C. et al. 2004 . In situ quantification of bioturbation using time-lapse fluorescent sediment profile imaging (f-SPI), luminophore tracers and model simulation . Marine Ecology Progress Series , 271 : 1 – 12 . Google Scholar Crossref Search ADS WorldCat Stolzenbach K. D. , Elimelech M. 1994 . The effect of particle density on collisions between sinking particles: implications for particle aggregation in the ocean . Deep Sea Research Part I: Oceanographic Research Papers , 41 : 469 – 483 . Google Scholar Crossref Search ADS WorldCat Sun R. , Xiao H., Sun H. 2018 . Investigating the settling dynamics of cohesive silt particles with particle-resolving simulations. Advances in Water Resources, 111 : 406 – 422 . Sutherland T. F. , Amos C. L., Grant J. 1998 . The effect of buoyant biofilms on the erodibility of sublittoral sediments of a temperate microtidal estuary . Limnology and Oceanography , 43 : 225 – 235 . Google Scholar Crossref Search ADS WorldCat Taigbenu A. , Liggett J. A. 1986 . An integral solution for the diffusion‐advection equation . Water Resources Research , 22 : 1237 – 1246 . Google Scholar Crossref Search ADS WorldCat Tait K. , Airs R. L., Widdicombe C. E., Tarran G. A., Jones M. R., Widdicombe S. 2015 . Dynamic responses of the benthic bacterial community at the Western English Channel observatory site L4 are driven by deposition of fresh phytodetritus . Progress in Oceanography , 137 : 546 – 558 . Google Scholar Crossref Search ADS WorldCat Thrush S. F. , Hewitt J. E., Cummings V. J., Dayton P. K. 1995 . The impact of habitat disturbance by scallop dredging on marine benthic communities: what can be predicted from the results of experiments? Marine Ecology Progress Series , 129 : 141 – 150 . Google Scholar Crossref Search ADS WorldCat Thrush S. F. , Hewitt J. E., Dayton P. K., Coco G., Lohrer A. M., Norkko A., Norkko J. et al. 2009 . Forecasting the limits of resilience: integrating empirical research with theory . Proceedings of the Royal Society of Biology , 276 : 3209 – 3217 . Google Scholar Crossref Search ADS WorldCat Thrush S. F. , Pridmore R. D., Hewitt J. E. 1996 . Impacts on soft-sediment macrofauna. In Detecting Ecological Impacts , pp. 49 – 66 . Ed. by Schmitt, R. J., and Osenberg, C. W. Elsevier, Cambridge, MA . doi: 10.1016/b978-012627255-0/50006-9. Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Tiano J. C. , Witbaard R., Bergman M. J. N., van Rijswijk P., Tramper A., van Oevelen D., Soetaert K. et al. 2019 . Acute impacts of bottom trawl gears on benthic metabolism and nutrient cycling . ICES Journal of Marine Science , 76 : 1917 – 1930 . Google Scholar Crossref Search ADS WorldCat Townsend D. W. , Mayer L. M., Dortch Q., Spinrad R. W. 1992 . Vertical structure and biological activity in the bottom nepheloid layer of the Gulf of Maine . Continental Shelf Research , 12 : 367 – 387 . Google Scholar Crossref Search ADS WorldCat Tsai C. , Iacobellis S., Lick W. 1987 . Flocculation of fine-grained lake sediments due to a uniform shear stress . Journal of Great Lakes Research , 13 : 135 – 146 . Google Scholar Crossref Search ADS WorldCat Van Der Kamp G. , Gale J. E. 1983 . Theory of earth tide and barometric effects in porous formations with compressible grains . Water Resources Research , 9 : 538 – 544 . Google Scholar Crossref Search ADS WorldCat Van Duyl F. C. , Kop A. J., Kok A., Sandee A. J. J. 1992 . The impact of organic matter and macrozoobenthos on bacterial and oxygen variables in marine sediment boxcosms . Netherlands Journal of Sea Research , 29 : 343 – 355 . Google Scholar Crossref Search ADS WorldCat Van Hoey G. , Guilini K., Rabaut M., Vincx M., Degraer S. 2008 . Ecological implications of the presence of the tube-building polychaete Lanice conchilega on soft-bottom benthic ecosystems . Marine Biology , 154 : 1009 – 1019 . Google Scholar Crossref Search ADS WorldCat Volkenborn N. , Polerecky L., Hedtkamp S. I. C., van Beusekom J. E. E., de Beer D. 2007 . Bioturbation and bioirrigation extend the open exchange regions in permeable sediments . Limnology and Oceanography , 52 : 1898 – 1909 . Google Scholar Crossref Search ADS WorldCat Volkenborn N. , Polerecky L., Wethey D. S., Woodin S. A. 2010 . Oscillatory porewater bioadvection in marine sediments induced by hydraulic activities of Arenicola marina . Limnology and Oceanography , 55 : 1231 – 1247 . Google Scholar Crossref Search ADS WorldCat Volkenborn N. , Polerecky L., Wethey D. S., DeWitt T. H., Woodin S. A. 2012 . Hydraulic activities by ghost shrimp Neotrypaea californiensis induce oxic-anoxic oscillations in sediments . Marine Ecology Progress Series , 455 : 141 – 156 . Google Scholar Crossref Search ADS WorldCat Waldbusser G. G. , Marinelli R. L., Whitlatch R. B., Visscher P. T. 2004 . The effects of infaunal biodiversity on biogeochemistry of coastal marine sediments . Limnology and Oceanography , 49 : 1482 – 1492 . Google Scholar Crossref Search ADS WorldCat Walsh J. J. 1991 . Importance of continental margins in the marine biogeochemical cycling of carbon and nitrogen . Nature , 350 : 53 – 55 . Google Scholar Crossref Search ADS WorldCat Webster I. T. , Norquay S. J., Ross F. C., Wooding R. A. 1996 . Solute exchange by convection within estuarine sediments . Estuarine, Coastal and Shelf Science , 42 : 171 – 183 . Google Scholar Crossref Search ADS WorldCat Wethey D. S. , Woodin S. A. 2005 . Infaunal hydraulics generate porewater pressure signals . Biological Bulletin , 209 : 139 – 145 . Google Scholar Crossref Search ADS PubMed WorldCat Widdicombe S. , Austen M. C. 1999 . Mesocosm investigation into the effects of bioturbation on the diversity and structure of a subtidal macrobenthic community . Marine Ecology Progress Series , 189 : 181 – 193 . Google Scholar Crossref Search ADS WorldCat Widdows J. , Brinsley M. D., Bowley N., Barrett C. 1998 a. A benthic annular flume for in situ measurement of suspension feeding/biodeposition rates and erosion potential of intertidal cohesive sediments . Estuarine Coastal and Shelf Science , 46 : 27 – 38 . Google Scholar Crossref Search ADS WorldCat Widdows J. , Brown S., Brinsley M. D., Salkeld P. N., Elliott M. 2000 . Temporal changes in intertidal sediment erodability: influence of biological and climatic factors . Continental Shelf Research , 20 : 1275 – 1289 . Google Scholar Crossref Search ADS WorldCat Widdows J. , Brinsley M. D., Salkeld P. N., Elliott M. 1998 b. Use of annular flumes to determine the influence of current velocity and bivalves on material flux at the sediment-water interface . Estuaries , 21 : 552 – 559 . Google Scholar Crossref Search ADS WorldCat Widdows J. , Brinsley M., Elliott M. 1998 c. Use of in situ flume to quantify particle flux (biodeposition rates and sediment erosion) for an intertidal mudflat in relation to changes in current velocity and benthic macrofauna . Geological Society, London, Special Publications , 139 : 85 – 97 . Google Scholar Crossref Search ADS WorldCat Wildish D. J. , Thomas M. L. H. 1985 . Effects of dredging and dumping on benthos of Saint John Harbour, Canada . Marine Environmental Research , 15 : 45 – 57 . Google Scholar Crossref Search ADS WorldCat Williams J. , le B., del Giorgio P. A. 2005 . Respiration in aquatic ecosystems: history and background. In Respiration in Aquatic Ecosystems , 1st edn, pp. 1 – 17 . Ed. by del Giorgio P. A., Williams J. B.. Oxford University Press , New York . Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Williams R. G. , Follows M. J. 1998 . The Ekman transfer of nutrients and maintenance of new production over the North Atlantic . Deep Sea Research Part I: Oceanographic Research Papers , 45 : 461 – 489 . Google Scholar Crossref Search ADS WorldCat Winterwerp J. C. 2011 . The Physical Analyses of Muddy Sedimentation Processes, Water and Fine Sediment Circulation, Treatise on Estuarine and Coastal Science . Elsevier Inc, Cambridge, MA . doi: 10.1016/B978-0-12-374711-2.00214-X. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Winterwerp J. C. , Kesteren W. G. M. 2004 . Introduction to the Physics of Cohesive Sediment in the Marine Environment . Elsevier, Exeter, UK . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Yang Y. , Aplin A. C. 2010 . A permeability-porosity relationship for mudstones . Marine and Petroleum Geology , 27 : 1692 – 1697 . Google Scholar Crossref Search ADS WorldCat Yazdani Foshtomi M. , Braeckman U., Derycke S., Sapp M., Van Gansbeke D., Sabbe K., Willems A. et al. 2015 . The link between microbial diversity and nitrogen cycling in marine sediments is modulated by macrofaunal bioturbation . PLoS One , 10 : 1– 20 . Google Scholar OpenURL Placeholder Text WorldCat Yingst J. Y. , Rhoads D. C. 1980 . The role of bioturbation in the enhancement of bacterial growth rates in marine sediments. In Marine Benthic Dynamics , pp. 407 – 421 . University of South Carolina Press , Columbia . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Zhang Q. , Warwick R. M., McNeill C. L., Widdicombe C. E., Sheehan A., Widdicombe S. 2015 . An unusually large phytoplankton spring bloom drives rapid changes in benthic diversity and ecosystem function . Progress in Oceanography , 137 : 533 – 545 . Google Scholar Crossref Search ADS WorldCat Ziebis W. , Huettel M., Forster S. 1996 . Impact of biogenic sediment topography on oxygen fluxes in permeable seabeds . Marine Ecology Progress Series , 140 : 227 – 237 . Google Scholar Crossref Search ADS WorldCat © International Council for the Exploration of the Sea 2020. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. © International Council for the Exploration of the Sea 2020.

Dolan, John, R

doi: 10.1093/icesjms/fsaa053pmid: N/A

Abstract William Beebe (1877–1962) was a very popular 20th century naturalist and an early proponent of studying all organisms in a habitat. Beebe’s deep-sea work began with his Arcturus Oceanographic Expedition in 1925 with sampling closely modelled on the Michael Sars deep-sea expedition. Dissatisfied with ship-based sampling of stations for a few days at best, he established a field laboratory in Bermuda to do intensive deep-water sampling. From 1929 to 1934, plankton net tows were carried out at the same site, over several months each year, totalling over 1500 net tows in deep waters. Here, the sampling efforts and results are reviewed from both the Arcturus Expedition and the Bermuda station. Study of the deep-sea samples yielded 43 scientific articles, published from 1926 to 1952, on a large variety of taxa. Beebe is still a popular figure connected in the public view with deep-sea exploration from his famous Bathysphere dives at the Bermuda site. However, his name rarely, if ever, appears in academic reviews of deep-sea biology or deep-sea expeditions. This study is an attempt to draw attention to Beebe’s considerable scientific deep-sea work and provide some speculation as to why his contributions might be neglected. Introduction to William Beebe Charles William Beebe, generally known as William Beebe, had a long and unusually full and productive life as attested to in book-length biographies of Beebe (Welker, 1975; Gould, 2004), and the detailed bibliography “William Beebe, an Annotated Bibliography” (Berra, 1977). There is also a plethora of short biographies in popular books (e.g. Cullen, 2006; Ballard and Hively, 2017; Morell, 2019). However, the most authoritative account of Beebe’s life is that of Gould (2004) as it is based on original source material, unavailable before the death of Beebe’s second wife. The following brief account of Beebe’s life, situating his deep-sea studies, is based on Gould’s (2004) biography. Beebe, from a young age, was drawn to natural history. By age 14, he was an avid collector of birds and their eggs, insects, shells, and minerals. Age at 16, his last journal entry for the year 1893 was “To be a Naturalist is better than to be a King”, and by age 17, he had his first article, on a bird, published in “Harper’s Young People” (Beebe, 1895). An exceptional student in high school, he was given advance placement at Columbia University, skipping the first year. At Columbia, Henry Osborn who would be a large figure in his life supervised him. Osborn was not only Chair of the Zoology Department but also the president of the American Museum of Natural History as well as the head of the New York Zoological Society. Beebe split his days between lectures and labs at the University and days at the American Museum of Natural History. In autumn 1899, Osborne told Beebe that he had completed all the requirements for his degree in zoology except for a maths class he had been avoiding. Osborn gave Beebe a choice between staying in school for another year to complete his missing class or he could go with Osborn to the new, still under construction, Bronx Zoo of the Zoological Society and apply for a job as an assistant curator of birds. The choice was quickly made. Beebe would spend his entire working life with the New York Zoological Society (now the Wildlife Conservation Society) and never would earn a college degree. Beebe’s career can be roughly divided into four periods. The first period of 1899–1908 consists of his early years as curator of birds. In 1908, with the aid of Osborn, he won a status similar to that of the staff scientists at the American Museum of Natural History with 2 months salary paid to conduct research. Thus, the second period, 1908–1916, was the start of long expeditions, primarily to South American jungles in this first period but also a year spent investigating pheasants worldwide. He later produced a monumental multi-volume monograph on pheasants regarded as one of the “vital books of science” (Bay, 1948). By 1916, he secured funding for the establishment of a field station in British Guiana, a facility where intensive study of tropical life could be conducted over long periods of time. The third period of 1916–1924 then was primarily tropical fauna studies. During this period, Beebe’s position evolved from Curator to Head of the Department of Tropical Research. Work conducted during this period has led to Beebe’s being declared the “Father of Neotropical Ecology” (Mendyk, 2014). It also included an expedition to the Galapagos, financed by a wealthy zoo supporter; the expedition produced a best seller “Galapagos: World’s End” (Beebe, 1924). During this period, he was awarded the Daniel Giraud Elliott Medal of National Academy of Science, an award for remarkable achievements in zoology. Later recipients of the prestigious award were G. Evelyn Hutchinson, Ernst Mayr, and Henry Bigelow. The fourth period of 1925–1939 is that of Beebe’s field studies of marine fauna, the focus of this article. It begins with the oceanographic voyage of the Arcturus and ended with the approach of World War 2. The Arcturus voyage inspired Beebe to establish a field station devoted to deep-sea work. The Nonsuch field station in Bermuda was founded, and intensive deep-sea studies were carried out from 1929 to 1935. It was also the site of the famous Bathysphere dives. These dives, one of which was broadcast on radio live, were celebrated in Science (Anon, 1930a) and Nature (Anon, 1930b), detailed in his book Half Mile Down (Beebe, 1934), reported by Beebe in Science (Beebe, 1932c), and in lavish articles in the National Geographic Magazine. The activities of this period, exclusive of the bathysphere dives, are dealt with in detail here in this article. The fifth and last period, from 1945 to his death in 1962, was a return to the studies of tropical fauna from, but from another field station, one he installed in Venezuela. Beebe’s deep-sea work is often over-looked Beebe was immensely popular in his time (Gould, 2004) and still in today’s popular books is credited not only for drawing attention to the deep-sea with the Bathysphere dives but is also credited with being a pioneer ecologist because of his systematic sampling of the deep-sea (e.g. Cullen, 2006; Ballard and Hively, 2017; Morell, 2019). In many academic works, however, the considerable results (which will be shown below) from the Arcturus Expedition and the Nonsuch sampling are simply not mentioned. For example, in Mills’ book History of Biological Oceanography (Mills, 1989), one finds no mention, nor in Hedgpeth’s article “History of Pacific Oceanography” (Hedgpeth, 1974). Similarly, in their review of the oceanography of the Eastern Tropical Pacific, Fiedler and Lavin (2006) mention only Beebe’s popular books with no mention of the research reports from the Arcturus Oceanographic Expedition. Likewise, a history of deep-sea biology (Mills, 1983), a history of deep-sea expeditions (Wüst, 1964), and deep-sea plankton studies (Kimor, 2002) contain no mention of Beebe’s work, nor that of his colleagues. Even the general comprehensive book on deep-sea organisms of Marshall (Marshall, 1979) cites but one of Beebe’s many articles on deep-sea fish. Histories of marine ecology give a nod to Beebe but not the deep-sea work. Riedl’s (1980) review of the development of marine ecology placed Beebe’s work in the stage “before its time” but only in reference to revealing “the splendours of tropical shallow seas”. Likewise, Egerton’s (2016) instalment of his “History of Ecological Sciences: Marine Ecology featuring Beebe, Bigelow, Ricketts”, while placing Beebe in admirable company, makes no mention of Beebe’s deep-sea work. Ironically perhaps, Beebe while largely if not completely unknown to biological oceanographers is recognized by physical oceanographers for his early observation of El Nino event during Arcturus Expedition (Wooster, 1980; Quinn et al., 1987). What follows Here, the sampling and results, first from Beebe’s Arcturus Oceanographic Expedition, and then from the Nonsuch studies, are described in an effort to draw attention to a remarkable body of work. Study of the deep-sea samples yielded 43 scientific articles by Beebe and his colleagues on a large variety of taxa. Beebe’s famous Bathysphere dives have been dealt with at length (e.g. Matsen, 2005) and will only be considered here in relation to Beebe’s scientific reputation. Finally, possible reasons for the fact that such a considerable body of work is often unremarked are considered. Inspired by the Michael Sars North Atlantic deep-sea expedition: the Arcturus Oceanographic Expedition According to Gould (2004), Beebe’s interest in the deep-sea can be traced to his reading about the Michael Sars expedition. She describes Beebe as having nearly memorized Murray and Hjort’s (1912),The Depths of the Ocean. Indeed, a Michael Sars inspiration can be seen clearly in comparing the illustration of the pelagic sampling from The Depths of the Ocean (Figure 1, from p. 49) with that of the Arcturus from Tee-Van (1926, p. 70) shown in the top panel of Figure 2. Furthermore, in describing the equipment and re-fitting of the vessel, Tee-Van (1926) stated that they were indebted for much information, both before and during the expedition, to published accounts of other expeditions but especially to that of Murray and Hjort’s The Depths of the Ocean. In 1925, few results were available from deep-sea expeditions other than Michael Sars and results from it were still emerging. The results of Danish “Great Atlantic Expedition of the Dana of 1921–1922” were as yet largely unpublished in 1925 (see Poulsen, 2016). Figure 1. Open in new tabDownload slide Michael Sars pelagic sampling from Murray and Hjort (1912). Figure 1. Open in new tabDownload slide Michael Sars pelagic sampling from Murray and Hjort (1912). Figure 2. Open in new tabDownload slide The Arcturus Oceanographic Expedition from Tee-Van (1926): (a) the sampling equipment, (b) the vessel, a sturdy 82-m coal-burning steam-ship built 6 years earlier as trawler to work the Alaskan coast, re-fitted and re-named for the expedition. (c) The dry lab, location on the ship shown by the arrow, on the deck above the wet lab. Beebe is seated the desk in the rear, facing the camera. Figure 2. Open in new tabDownload slide The Arcturus Oceanographic Expedition from Tee-Van (1926): (a) the sampling equipment, (b) the vessel, a sturdy 82-m coal-burning steam-ship built 6 years earlier as trawler to work the Alaskan coast, re-fitted and re-named for the expedition. (c) The dry lab, location on the ship shown by the arrow, on the deck above the wet lab. Beebe is seated the desk in the rear, facing the camera. The Arcturus, re-named for star of the mariners, was given to the New York Zoological society for the expedition by a wealthy patron, expressly for the expedition. The re-fitting and financial support for the expedition came from other patrons of the Zoological Society. The ship was modified to increase its range and suitability for deep-sea oceanographic work. The modifications included increasing coal storage and refrigerator space, adding a wet and dry lab, and installing custom-made trawling and dredging winches holding 8 km of steel cable (Tee-Van, 1926). The objectives of the expedition were simply stated as “investigating the Sargasso Sea and the Humboldt Current” (Beebe, 1925a). The Sargasso Sea at the time was an area of great interest as it had been recently identified as the breeding site of the eel, previously a major mystery (Poulsen, 2016), and in popular legend, the Sargasso Sea was a sea of ghost ships (e.g. Levick, 1925). The second goal of investigating the fauna of the Humboldt Current was quite possibly simply an excuse to return to the Galapagos. The Arcturus left New York on 11 February 1925 and returned to New York on 30 July 1925. The cruise track is shown in Figure 3. The first sampling of 22 Sargasso Sea stations began February 23 and ended on March 13. The Arcturus passed through the Panama Canal and on March 27 began the sampling of 38 stations along a cruise track from Panama to the Galapagos, then the Cocos Islands, and back through the Panama Canal to the Atlantic in late June. They failed to find the Humboldt Current, and Beebe’s observations, reported in Science (Beebe, 1926a), have been taken as one of the first observations of an El Nino event (Wooster, 1980; Quinn et al., 1987). On the return leg, 20 more stations were sampled between the Atlantic coast of San Salvador and the homeport of New York. The station locations and summary of ship operations are given in Beebe (1926b). A total of 251 samples were acquired from deep water (≥300 m depth) during the cruise, pooling all net, trawl, and dredge sampling. Figure 3. Open in new tabDownload slide Cruise track and Station Maps of the Arcturus Oceanographic Expedition from Beebe (1926b). Figure 3. Open in new tabDownload slide Cruise track and Station Maps of the Arcturus Oceanographic Expedition from Beebe (1926b). The expedition was closely followed in the press, as no previous oceanographic expedition had been before, nor quite possibly has ever since been so closely followed in the popular press. For example, The New York Times published 35 articles on the expedition from 6 February 1925 to 30 August 1925, thus averaging over one article per week on the Arcturus Expedition. Many of the articles were simply transcripts of Beebe’s periodically radioed reports of expedition activities. The coverage in The New York Times though also included multi-page articles with illustrations as well as several front-page articles (e.g. Anon, 1925). Beebe’s popular book on the expedition, The Arcturus Adventure (Beebe, 1926c), appeared in May 1926 and was glowingly reviewed in The New York Times (Duffus, 1926). Sample material gathered during the expedition was dispatched to renowned experts scattered around the globe. The scientific results took some time to appear, as is usually the case. The ten publications resulting from the Arcturus Oceanographic Expedition are given in Table 1. The scientific output of the Arcturus Expedition obviously was not of the same magnitude as large-scale expeditions such as the Michael Sars in 1910 and the Dana 1921–1922 or the expedition shortly after the Arcturus, the 1929 Cruise VII of the Carnegie (also under-appreciated, see Dolan, 2011). However, the scientific results of the Arcturus, while perhaps not considerable compared to other expeditions, were not negligible either. Admittedly, none of the Arcturus reports can be called “highly cited”, but some are relatively well-cited (see Table 1) and continue to be cited in recent years such as Bigelow (1928, 1931), Robson (1948), and Treadwell (1928). Table 1. Arcturus Oceanographic Expedition publications Taxa . Reference . # Cites . Siphonophores Bigelow (1931) 14 Medusa Bigelow (1928) 10 Echinoderms Fisher (1928) 6 Polychaetes Treadwell (1928) 21 Cephalopods Robson (1948) 12 Fish Beebe (1926a) 44 Fish Beebe (1926d) 0 Fish Trotter (1926) 26 Fish Gregory (1928) 12 Fish Nigrelli (1947) 7 Taxa . Reference . # Cites . Siphonophores Bigelow (1931) 14 Medusa Bigelow (1928) 10 Echinoderms Fisher (1928) 6 Polychaetes Treadwell (1928) 21 Cephalopods Robson (1948) 12 Fish Beebe (1926a) 44 Fish Beebe (1926d) 0 Fish Trotter (1926) 26 Fish Gregory (1928) 12 Fish Nigrelli (1947) 7 Open in new tab Table 1. Arcturus Oceanographic Expedition publications Taxa . Reference . # Cites . Siphonophores Bigelow (1931) 14 Medusa Bigelow (1928) 10 Echinoderms Fisher (1928) 6 Polychaetes Treadwell (1928) 21 Cephalopods Robson (1948) 12 Fish Beebe (1926a) 44 Fish Beebe (1926d) 0 Fish Trotter (1926) 26 Fish Gregory (1928) 12 Fish Nigrelli (1947) 7 Taxa . Reference . # Cites . Siphonophores Bigelow (1931) 14 Medusa Bigelow (1928) 10 Echinoderms Fisher (1928) 6 Polychaetes Treadwell (1928) 21 Cephalopods Robson (1948) 12 Fish Beebe (1926a) 44 Fish Beebe (1926d) 0 Fish Trotter (1926) 26 Fish Gregory (1928) 12 Fish Nigrelli (1947) 7 Open in new tab The Nonsuch studies Beebe experienced frustration on the Arcturus with the very limited number of samples that can be gathered at a given station from a ship in open waters. His previous experience in sampling tropical terrestrial systems from field stations had involved intensive sampling of small areas over long periods of time. One of his best-known works is “Studies of a tropical jungle: one quarter of a square mile of jungle” (Gould, 2004), the result of investigations over several seasons (Beebe, 1925b). Beebe stated this his idea to establish a shore laboratory from which daily deep-sea sampling could be carried occurred to him on the return leg of the Arcturus Expedition, sampling at Station 100 near Bermuda (Beebe, 1931), the genesis then of the Nonsuch laboratory in Bermuda, established 4 years later. Through his considerable social connections (see Kroll, 1970), he obtained the use of a former hospital and quarantine facility on Nonsuch Island in Bermuda and the use, at cost, of a 28-m tugboat, the Gladisfen. Deep water, 1000 fathoms (or 1828 m), was only 8 km offshore. The winches and sounding machine from the Arcturus were brought from New York and mounted on the Gladisfen, and sampling began in 13 March 1929 and, in that first sampling season, lasted until 22 October 1929. The sampling was always performed at the same site and involved towing nets across a transect of about 13 km. Thus, the basic strategy was to use long horizontal net tows. The net-tow catches were roughly sorted on board, especially to isolate living organisms, and transported back to the Nonsuch laboratory for immediate intensive sorting and examination. Figure 4 shows the sampling site and method schematically, the Gladisfen, and the Nonsuch laboratory. Figure 4. Open in new tabDownload slide The Nonsuch sampling, vessel, and laboratory: (a) the sampling scheme, (b) the Gladisfen, a 28-m tugboat. (c) The laboratory on Nonsuch Island. From Beebe (1931). Beebe is seated at the first desk, far left. Figure 4. Open in new tabDownload slide The Nonsuch sampling, vessel, and laboratory: (a) the sampling scheme, (b) the Gladisfen, a 28-m tugboat. (c) The laboratory on Nonsuch Island. From Beebe (1931). Beebe is seated at the first desk, far left. Usually used at all depths were 1 m diameter Sars nets, mesh size of 366 µm, without any closing apparatus, and a glass jar protected with padding, for the cod end. The first net set, the deepest net (see scheme in Figure 4a), fished for the longest time period, and the last, surface layer net, fished the shortest time along the transect. Beebe gave a summary of a “typical” deep-sea net tow at 1463 m (Beebe, 1936a), summarized in Table 2. In the example he gave, the catch included about 150 fish of 11 species for just one of the 6 deep-water nets towed that day. Figure 5 shows the number of plankton net tows carried by month from the 1929 sampling campaign to the 1935 sampling campaign. A total of over 1500 net tows were made at the Nonsuch sampling site. Figure 5. Open in new tabDownload slide The number plankton net tows performed by month from 1929 to 1935, separated into surface layer and deep-water sampling. No net sampling was done in the 1932 season dedicated to Bathysphere dives. Figure 5. Open in new tabDownload slide The number plankton net tows performed by month from 1929 to 1935, separated into surface layer and deep-water sampling. No net sampling was done in the 1932 season dedicated to Bathysphere dives. Table 2. Typical deep-water Nonsuch net tow catch Invertebrates Copepods, a dozen or more species, mostly calanoids, with also Corycaeus, Oithona, etc. Schizopods, chiefly small species of Euphausia, with a dozen others belonging to two or three genera. Shrimps, one specimen, aff. Pandalus danae. Ostracods, a few of one or two species. Amphipods, few and small, a dozen individuals of four or five species. Sagitta, apparently two or three species. Polychaetes, one Tomopteris septentrionale. Siphonophores, Diphys truncata. Sponges, fair number of spicules of various kinds. Radiolaria, large numbers of portions of a hexagonal framework and a few small, conical specimens mostly incomplete; numbers of perforated spherical species and Astrophaeroidea. Diatoms: one each Asteromphalus heptactis, Melosira moniliformis, Coscinodiscus. Tintinnoinea, one Tintinnopsis cylindrica and one Parafavella near P. acuta. Foraminifera, few, of two or three species. Fish Fish larvae: three specimens one of a deep-sea species, with very large lower jaw and black spots on sides. Fish, adolescent, and adult: Bregmaceros macclellandii, 45 mm (1 specimen) Cyclothone microdon (117 specimens) Cyclothone pallida (1 specimen) Cyclothone signata (14 specimens) Lampadena chavesi (1 specimen) Lampanyctus warmingi, 11–21 mm (6 specimens) Lestidium intermedium, 87 mm (1 specimen) Myctophum benoiti, 11–12 mm (3 specimens) Myctophum laternatum, 12 mm (13 specimens) Omosudis lowi, 11–38 mm (2 specimens) Stomias ferox, 80 mm (1 specimen) Invertebrates Copepods, a dozen or more species, mostly calanoids, with also Corycaeus, Oithona, etc. Schizopods, chiefly small species of Euphausia, with a dozen others belonging to two or three genera. Shrimps, one specimen, aff. Pandalus danae. Ostracods, a few of one or two species. Amphipods, few and small, a dozen individuals of four or five species. Sagitta, apparently two or three species. Polychaetes, one Tomopteris septentrionale. Siphonophores, Diphys truncata. Sponges, fair number of spicules of various kinds. Radiolaria, large numbers of portions of a hexagonal framework and a few small, conical specimens mostly incomplete; numbers of perforated spherical species and Astrophaeroidea. Diatoms: one each Asteromphalus heptactis, Melosira moniliformis, Coscinodiscus. Tintinnoinea, one Tintinnopsis cylindrica and one Parafavella near P. acuta. Foraminifera, few, of two or three species. Fish Fish larvae: three specimens one of a deep-sea species, with very large lower jaw and black spots on sides. Fish, adolescent, and adult: Bregmaceros macclellandii, 45 mm (1 specimen) Cyclothone microdon (117 specimens) Cyclothone pallida (1 specimen) Cyclothone signata (14 specimens) Lampadena chavesi (1 specimen) Lampanyctus warmingi, 11–21 mm (6 specimens) Lestidium intermedium, 87 mm (1 specimen) Myctophum benoiti, 11–12 mm (3 specimens) Myctophum laternatum, 12 mm (13 specimens) Omosudis lowi, 11–38 mm (2 specimens) Stomias ferox, 80 mm (1 specimen) From Beebe (1936a), the example from a tow at 800 fathoms (1463 m) depth on 5 July 1930. The net was the usual 1 m diameter Sars net, mesh size 366 µm, towed for 4 h [time from Beebe (1931)] on a transect of 12.9 km distance yielding a putative volume sampled of 12 875 m3. The tintinnid listed as Parafavella, a genus of boreal sea tintinnids, was likely Parundella acuta as found by Wailes later in the Nonsuch samples (Wailes, 1936). Open in new tab Table 2. Typical deep-water Nonsuch net tow catch Invertebrates Copepods, a dozen or more species, mostly calanoids, with also Corycaeus, Oithona, etc. Schizopods, chiefly small species of Euphausia, with a dozen others belonging to two or three genera. Shrimps, one specimen, aff. Pandalus danae. Ostracods, a few of one or two species. Amphipods, few and small, a dozen individuals of four or five species. Sagitta, apparently two or three species. Polychaetes, one Tomopteris septentrionale. Siphonophores, Diphys truncata. Sponges, fair number of spicules of various kinds. Radiolaria, large numbers of portions of a hexagonal framework and a few small, conical specimens mostly incomplete; numbers of perforated spherical species and Astrophaeroidea. Diatoms: one each Asteromphalus heptactis, Melosira moniliformis, Coscinodiscus. Tintinnoinea, one Tintinnopsis cylindrica and one Parafavella near P. acuta. Foraminifera, few, of two or three species. Fish Fish larvae: three specimens one of a deep-sea species, with very large lower jaw and black spots on sides. Fish, adolescent, and adult: Bregmaceros macclellandii, 45 mm (1 specimen) Cyclothone microdon (117 specimens) Cyclothone pallida (1 specimen) Cyclothone signata (14 specimens) Lampadena chavesi (1 specimen) Lampanyctus warmingi, 11–21 mm (6 specimens) Lestidium intermedium, 87 mm (1 specimen) Myctophum benoiti, 11–12 mm (3 specimens) Myctophum laternatum, 12 mm (13 specimens) Omosudis lowi, 11–38 mm (2 specimens) Stomias ferox, 80 mm (1 specimen) Invertebrates Copepods, a dozen or more species, mostly calanoids, with also Corycaeus, Oithona, etc. Schizopods, chiefly small species of Euphausia, with a dozen others belonging to two or three genera. Shrimps, one specimen, aff. Pandalus danae. Ostracods, a few of one or two species. Amphipods, few and small, a dozen individuals of four or five species. Sagitta, apparently two or three species. Polychaetes, one Tomopteris septentrionale. Siphonophores, Diphys truncata. Sponges, fair number of spicules of various kinds. Radiolaria, large numbers of portions of a hexagonal framework and a few small, conical specimens mostly incomplete; numbers of perforated spherical species and Astrophaeroidea. Diatoms: one each Asteromphalus heptactis, Melosira moniliformis, Coscinodiscus. Tintinnoinea, one Tintinnopsis cylindrica and one Parafavella near P. acuta. Foraminifera, few, of two or three species. Fish Fish larvae: three specimens one of a deep-sea species, with very large lower jaw and black spots on sides. Fish, adolescent, and adult: Bregmaceros macclellandii, 45 mm (1 specimen) Cyclothone microdon (117 specimens) Cyclothone pallida (1 specimen) Cyclothone signata (14 specimens) Lampadena chavesi (1 specimen) Lampanyctus warmingi, 11–21 mm (6 specimens) Lestidium intermedium, 87 mm (1 specimen) Myctophum benoiti, 11–12 mm (3 specimens) Myctophum laternatum, 12 mm (13 specimens) Omosudis lowi, 11–38 mm (2 specimens) Stomias ferox, 80 mm (1 specimen) From Beebe (1936a), the example from a tow at 800 fathoms (1463 m) depth on 5 July 1930. The net was the usual 1 m diameter Sars net, mesh size 366 µm, towed for 4 h [time from Beebe (1931)] on a transect of 12.9 km distance yielding a putative volume sampled of 12 875 m3. The tintinnid listed as Parafavella, a genus of boreal sea tintinnids, was likely Parundella acuta as found by Wailes later in the Nonsuch samples (Wailes, 1936). Open in new tab Although Beebe never cited Haeckel, he followed his dictum concerning the importance of sampling the same site over a period of years (Haeckel, 1891). The amount of deep-sea material collected over relatively long periods of time at different depths at the same location was unprecedented at that time and, to my knowledge, has never been repeated. Regular deep-sea sampling has, in recent years, been conducted at other sites such as the Bermuda Atlantic Time-Series Station and off Los Angeles at the San Pedro Ocean Time-Series Station but at only monthly, not daily, intervals and typically focused on microbial populations (e.g. Vergin et al., 2013; Kim et al., 2014). Thus, the data gathered by Beebe are difficult to compare with any contemporary sampling, hindering possible assessment of long-term changes in the deep-sea ecosystem off Bermuda. The unique intensive sampling performed allowed Beebe and his colleagues to work out details of the development and ecology of individual forms and their inter-relationships. An example is the working out the life history of a deep-sea fish, characterized by morphologically odd developmental stages, and sexual dimorphism: Idiacanthus fasciola. Below is a very brief summary of Beebe’s short report in Science (Beebe, 1933a) and his detailed report of 94 pages (Beebe, 1933b) in Zoologica. The odd stalk-eyed deep-sea fish shown in the top panel of Figure 6 was previously thought to be the species Stylophthalmus paradoxa Brauer 1902. It was iconic of the odd morphologies of deep-sea forms, for example decorating the cover of Chun’s book on the Valdivia German deep-sea expedition (Chun, 1903). The middle panel of Figure 6 shows the intermediate forms Beebe found allowing him to identify putative S. paradoxa as actually the larval form of I. fasciola. His brief report in Science stated that the stalk-eyed forms were mostly found in samples from above 200 m depth while post-larval forms were found in samples from about 750 to 1500 m depth (Beebe, 1933a). In his detailed report (Beebe, 1933b), he also showed that forms thought to be larvae of I. fasciola (the small forms in the bottom panel of Figure 6), were non-feeding adult males with enlarged livers and degenerate digestive tracts. The remarkable sexual dimorphism discovered by Beebe is among the most extreme known among fish (Fairbairn, 2013). Figure 6. Open in new tabDownload slide Life-history stages and sexual dimorphism in I. fasciola. Top panel shows the stalk-eyed larvae previously thought to be another species. Middle panel shows developmental stages of the male. Bottom panel shows the relatively small transparent males and dark females. All figures from Beebe (1933b). Figure 6. Open in new tabDownload slide Life-history stages and sexual dimorphism in I. fasciola. Top panel shows the stalk-eyed larvae previously thought to be another species. Middle panel shows developmental stages of the male. Bottom panel shows the relatively small transparent males and dark females. All figures from Beebe (1933b). Trophic relationships were also studied with the Nonsuch samples. For example, the large amount of data gathered on the depth distribution of a variety of taxa in the deep layers allowed the diagnosis of where predators from surface layers, for example tuna, fed, and based on the gut contents of the tuna prey, what prey the tuna were both directly and indirectly consuming. Beebe (1936b) analysed the gut contents of 58 black-finned tuna to reconstruct, in part, tuna food webs as the gut contents of the prey ingested by the tune were identified. Thus, not only was the tuna prey revealed, but also the food of the tuna prey were revealed. Figure 7 shows the gut contents of a tuna specimen and the partially re-constituted food web of the individual. Figure 7. Open in new tabDownload slide Gut contents of Black-Finned Tuna from Bermuda (upper panel) and a re-constituted food web from prey items recognizable in the guts of the tuna’s prey (lower panel), from Beebe (1936b). Figure 7. Open in new tabDownload slide Gut contents of Black-Finned Tuna from Bermuda (upper panel) and a re-constituted food web from prey items recognizable in the guts of the tuna’s prey (lower panel), from Beebe (1936b). The 33 publications resulting from the analysis of Nonsuch samples are given in Table 3. While a large variety of taxa were studied, most of the publications were on deep-sea fish and authored by Beebe. Many of Beebe’s studies of fish included ecological information such as gut contents, observations of parasites, seasonal occurrences, frequencies of occurrences, as well as occurrences in the gut tract of other species, thus identifying the fish’s “enemies”. Table 3. Publications from Nonsuch sampling Taxa . Reference . # cites . Taxa . Reference . # cites . Tintinnids Wailes (1936) 1 Fish Beebe (1929b) 4 Copepods Wilson (1936) 5 Fish Beebe (1933c) 6 Euphausids Tattersall (1936) 2 Fish Beebe (1933a) 0 Siphonophores Totton (1936) 8 Fish Beebe (1933c) 6 Medusa Bigelow (1938) 22 Fish Beebe (1933d) 6 Shrimp Chace (1940) 62 Fish Beebe (1933e) 1 Polychaetes Berleley (1936) 0 Fish Beebe (1933f) 9 Polychaetes Treadwell (1941) 23 Fish Beebe (1933g) 2 Amphipods Shoemaker (1945) 44 Fish Beebe (1935a) 11 Ribbon Worms Coe (1945) 4 Fish Beebe (1935b) 4 Cephalopods Pickford (1950) 5 Fish Beebe and Crane (1936) 12 Fish Beebe (1932a) 22 Fish Beebe (1937) 25 Fish Beebe (1932b) 0 Fish Beebe and Crane (1937a) 2 Fish Beebe (1933b) 0 Fish Beebe and Crane (1937b) 9 Fish Beebe and Vander Pyl (1944) 35 Fish Beebe and Crane (1939) 27 Fish Beebe and Tee-Van (1932) 3 Fish Harry (1951) 13 Fish Beebe (1929a) 2 Fish Harry (1952) 6 Taxa . Reference . # cites . Taxa . Reference . # cites . Tintinnids Wailes (1936) 1 Fish Beebe (1929b) 4 Copepods Wilson (1936) 5 Fish Beebe (1933c) 6 Euphausids Tattersall (1936) 2 Fish Beebe (1933a) 0 Siphonophores Totton (1936) 8 Fish Beebe (1933c) 6 Medusa Bigelow (1938) 22 Fish Beebe (1933d) 6 Shrimp Chace (1940) 62 Fish Beebe (1933e) 1 Polychaetes Berleley (1936) 0 Fish Beebe (1933f) 9 Polychaetes Treadwell (1941) 23 Fish Beebe (1933g) 2 Amphipods Shoemaker (1945) 44 Fish Beebe (1935a) 11 Ribbon Worms Coe (1945) 4 Fish Beebe (1935b) 4 Cephalopods Pickford (1950) 5 Fish Beebe and Crane (1936) 12 Fish Beebe (1932a) 22 Fish Beebe (1937) 25 Fish Beebe (1932b) 0 Fish Beebe and Crane (1937a) 2 Fish Beebe (1933b) 0 Fish Beebe and Crane (1937b) 9 Fish Beebe and Vander Pyl (1944) 35 Fish Beebe and Crane (1939) 27 Fish Beebe and Tee-Van (1932) 3 Fish Harry (1951) 13 Fish Beebe (1929a) 2 Fish Harry (1952) 6 Open in new tab Table 3. Publications from Nonsuch sampling Taxa . Reference . # cites . Taxa . Reference . # cites . Tintinnids Wailes (1936) 1 Fish Beebe (1929b) 4 Copepods Wilson (1936) 5 Fish Beebe (1933c) 6 Euphausids Tattersall (1936) 2 Fish Beebe (1933a) 0 Siphonophores Totton (1936) 8 Fish Beebe (1933c) 6 Medusa Bigelow (1938) 22 Fish Beebe (1933d) 6 Shrimp Chace (1940) 62 Fish Beebe (1933e) 1 Polychaetes Berleley (1936) 0 Fish Beebe (1933f) 9 Polychaetes Treadwell (1941) 23 Fish Beebe (1933g) 2 Amphipods Shoemaker (1945) 44 Fish Beebe (1935a) 11 Ribbon Worms Coe (1945) 4 Fish Beebe (1935b) 4 Cephalopods Pickford (1950) 5 Fish Beebe and Crane (1936) 12 Fish Beebe (1932a) 22 Fish Beebe (1937) 25 Fish Beebe (1932b) 0 Fish Beebe and Crane (1937a) 2 Fish Beebe (1933b) 0 Fish Beebe and Crane (1937b) 9 Fish Beebe and Vander Pyl (1944) 35 Fish Beebe and Crane (1939) 27 Fish Beebe and Tee-Van (1932) 3 Fish Harry (1951) 13 Fish Beebe (1929a) 2 Fish Harry (1952) 6 Taxa . Reference . # cites . Taxa . Reference . # cites . Tintinnids Wailes (1936) 1 Fish Beebe (1929b) 4 Copepods Wilson (1936) 5 Fish Beebe (1933c) 6 Euphausids Tattersall (1936) 2 Fish Beebe (1933a) 0 Siphonophores Totton (1936) 8 Fish Beebe (1933c) 6 Medusa Bigelow (1938) 22 Fish Beebe (1933d) 6 Shrimp Chace (1940) 62 Fish Beebe (1933e) 1 Polychaetes Berleley (1936) 0 Fish Beebe (1933f) 9 Polychaetes Treadwell (1941) 23 Fish Beebe (1933g) 2 Amphipods Shoemaker (1945) 44 Fish Beebe (1935a) 11 Ribbon Worms Coe (1945) 4 Fish Beebe (1935b) 4 Cephalopods Pickford (1950) 5 Fish Beebe and Crane (1936) 12 Fish Beebe (1932a) 22 Fish Beebe (1937) 25 Fish Beebe (1932b) 0 Fish Beebe and Crane (1937a) 2 Fish Beebe (1933b) 0 Fish Beebe and Crane (1937b) 9 Fish Beebe and Vander Pyl (1944) 35 Fish Beebe and Crane (1939) 27 Fish Beebe and Tee-Van (1932) 3 Fish Harry (1951) 13 Fish Beebe (1929a) 2 Fish Harry (1952) 6 Open in new tab Deep-sea fish descriptions Beebe described over 80 species of fish (Berra, 1977). According to the WoRMS database, at present, the descriptions of 37 accepted species are credited to Beebe and colleagues (WoRMS 2020). Of the 37 accepted species described by Beebe and colleagues, 16 are deep-sea forms (Table 4). In addition to these 16 species, 2 other deep-sea species, presently accepted as valid, were described by Harry (1952) from Nonsuch samples and named after Beebe’s colleagues: Cetomimus teevani and Cetomimus craneae for John Tee-Van and Jocelyn Crane. Thus, 18 species of deep-sea fish were first described from Beebe’s deep-water samples. Table 4. Deep-sea fish species descriptions attributed to Beebe Original name . Accepted name . Expedition . Sampling depth . Reference . Diabolidium arcturi (Beebe, 1926) Linophryne arcturi (Beebe, 1926) Arcturus 1925 915 Beebe (1926d) Linophryne brevibarbata (Beebe, 1932) Linophryne brevibarbata (Beebe, 1932) Bermuda 1929 1647 Beebe (1932a) Saccopharynx harrisoni (Beebe, 1932) Saccopharynx harrisoni (Beebe, 1932) Bermuda 1931 1647 Beebe (1932a) Dolopichthys gladisfenae (Beebe, 1932) Spiniphryne gladisfenae (Beebe, 1932) Bermuda 1930 1281 Beebe (1932a) Chaenophryne draco (Beebe, 1932) Chaenophryne draco (Beebe, 1932) Bermuda 1931 1098 Beebe (1932a) Eustomias schiffi (Beebe, 1932) Eustomias schiffi (Beebe, 1932) Bermuda 1930 1098 Beebe (1932a) Photichthys nonsuchae (Beebe, 1932) Woodsia nonsuchae (Beebe, 1932) Bermuda 1929 1098 Beebe (1932a) Leptostomias bermudensis (Beebe, 1932) Leptostomias bermudensis (Beebe, 1932) Bermuda 1931 915 Beebe (1932a) Dolichopteryx binocularis (Beebe, 1932) Dolichopteroides binocularis (Beebe, 1932) Bermuda 1931 732 Beebe (1932a) Eustomias satterleei (Beebe, 1933) Eustomias satterleei (Beebe, 1933) Bermuda 1929 1830 Beebe (1932a) Bathophilus altipinnis (Beebe, 1933) Bathophilus altipinnis (Beebe, 1933) Bermuda 1929 1464 Beebe (1933c) Photostylus pycnopterus (Beebe, 1933) Photostylus pycnopterus (Beebe, 1933) Bermuda 1929 1464 Beebe (1933c) Psammobatus spinosissimus (Beebe and Tee-Van 1941) Bathyraja spinosissima (Beebe and Tee-Van 1941) Arcturus 1925 1400 Beebe and Tee-Van (1941) Gigantactis perlatus (Beebe and Crane, 1947) Gigantactis perlatus (Beebe and Crane, 1947) Zaca 1938 915 Beebe and Crane (1947) Himantolophus azurlucens (Beebe and Crane, 1947) Himantolophus azurlucens (Beebe and Crane, 1947) Zaca 1938 915 Beebe and Crane (1947) Linophryne quinqueramosa (Beebe and Crane, 1947) Linophryne quinqueramosa (Beebe and Crane, 1947) Zaca 1938 915 Beebe and Crane (1947) Original name . Accepted name . Expedition . Sampling depth . Reference . Diabolidium arcturi (Beebe, 1926) Linophryne arcturi (Beebe, 1926) Arcturus 1925 915 Beebe (1926d) Linophryne brevibarbata (Beebe, 1932) Linophryne brevibarbata (Beebe, 1932) Bermuda 1929 1647 Beebe (1932a) Saccopharynx harrisoni (Beebe, 1932) Saccopharynx harrisoni (Beebe, 1932) Bermuda 1931 1647 Beebe (1932a) Dolopichthys gladisfenae (Beebe, 1932) Spiniphryne gladisfenae (Beebe, 1932) Bermuda 1930 1281 Beebe (1932a) Chaenophryne draco (Beebe, 1932) Chaenophryne draco (Beebe, 1932) Bermuda 1931 1098 Beebe (1932a) Eustomias schiffi (Beebe, 1932) Eustomias schiffi (Beebe, 1932) Bermuda 1930 1098 Beebe (1932a) Photichthys nonsuchae (Beebe, 1932) Woodsia nonsuchae (Beebe, 1932) Bermuda 1929 1098 Beebe (1932a) Leptostomias bermudensis (Beebe, 1932) Leptostomias bermudensis (Beebe, 1932) Bermuda 1931 915 Beebe (1932a) Dolichopteryx binocularis (Beebe, 1932) Dolichopteroides binocularis (Beebe, 1932) Bermuda 1931 732 Beebe (1932a) Eustomias satterleei (Beebe, 1933) Eustomias satterleei (Beebe, 1933) Bermuda 1929 1830 Beebe (1932a) Bathophilus altipinnis (Beebe, 1933) Bathophilus altipinnis (Beebe, 1933) Bermuda 1929 1464 Beebe (1933c) Photostylus pycnopterus (Beebe, 1933) Photostylus pycnopterus (Beebe, 1933) Bermuda 1929 1464 Beebe (1933c) Psammobatus spinosissimus (Beebe and Tee-Van 1941) Bathyraja spinosissima (Beebe and Tee-Van 1941) Arcturus 1925 1400 Beebe and Tee-Van (1941) Gigantactis perlatus (Beebe and Crane, 1947) Gigantactis perlatus (Beebe and Crane, 1947) Zaca 1938 915 Beebe and Crane (1947) Himantolophus azurlucens (Beebe and Crane, 1947) Himantolophus azurlucens (Beebe and Crane, 1947) Zaca 1938 915 Beebe and Crane (1947) Linophryne quinqueramosa (Beebe and Crane, 1947) Linophryne quinqueramosa (Beebe and Crane, 1947) Zaca 1938 915 Beebe and Crane (1947) Open in new tab Table 4. Deep-sea fish species descriptions attributed to Beebe Original name . Accepted name . Expedition . Sampling depth . Reference . Diabolidium arcturi (Beebe, 1926) Linophryne arcturi (Beebe, 1926) Arcturus 1925 915 Beebe (1926d) Linophryne brevibarbata (Beebe, 1932) Linophryne brevibarbata (Beebe, 1932) Bermuda 1929 1647 Beebe (1932a) Saccopharynx harrisoni (Beebe, 1932) Saccopharynx harrisoni (Beebe, 1932) Bermuda 1931 1647 Beebe (1932a) Dolopichthys gladisfenae (Beebe, 1932) Spiniphryne gladisfenae (Beebe, 1932) Bermuda 1930 1281 Beebe (1932a) Chaenophryne draco (Beebe, 1932) Chaenophryne draco (Beebe, 1932) Bermuda 1931 1098 Beebe (1932a) Eustomias schiffi (Beebe, 1932) Eustomias schiffi (Beebe, 1932) Bermuda 1930 1098 Beebe (1932a) Photichthys nonsuchae (Beebe, 1932) Woodsia nonsuchae (Beebe, 1932) Bermuda 1929 1098 Beebe (1932a) Leptostomias bermudensis (Beebe, 1932) Leptostomias bermudensis (Beebe, 1932) Bermuda 1931 915 Beebe (1932a) Dolichopteryx binocularis (Beebe, 1932) Dolichopteroides binocularis (Beebe, 1932) Bermuda 1931 732 Beebe (1932a) Eustomias satterleei (Beebe, 1933) Eustomias satterleei (Beebe, 1933) Bermuda 1929 1830 Beebe (1932a) Bathophilus altipinnis (Beebe, 1933) Bathophilus altipinnis (Beebe, 1933) Bermuda 1929 1464 Beebe (1933c) Photostylus pycnopterus (Beebe, 1933) Photostylus pycnopterus (Beebe, 1933) Bermuda 1929 1464 Beebe (1933c) Psammobatus spinosissimus (Beebe and Tee-Van 1941) Bathyraja spinosissima (Beebe and Tee-Van 1941) Arcturus 1925 1400 Beebe and Tee-Van (1941) Gigantactis perlatus (Beebe and Crane, 1947) Gigantactis perlatus (Beebe and Crane, 1947) Zaca 1938 915 Beebe and Crane (1947) Himantolophus azurlucens (Beebe and Crane, 1947) Himantolophus azurlucens (Beebe and Crane, 1947) Zaca 1938 915 Beebe and Crane (1947) Linophryne quinqueramosa (Beebe and Crane, 1947) Linophryne quinqueramosa (Beebe and Crane, 1947) Zaca 1938 915 Beebe and Crane (1947) Original name . Accepted name . Expedition . Sampling depth . Reference . Diabolidium arcturi (Beebe, 1926) Linophryne arcturi (Beebe, 1926) Arcturus 1925 915 Beebe (1926d) Linophryne brevibarbata (Beebe, 1932) Linophryne brevibarbata (Beebe, 1932) Bermuda 1929 1647 Beebe (1932a) Saccopharynx harrisoni (Beebe, 1932) Saccopharynx harrisoni (Beebe, 1932) Bermuda 1931 1647 Beebe (1932a) Dolopichthys gladisfenae (Beebe, 1932) Spiniphryne gladisfenae (Beebe, 1932) Bermuda 1930 1281 Beebe (1932a) Chaenophryne draco (Beebe, 1932) Chaenophryne draco (Beebe, 1932) Bermuda 1931 1098 Beebe (1932a) Eustomias schiffi (Beebe, 1932) Eustomias schiffi (Beebe, 1932) Bermuda 1930 1098 Beebe (1932a) Photichthys nonsuchae (Beebe, 1932) Woodsia nonsuchae (Beebe, 1932) Bermuda 1929 1098 Beebe (1932a) Leptostomias bermudensis (Beebe, 1932) Leptostomias bermudensis (Beebe, 1932) Bermuda 1931 915 Beebe (1932a) Dolichopteryx binocularis (Beebe, 1932) Dolichopteroides binocularis (Beebe, 1932) Bermuda 1931 732 Beebe (1932a) Eustomias satterleei (Beebe, 1933) Eustomias satterleei (Beebe, 1933) Bermuda 1929 1830 Beebe (1932a) Bathophilus altipinnis (Beebe, 1933) Bathophilus altipinnis (Beebe, 1933) Bermuda 1929 1464 Beebe (1933c) Photostylus pycnopterus (Beebe, 1933) Photostylus pycnopterus (Beebe, 1933) Bermuda 1929 1464 Beebe (1933c) Psammobatus spinosissimus (Beebe and Tee-Van 1941) Bathyraja spinosissima (Beebe and Tee-Van 1941) Arcturus 1925 1400 Beebe and Tee-Van (1941) Gigantactis perlatus (Beebe and Crane, 1947) Gigantactis perlatus (Beebe and Crane, 1947) Zaca 1938 915 Beebe and Crane (1947) Himantolophus azurlucens (Beebe and Crane, 1947) Himantolophus azurlucens (Beebe and Crane, 1947) Zaca 1938 915 Beebe and Crane (1947) Linophryne quinqueramosa (Beebe and Crane, 1947) Linophryne quinqueramosa (Beebe and Crane, 1947) Zaca 1938 915 Beebe and Crane (1947) Open in new tab Why are Beebe’s contributions of the natural history of the deep-sea ignored? According to Occam’s Razor, for any given question, the simplest explanation is the most likely to be true. The simplest explanation for the neglect of Beebe’s contributions is that the contributions are of no consequence and so need not to be acknowledged. However, judging scientific contributions as inconsequential or considerable is obviously subjective. There are no clear means to estimate the present value of past studies other than the obvious landmark works such as Darwin’s On the Origin of the Species (Darwin, 1859). The quantity and originality of Beebe’s contributions have been described here so the position taken is not should Beebe’s contributions to our knowledge of deep-sea be recognized, but rather why are they not? While there are possibly many reasons, below will be considered three major, but not mutually exclusive, reasons why Beebe’s contributions, consciously or unconsciously, may have been slighted. The first is that the quasi-totality of his deep-sea scientific work appeared in one journal possibly lacking a reputation of rigour, Zoologica. The second is that Beebe’s scientific reputation suffered from his having described four deep-sea fish species from visual observations during the Bathysphere dives. The third is that Beebe was an early victim of the “Sagan Effect” wherein media-driven fame negatively effects scientific reputation. The journal Zoologica was created as an outlet for the scientific work conducted by those working for the New York Zoological Society or its facilities or collections. According to Matsen (2005, p. 157), Zoologica was “not considered to be in the top ranks of taxonomy because of inconsistencies in their peer review”, unfortunately citing no sources for the statement. Thus, there is no evidence other than one undocumented opinion. The possibility that Beebe’s scientific reputation was damaged by his description of four deep-sea fishes based solely on visual observations (none of the species are currently recognized) appears in biographies of Beebe (Welker, 1975; Gould, 2004; Matsen, 2005) without, however, any documentary evidence beyond noting the sharp criticism of Beebe’s Bathyscaphe-based descriptions in a review of Beebe’s book Half Mile Down by the ichthyologist Carl Hubbs in Copeia (1935). Notably, Hubbs later cited Beebe’s articles on surface and deep-sea fish in Zoologica as authoritative (Hubbs and Kampa, 1946, Hubbs et al., 1953) suggesting that he did not doubt all of Beebe’s work nor that Zoologica article was untrustworthy. Other reviews of Half Mile Down appeared in Nature (Anon, 1935a), the Quarterly Review of Biology (Anon, 1935b), the Geographical Journal (CMY, 1936), and two by the Ichthyologist John Nichols, one in Natural History and the other in the Saturday Review of Literature (Nichols, 1934a, b). None of the reviews other than Hubbs contains overt criticism of the description of fish from visual observations only. The last major possibility to consider is that Beebe was an early victim of the “Sagan Effect”. This phenomenon posits that scientists who receive lots of media attention have their scientific work de-valued by the scientific community. It is based on the view that the astronomer Carl Sagan was denied election to the Academy of Science (USA) despite ample qualification because of his status as a media figure (Gwynne, 1997). Another well-known scientist, the palaeontologist, Stephen Jay Gould, is also thought to have had his scientific reputation suffer from the “Sagan Effect” (Shermer, 2002) as he was also a “Celebrity Scientist” (Fahy, 2015). The phenomenon may appear odd to us today. In recent years, with outreach efforts often mandated, any stigma associated with media attention is thought to be negligible with media attention actually linked to increases in citation rates (Russo, 2010). As time goes on, any or all the effects considered above should diminish. Knowledge of the relative prestige of Zoologica, the unorthodox naming of 4 out of the over 80 fish species, and the amount of media coverage given Beebe, should all decline with time but perhaps not at the same rate. Do any measures of prestige show a temporal change indicating an abrupt shift at some point in time, for example in the late 1930s following the Bathysphere dives? Two metrics were examined simply because data were relatively accessible: the number of marine species named for Beebe from the WoRMS website (WoRMS Editorial Board (2020), searching for marine and freshwater species containing the term ‘beebe’ and citations per year to Beebe publications using the Web of Science (www.webofknowledge.com, consulted 20 January 2020). Cumulative numbers of species named for Beebe with time and total citations to Beebe articles with time are shown in Figure 8. Figure 8. Open in new tabDownload slide Cumulative number of species named for William Beebe and cumulative number of citations to Beebe’s work with time. Figure 8. Open in new tabDownload slide Cumulative number of species named for William Beebe and cumulative number of citations to Beebe’s work with time. Surprisingly, the point in time corresponding to changes in both temporal trends is in the mid-1960s is following Beebe’s death (in 1962) and the changes in the two measures show opposite trends. Following Beebe’s death, there is an abrupt halt to naming species for Beebe that begins again only in recent years, since 2013. With regard to citations to Beebe articles, there appears to be an increase in citation rates following his death. The opposing temporal trends are very difficult to explain. The paired negative inflections of species naming declining and increase in citation rate increasing may simply reflect a shift in academic activity away from taxonomy and towards an increasing importance of publishing. Regardless though, both metrics show no sign of a shift corresponding with the Bathysphere dives, a source of a great deal of media attention as well as the contentious fish descriptions. In conclusion, there lacks clear evidence of any particularly strong reason behind the apparent slighting of Beebe’s deep-sea work by the scientific community. Finally, there are two additional facts that may have contributed to a lack of recognition for Beebe’s work by oceanographers. The first, following Anthony Adler (2019), is an adherence in the history the marine sciences to what he terms the “great ship narrative” in which developments are linked to large-scale expeditions to the detriment of work done in laboratories and field stations (Adler, 2019). Nonsuch was the first, and remains the only, field laboratory devoted to deep-sea research. The second is the fact that, unlike most well-known scientific figures of the 20th century, Beebe did not train any students, nor did his close collaborators in his deep-sea work, John Tee-Van and Jocelyn Crane, as they all were employed by the New York Zoological Society. Following the Nonsuch laboratory days, John Tee-Van moved into administrative posts of the New York Zoological Society, eventually assuming the directorship (Gould, 2004) and Jocelyn Crane became a very well-known expert, not on deep-sea life, but on hermit crabs (Yost, 1959). One could say then that Beebe had no “academic children” for his deep-sea work, a factor perhaps contributing to a lack of recognition for his deep-sea work. Conclusion Here is shown that the contributions of William Beebe to our knowledge of the natural history of the deep-sea are considerable, ranging from the descriptions of many new forms to observations on developmental stages and basic ecologies of many species. The reason(s) behind the fact that his contributions appear to be largely neglected remains unclear. However, hopefully this attempt to shed light on Beebe’s contributions will lead to their recognition. Acknowledgements Archivists at the Wildlife Conservation Society, Madeleine Thompson and Cassandra Paul, kindly provided copies of the N.Y. Zool. Soc. Bulletin. I am indebted to Tim Berra, Ted Pietsch, and Eric Mills who provided valuable information and encouragement. The advice of the anonymous reviewers and handling editor on earlier versions of the manuscript led to significant improvements. References Adler A. 2019 . Neptune’s Laboratory: Fantasy, Fear, and Science at Sea . Harvard University Press , Cambridge, MA, USA . 241 pp. Google Scholar Crossref Search ADS Google Scholar Google Preview WorldCat COPAC Anon. 1925 . BEEBE AND ARCTURUS HOME WITH MARVELS; Floating Laboratory Brings in Myriad-Lighted Fish and Bejeweled Crabs. SARGASSO LEGEND A MYTH Explorers Found No Wrecked Ships Caught in Weeds—The Humboldt Current Gone. N.Y. Times, July 31, 1925, pp. 1 and 8. Anon. 1930 a. Explorations of the deep sea . Scientific Monthly , 31 : 192 . OpenURL Placeholder Text WorldCat Anon. 1930 b. Deep sea investigations by submarine observation chamber . Nature , 126 : 220 . OpenURL Placeholder Text WorldCat Anon. 1935 a. Penetrating ocean depths . Nature Supplement , 586 – 587 . OpenURL Placeholder Text WorldCat Anon. 1935 b. Half mile down . Quarterly Review of Biology , 10 : 215 . OpenURL Placeholder Text WorldCat Ballard R. , Hively W. 2017 . The Eternal Darkness: A Personal History of Deep-Sea Exploration . NJ Princeton University Press , Princeton, NJ, USA . 388 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Bay J. C. 1948 . Some vital books in Science: 1848-1947 . Science , 107 : 485 – 491 . Google Scholar Crossref Search ADS PubMed WorldCat Beebe W. 1895 . The bird called ‘Brown Creeper’ . Harper’s Young People , 16 : 79 . OpenURL Placeholder Text WorldCat Beebe W. 1924 . Galapagos, World’s End . G.P. Putnam’s Sons , New York . 443 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Beebe W. 1925 a. Report of the director department of tropical research. New York Zoological Society Twenty-Ninth Annual Report, pp. 87 – 91 . Beebe W. 1925 b. Studies of a tropical jungle: one quarter of a square mile of jungle at Kartabo, British Guiana . Zoologica , 6 : 5 – 193 . OpenURL Placeholder Text WorldCat Beebe W. 1926 a. Note on the Humboldt current and Sargasso Sea . Science , 63 : 91 – 92 . Google Scholar Crossref Search ADS PubMed WorldCat Beebe W. 1926 b. The Arcturus Oceanographic Expedition . Zoologica , 8 : 1 – 45 . OpenURL Placeholder Text WorldCat Beebe W. 1926 c. The Arcturus Adventure . G.P. Putnam’s Sons , New York . 439 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Beebe W. 1926 d. A new ceratoid fish: preliminary description of a new genus and species . Bulletin of the New York Zoological Society , 29 : 80 . OpenURL Placeholder Text WorldCat Beebe W. 1929 a. Deep sea fish of the Hudson Gorge . Zoologica , 12 : 1 – 19 . OpenURL Placeholder Text WorldCat Beebe W. 1929 b. Haplophryne hudsonius: a new species; description and osteology . Zoologica , 12 : 21 – 36 . OpenURL Placeholder Text WorldCat Beebe W. 1931 a. Bermuda Oceanographic expeditions 1929-1930. Introduction . Zoologica , 13 : 1 – 14 . OpenURL Placeholder Text WorldCat Beebe W. 1932 a. Nineteen new species and four post-larval deep-sea fish . Zoologica , 13 : 47 – 107 . OpenURL Placeholder Text WorldCat Beebe W. 1932 b. A new deep-sea fish . Bulletin New York Zoological Society , 35 : 175 – 177 . OpenURL Placeholder Text WorldCat Beebe W. 1932 c. Exploration of the deep sea . Science , 76 : 344 – 344 . Google Scholar Crossref Search ADS PubMed WorldCat Beebe W. 1933 a. New data on the deep sea fish Stylophthalmus and Idiacanthus . Science , 78 : 390 – 390 . Google Scholar Crossref Search ADS PubMed WorldCat Beebe W. 1933 b. Deep-sea fishes of the Bermuda Oceanographic expeditions. Family Idiacanthidae . Zoologica , 16 : 149 – 241 . OpenURL Placeholder Text WorldCat Beebe W. 1933 b. Preliminary account of deep sea dives in the bathysphere with special reference to one of 2200 feet . Proceedings of the National Academy of Sciences of the United States of America , 19 : 178 – 188 . Google Scholar Crossref Search ADS PubMed WorldCat Beebe W. 1933 c. Deep-sea stomiatod fishes. One new genus and eight new species . Copeia , 1933 : 160 – 175 . Google Scholar Crossref Search ADS WorldCat Beebe W. 1933 d. Deep-sea isopondylous fishes. Two new genera and four new species . Zoologica , 13 : 159 – 167 . OpenURL Placeholder Text WorldCat Beebe W. 1933 e. Deep-sea fishes of the Bermuda Oceanographic expeditions. Introduction . Zoologica , 16 : 5 – 11 . OpenURL Placeholder Text WorldCat Beebe W. 1933 f. Deep-sea fishes of the Bermuda Oceanographic expeditions. Family Alepocephalidae . Zoologica , 16 : 15 – 93 . OpenURL Placeholder Text WorldCat Beebe W. 1933 g. Deep-sea fishes of the Bermuda Oceanographic expeditions. Family Argentinidae . Zoologica , 16 : 97 – 147 . OpenURL Placeholder Text WorldCat Beebe W. 1934 . Half Mile Down . Harcourt, Brace and Co ., New York . 344 pp. Google Scholar Crossref Search ADS Google Scholar Google Preview WorldCat COPAC Beebe W. 1935 a. Deep-sea fishes of the Bermuda Oceanographic expeditions. Family Derichthyidae . Zoologica , 20 : 1 – 23 . OpenURL Placeholder Text WorldCat Beebe W. 1935 b. Deep-sea fishes of the Bermuda Oceanographic expeditions. Family Nessorhamphidae . Zoologica , 20 : 25 – 51 . OpenURL Placeholder Text WorldCat Beebe W. 1936 a. Plankton of the Bermuda oceanographic expedition & introduction . Zoologica , 24 : 75 – 80 . OpenURL Placeholder Text WorldCat Beebe W. 1936 a. Bermuda Oceanographic expeditions 1929-1930. Individual nets and data, 1932-1935 . Zoologica , 21 : 69 – 73 . OpenURL Placeholder Text WorldCat Beebe W. 1936 b. Food of the Bermuda and West Indian tunas of the genera Parathunnus and Neothunnus . Zoologica , 21 : 195 – 225 . OpenURL Placeholder Text WorldCat Beebe W. 1937 . Preliminary list of Bermuda deep-sea fish . Zoologica , 22 : 197 – 208 . OpenURL Placeholder Text WorldCat Beebe W. , Crane J. 1936 . Deep-sea fishes of the Bermuda Oceanographic expeditions. Family Serrivomeridae. Part 1. Genus Serrivomer . Zoologica , 20 : 53 – 102 . OpenURL Placeholder Text WorldCat Beebe W. , Crane J. 1937 a. Deep-sea fishes of the Bermuda Oceanographic expeditions. Family Serrivomeridae. Part II. Genus Platuronides . Zoologica , 22 : 331 – 348 . OpenURL Placeholder Text WorldCat Beebe W. , Crane J. 1937 b. Deep-sea fishes of the Bermuda Oceanographic expeditions. Family Nemichthyidae . Zoologica , 22 : 349 – 383 . OpenURL Placeholder Text WorldCat Beebe W. , Crane J. 1939 . Deep-sea fishes of the Bermuda Oceanographic expeditions. Family Melanostomiatidae . Zoologica 24 : 65 – 238 . OpenURL Placeholder Text WorldCat Beebe W. , Crane J. 1947 . Eastern Pacific expeditions of the New York Zoological Society. XXXVII. Deep-sea ceratoid fishes . Zoologica , 31 : 151 – 182 . OpenURL Placeholder Text WorldCat Beebe W. , Tee-Van J. 1932 . New Bermuda fish, including six new species and forty-three species hitherto unrecorded from Bermuda . Zoologica , 13 : 109 – 120 . OpenURL Placeholder Text WorldCat Beebe W. , Tee-Van J. 1941 . Eastern Pacific expeditions of the New York Zoological Society. XXV. Fishes from the tropical eastern Pacific. [From Cedros Island, Lower California, south to the Galápagos Islands and northern Peru.] Part 3. Rays, Mantas and Chimeras . Zoologica , 26 : 245 – 280 . OpenURL Placeholder Text WorldCat Beebe W. , Vander Pyl M. 1944 . Eastern Pacific expeditions of the New York Zoological Society. XXXIII. Pacific Myctophidae (fishes) . Zoologica , 29 : 59 – 95 . OpenURL Placeholder Text WorldCat Berra T. M. 1977 . William Beebe: An Annotated Bibliography . Archon Books , Hamden, CN, USA . 157 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Berleley E. 1936 . Plankton of the Bermuda Oceanographic expeditions. 111. Notes on Polychaeta . Zoologica , 21 : 85 – 87 . OpenURL Placeholder Text WorldCat Bigelow H. B. 1928 . Scyphomedusae from the Arcturus Oceanographic expedition . Zoologica , 8 : 495 – 524 . OpenURL Placeholder Text WorldCat Bigelow H. B. 1931 . Siphonophorae from the Arcturus Oceanographic expedition . Zoologica , 8 : 525 – 592 . OpenURL Placeholder Text WorldCat Bigelow H. B. 1938 . Plankton of the Bermuda Oceanographic expeditions. VIII. Medusae taken during the years 1929 and 1930 . Zoologica , 23 : 99 – 189 . OpenURL Placeholder Text WorldCat Chace F. A. 1940 . Plankton of the Bermuda Oceanographic expeditions, IX: the bathypelagic caridean Crustacea . Zoologica , 25 : 117 – 209 . OpenURL Placeholder Text WorldCat Chun C. 1903 . Aus Den Tiefen Des Weltmeeres . Verlag von Gustav Fischer , Jena, Germany . 592 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC CMY. 1936 . Half mile down . Geographical Journal , 87 : 276 – 278 . Crossref Search ADS WorldCat Coe W. R. 1945 . Plankton of the Bermuda Oceanographic expeditions; bathypelagic nemerteans of the Bermuda area and other parts of the North and South Atlantic Oceans, with evidence as to their means of dispersal . Zoologica , 30 : 145 – 168 . OpenURL Placeholder Text WorldCat Cullen K. 2006 . Marine Science: The People behind the Science . Chelea House , New York . 174 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Darwin C. 1859 . On the Origin of the Species . Murray , London . 502 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Dolan J. R. 2011 . The legacy of the last cruise of the Carnegie: a lesson in the value of dusty old taxonomic monographs . Journal of Plankton Research , 33 : 1317 – 1324 . Google Scholar Crossref Search ADS WorldCat Duffus R. I. 1926 . “Arcturus”, Whither Away? Mr. Beebe Reports His Latest Adventure in Science. N.Y. Times, May 23 p BR1. Egerton F. N. 2016 . History of Ecological Sciences, Part 58A: marine Ecology, mid-1920s to about 1990, Featuring Beebe, Bigelow, Ricketts . Bulletin of the Ecological Society of America , 97 : 372 – 402 . Google Scholar Crossref Search ADS WorldCat Fahy D. 2015 . The New Celebrity Scientists: Out of the Lab and into the Limelight . Rowman & Littleman , Lanham, MD, USA . 285 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Fairbairn D. J. 2013 . Odd Couples: Extraordinary Differences between the Sexes in the Animal Kingdom . Princeton University Press , Princeton, NJ, USA . 300 pp. Google Scholar Crossref Search ADS Google Scholar Google Preview WorldCat COPAC Fiedler P. C. , Lavin M. F. 2006 . Introduction: a review of eastern tropical Pacific oceanography . Progress in Oceanography , 69 : 94 – 100 . Google Scholar Crossref Search ADS WorldCat Fisher W. K. 1928 . Sea stars from the Arcturus Oceanographic expedition . Zoologica , 8 : 487 – 493 . OpenURL Placeholder Text WorldCat Gould C. G. 2004 . The Remarkable Life of William Beebe, Explorer and Naturalist . Island Press , Washington, DC . 447 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Gregory W. K. 1928 . Studies on the body-forms of fishes . Zoologica , 8 : 325 – 421 . OpenURL Placeholder Text WorldCat Gwynne P. 1997 . Can you promote science without losing respect? The Scientist , 11 : 1 – 3 . OpenURL Placeholder Text WorldCat Haeckel E. , 1891 . Plankton-Studien . Jenaische Zeitschrift für Naturwissenschaft , 25 : 232 – 336 . (English translation: Report of the U.S. Commissioner of Fish and Fisheries for 1889 to 1891 (1893). pp. 565–641). OpenURL Placeholder Text WorldCat Harry R. R. 1951 . Deep-sea fishes of the Bermuda Oceanographic expeditions. Family Paralepididae . Zoologica , 36 : 17 – 35 . OpenURL Placeholder Text WorldCat Harry R. R. 1952 . Deep-sea fishes of the Bermuda Oceanographic expeditions. Families Cetomimidae and Rondeletiidae . Zoologica , 37 : 55 – 72 . OpenURL Placeholder Text WorldCat Hedgpeth J. W. 1974 . One hundred years of Pacific oceanography. In The Biology of the Oceanic Pacific , pp 137 – 155 . Ed. by Miller C. B.. Oregon State University Press , Corvallis, OR, USA . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Hubbs C. L. 1935 . Half mile down . Copeia , 1935 : 105 . Google Scholar Crossref Search ADS WorldCat Hubbs C. L. , Kampa E. M. 1946 . The early stages (egg, prolarva and juvenile) and the classification of the California flying fish . Copeia , 1946 : 188 – 182 . Google Scholar Crossref Search ADS WorldCat Hubbs C. L. , Mead G. W., Wilimovsky N. J. 1953 . The widespread, probably antitropical distribution and the relationship of the bathypelagic iniomous fish Anotopterus pharao . Bulletin of the Scripps Institute of Oceanography , 6 : 173 – 198 . OpenURL Placeholder Text WorldCat Kim D. Y. , Countway P. D., Jones A. C., Schnetzer A., Yamashita W., Tung C., Caron D. A. 2014 . Monthly to interannual variability of microbial eukaryote assemblages at four depths in the eastern North Pacific . The ISME Journal , 8 : 515 – 530 . Google Scholar Crossref Search ADS PubMed WorldCat Kimor B. 2002 . Deep-sea plankton exploration in historical perspective. In Oceanographic History: The Pacific and Beyond , pp. 210 – 214 . Ed. by Benson K. R., Rehbock P.. University of Washington Press , Seattle, WA, USA . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Kroll G. 1970 . America’s Ocean Wilderness: A Cultural History of Twentieth-Century Exploration . University of Kansas , Lawrence, KS, USA . 249 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Levick M. B. 1925 . Old Myths Defy the Light of Science. N.Y. Times, August 30, p SM11. Matsen B. 2005 . Descent: The Heroic Discovery of the Abyss . Pantheon Books , New York . 286 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Marshall N. B. 1979 . Developments in Deep-Sea Biology . Blandford , Poole, Dorset . 566 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Mills E. L. 1983 . Problems of deep-sea biology: an historical perspective. In The Sea V.8 , pp. 1 – 79 . Ed. by Roxwe G. T.. John Wiley & Sons , San Francisco, CA, USA . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Mills E. L. 1989 . Biological Oceanography: An Early History . Cornell University Press , Ithaca, NY, USA . 378 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Mendyk R. W. 2014 . The herpetological contributions of William Beebe: naturalist, explorer, and father of neotropical ecology . Herpetological Review , 45 : 76 – 84 . OpenURL Placeholder Text WorldCat Morell V. 2019 . Becoming a Marine Biologist . Simon & Schuster , New York . 193 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Murray J. , Hjort J. 1912 . The Depths of the Ocean . Macmillan and Co ., London . 821 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Nichols J. T. 1934 a. Half mile down . Natural History , 35 : 88 – 89 . OpenURL Placeholder Text WorldCat Nichols J. T. 1934 b. Life in the Bathysphere. Saturday Review of Literature, December 8 1934. Nigrelli R. F. 1947 . Spontaneous neoplasms in fishes. Fibro-carcinoma-like growth in the stomach of Borophryne apogon Regan, a deep-sea ceratoid fish . Zoologica , 31 : 183 – 184 . OpenURL Placeholder Text WorldCat Pickford G. E. 1950 . The Vampyromorpha (Cephalopoda) of the Bermuda Oceanographic expeditions . Zoologica , 35 : 87 – 95 . OpenURL Placeholder Text WorldCat Poulsen B. 2016 . Global Marine Science and Carlsberg: The Golden Connections of Johannes Schmidt (1877-1933) . Brill , Leiden . 524 pp. Google Scholar Crossref Search ADS Google Scholar Google Preview WorldCat COPAC Quinn W. H. , Neal V. T., Antunez De Mayolo S. E. 1987 . El Nino occurrences over the past four and half centuries . Journal of Geophysical Research , 92 : 14449 – 14461 . Google Scholar Crossref Search ADS WorldCat Riedl R. 1980 . Marine ecology—a century of changes . Marine Ecology , 1 : 3 – 46 . Google Scholar Crossref Search ADS WorldCat Robson G. C. 1948 . The cephalopoda decapoda of the Arcturus Oceanographic expedition, 1925 . Zoologica , 33 : 115 – 132 . OpenURL Placeholder Text WorldCat Russo G. 2010 . Meet the press . Nature , 468 : 465 – 467 . Google Scholar Crossref Search ADS WorldCat Shermer M. B. 2002 . This view of science: Stephen Jay Gould as historian of science and scientific historian, popular scientist and scientific popularizer . Social Studies of Science , 32 : 489 – 525 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Shoemaker C. R. 1945 . The Amphipoda of the Bermuda Oceanographic expeditions, 1929–1931 . Zoologica , 30 : 185 – 266 . OpenURL Placeholder Text WorldCat Tattersall W. M. 1936 . Plankton of the Bermuda Oceanographic expeditions. V. Notes on Schizopoda . Zoologica , 21 : 95 – 96 . OpenURL Placeholder Text WorldCat Tee-Van J. 1926 . The Arcturus: equipment and operation . Zoologica , 8 : 47 – 106 . OpenURL Placeholder Text WorldCat Totton A. K. 1936 . Plankton of the Bermuda Oceanographic expeditions. VII. Siphonophora taken during the year 1931 . Zoologica , 21 : 231 – 240 . OpenURL Placeholder Text WorldCat Treadwell A. L. 1928 . Polychaetous annelids from the Arcturus Oceanographic expedition . Zoologica , 8 : 449 – 485 . OpenURL Placeholder Text WorldCat Treadwell A. L. 1941 . Plankton of the Bermuda Oceanographic expeditions, X: polychaetous annelids from Bermuda plankton, with eight shore species, and four from Haiti . Zoologica , 26 : 25 – 30 . OpenURL Placeholder Text WorldCat Trotter E. S. 1926 . Brotulid fishes from the Arcturus Oceanographic expedition . Zoologica , 8 : 107 – 125 . OpenURL Placeholder Text WorldCat Vergin K. , Beszteri B., Monier A., Thrash J. C., Temperton B., Treusch A. H., Kilper F., et al. 2013 . High-resolution SAR11 ecotype dynamics at the Bermuda Atlantic time-series study site by phylogenetic placement of pyrosequences . ISME Journal , 7 : 1322 – 1332 . Google Scholar Crossref Search ADS PubMed WorldCat Welker R. H. 1975 . Natural Man: The Life of William Beebe . Indiana University Press , Bloomington, IN, USA . 224 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Wailes G. H. 1936 . Plankton of the Bermuda Oceanographic expeditions. II. Notes on protozoa . Zoologica , 21 : 81 – 84 . OpenURL Placeholder Text WorldCat Wilson C. B. 1936 . Plankton of the Bermuda Oceanographic expeditions. IV. Notes on Copodea . Zoologica , 21 : 89 – 93 . OpenURL Placeholder Text WorldCat Wooster W. S. 1980 . Early observations and investigation of El Nino: the event of 1925. In Oceanography: The Past , pp. 629 – 641 . Ed. by Sears M., Merriman D. III. Springer-Verlag , New York . Google Scholar Crossref Search ADS Google Scholar Google Preview WorldCat COPAC WoRMS Editorial Board 2020 . World Register of Marine Species. VLIZ. http://www.marinespecies.org (last accessed 24 February 2020). Wüst G. T. 1964 . The major deep-sea expeditions and research vessels 1873-1960, a contribution to the history of oceanography . Progress in Oceanography , 2 : 1 – 52 . Google Scholar Crossref Search ADS WorldCat Yost E. 1959 . Women of Modern Science. Dodd, Mead & Company , New York . 176 pp. © International Council for the Exploration of the Sea 2020. All rights reserved. For permissions, please email: [email protected] This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Koenigstein,, Stefan;Hentschel,, Lisa-Henrike;Heel, Lena, Christin;Drinkorn,, Catherine

doi: 10.1093/icesjms/fsaa035pmid: N/A

Abstract The goods and services of the ocean are increasingly threatened by anthropogenic pressures and climate change. Novel approaches for an integrated education for sustainable ocean development are needed, to teach an understanding of ocean systems and their sustainable governance to future generations of users and consumers. We developed a table-top, role-playing game for marine sustainability education at the high school level and above. Ocean Limited lets players negotiate their uses and interactions as ocean stakeholders, providing a comprehensive social–ecological integration of global ocean systems, marine sustainability challenges, and climate change impacts. Observations of in-game player behaviour, game results, and player feedback indicate that players understood the game world, identified with their roles, and actively engaged as ocean stakeholders. Ocean Limited stimulated empathy for other actors, systemic and foresighted thinking, and the development of sustainability-oriented cooperation and agreements. The game can demonstrate and teach real-world marine sustainability issues, and could support collective learning of problem-solving capacities for social–ecological conflicts and trade-offs in ocean uses. We suggest using role-playing game-based approaches for an integrated marine sustainability education, to train students the skills needed to participate in and support sustainable ocean development. Introduction The ocean provides vital resources and services to societies around the globe, including food provision from fisheries and aquaculture, raw materials, and cultural services such as recreation and identity (Millenium Ecosystem Assessment, 2005; Beaumont et al., 2007). The ocean is, therefore, highly disputed among a wide range of stakeholders: competition for resources and space involves users from local subsistence fishers to international shipping and energy corporations (Park and Kildow, 2014; Klinger et al., 2018). The impacts of ocean uses, such as overfishing, marine debris, and other pollution, the destruction of unique habitats such as coral reefs, and limited governance and regulation are challenges for global sustainable development, prompting the United Nations to declare 2021–2030 the decade of Ocean Science for Sustainable Development (United Nations, 2017; www.oceandecade.org). Global climate change is increasingly affecting ocean systems and their services and represents a major challenge for sustainable marine governance in the 21st century (Perry et al., 2011; Charles, 2012; IPCC, 2019). The growing recognition of the multifaceted interactions among environmental drivers, ocean services, and their users has led to integrated and ecosystem-based approaches for marine spatial planning and resource management (Foley et al., 2010; Long et al., 2015). An integrative systems perspective, which links elements and describes their interactions across scales, is thus necessary for sustainable ocean governance (Perry et al., 2010; Charles, 2012; Osterblom et al., 2016). As a basis for sustainable ocean development, this integrated social–ecological perspective should also be reflected in education of future generations of consumers and ocean users. That “the ocean and humans are inextricably interconnected” has been defined as one of the seven “essential principles of Ocean Literacy” by a network of US science and education organizations (Cava et al., 2005; NOAA, 2013). An “education for sustainable development” addresses environmental issues in interdisciplinary-, participatory-, and inquiry-based approaches that promote critical thinking (Sauvé, 1996; Vare and Scott, 2007). This enables learners to imagine future scenarios and make collaborative decisions, thus motivating them towards more sustainable behaviour (Chawla and Cushing, 2007; UNESCO, 2018). Thus, an integrated marine sustainability education needs to incorporate the different perspectives and interests of ocean users and stakeholders. To promote environmental engagement, it needs to be informed by an understanding of factors governing individual behaviour, such as social norms and values (Zaval and Cornwell, 2017). Game-based learning is an educational approach that can integrate multiple scientific topics into one learning activity, facilitate learning by contextualizing new information within existing knowledge and personal experience, and encourage active participation and stewardship (Cordova and Lepper, 1996; Foster, 2008). By employing both cognitive and affective learning, simulation games can lead to more efficient teaching of “real-world problems”, especially when integrated with other instructional methods (Sitzmann, 2011; Wouters et al., 2013). Games have been used to link scientific and social aspects of environmental problems (Swinerton, 1972; Bazan, 1976) and are promising tools for teaching complex system interactions, to address modern global sustainability challenges (Victoria Uribe and Utrilla Cobos, 2014). Educational games have been developed for ocean topics such as fisheries sustainability, conservation of marine ecosystems and coastal habitats, or flooding (Supplementary Material; https://meam.openchannels.org/games). Here, we present the development and initial testing of a novel game-based approach for marine sustainability education, which integrates a wide range of global ocean resources, users, and ecosystem attributes, aimed at high school students and young adult groups. The primary aim of the game is to immerge players as ocean stakeholders into a game world, where topical issues in global ocean sustainability are linked among each other and to the players’ personal actions—as opposed to a game acting merely as a vehicle for educational content. We explore the following questions: Can a comprehensive representation of global ocean users and sustainability-relevant topics be achieved in a game framework? (“Game-based integration …”) Do players engage actively in the game, identify with their roles, and take up social interactions as ocean stakeholders? (“Playing the game”) Do players consider the impacts of their in-game actions for the ocean and other users, and do they link their own real-world behaviour to the contents of the game? (“Sustainability-related behaviour and decision making”) Game-based integration of global ocean users and sustainability challenges Game mechanics We developed a table-top board game with a strong role-playing component, in which players take over the roles of actual ocean stakeholders. We chose to develop a physical, board-based game without digital game components, in order to maximize social interaction time and opportunities for in-game discussions among the players (Xu et al., 2011; Kaufman and Flanagan, 2016). Furthermore, we wanted to avoid potential distraction by technological equipment in a class-room setting with large groups. The game was developed between September 2016 and December 2018, by a team of six early career ocean scientists, game and graphic designers, and environmental educators (www.ocean-limited.com). In the game, all characters possess a spectrum of options for actions and ocean uses, from more egoistic and/or impactful to more cooperative and sustainable. We aimed to minimize external direction towards sustainable behaviour, to allow for the reflection of the players’ personal values and social interactions in their decisions. A common game currency, “power points”, represents socio-economic capital as a basis for income, trading, and compensation in the game. Competition for marine space and resources, the environmental effects of high-impact ocean uses, and climate change impacts on the ocean become more marked as the game progresses, and players should realize the need for agreements aiming at a more sustainable use and distribution of marine resources and areas. Game mechanics in Ocean Limited share similarities with “serious games” (Abt, 1970) utilized for example in marine spatial planning or fisheries economics, which are played with the actual stakeholders and policy-makers in a local resource system (e.g. Verutes and Rosenthal, 2014; Finkbeiner et al., 2018; Abspoel et al., 2019). Common aspects incorporated during game development were (i) the provision of character roles with specific goals, (ii) incomplete and asymmetrical availability of information to the characters, (iii) ethical ambiguity and personal subjectivity, and (iv) uncertainty about the future (Mayer et al., 2013; Keijser et al., 2018). However, our game is intended for use in education, takes up a global perspective, and is not limited to the actors and resources in a specific local marine social–ecological system. Game characters and interactions A set of game characters was created to let players participate personally in sustainability-related decisions as ocean stakeholders. The main challenge of game development was to integrate diverse and interrelated global ocean stakeholders and impacts into a game playable and understandable for a broad audience, whilst representing major interactions of real-world marine social–ecological systems. The most relevant ecosystem services provided by the global ocean, user groups of marine systems and their interactions, and impacts of human uses and climate change on the marine environment were collected from the scientific literature, government reports, news outlets, and ocean-themed internet portals. Iterative simplification and extension of character descriptions and interactions during game development and play testing led to a social–ecological interaction network of 11 ocean stakeholders, with a limited number of 3–4 interaction options for most characters (Figure 1). The major ocean economic sectors shipping, living marine resources (fisheries and aquaculture), hydrocarbon and mineral resources, renewable energies, tourism and recreation, marine construction and infrastructure, as well as education, public administration, and research and development, are represented in the game (Park et al., 2014; NOEP, 2016; Klinger et al., 2018). Briefing sheets and individual ocean maps for the game characters were designed with custom illustrations in a distinctive character colour and high-quality printed in colour on heavy paper. Figure 1. Open in new tabDownload slide Social–ecological network of the principal interactions among game characters and marine resources in Ocean Limited. Direct ocean users (solid circles), non-use characters (dashed circles), and marine resources (boxes) are linked by resource uses (solid lines), and game character actions (dashed lines). Depicted are interactions explicitly given in game character sheets (further interactions are created by competition for ocean space on the game map, the gameplay functions of the characters “Journalist” and “Soul of the Seas”, and creative character interpretation by the players). Figure 1. Open in new tabDownload slide Social–ecological network of the principal interactions among game characters and marine resources in Ocean Limited. Direct ocean users (solid circles), non-use characters (dashed circles), and marine resources (boxes) are linked by resource uses (solid lines), and game character actions (dashed lines). Depicted are interactions explicitly given in game character sheets (further interactions are created by competition for ocean space on the game map, the gameplay functions of the characters “Journalist” and “Soul of the Seas”, and creative character interpretation by the players). The incorporated game characters belong to two main categories, ocean users and non-use stakeholders (Table 1). Ocean user game characters have the primary goal to gain power points by building facilities on the game map (e.g. fishing boats, oil platforms, aquaculture installations, and shipping routes). These characters can choose among up to three character-specific ocean use activities, which differ in their severity of impact on the oceans (high-impact, medium-impact, and low-impact uses; cf. Table 1). Ocean uses are visualized by acrylic glass game tiles in different transparency levels (dark, semi-transparent, and transparent) placed onto ocean cells on the game map. High-impact uses generally provide higher income per round, whereas lower-impact options have lower potential for conflicts, because of lower impacts on the marine environment and the resources used by other players. Some options for generating income require cooperation with another character (e.g. oil platforms require connection to oil tanker routes) and some of the information necessary for generating income, for example location of fish stocks or sea-bottom resources, are distributed among the characters, to encourage communication and information exchange. Table 1. Game characters and their basic activities (a) tile-based characters (ocean users) and (b) token-based characters (non-use ocean stakeholders). Name . Starting power points . Personal ocean map . High-impact use . Medium-impact use . Low-impact use . Development option . (a) Ocean users (tile-based characters)  Small-scale fisher 20 – – Fishing – Buy further boats Whale watching (with tourism)  Commercial fisher 30 Pelagic and groundfish stocks Bottom-trawl fishing Open-ocean fishing – Certified sustainable fishing (low-impact activity)  Aquaculture farmer 30 Mangroves Shrimp farm Fish farm – Integrated aquaculture (low-impact activity)  Tourism entrepreneur 20 – Mass tourism Ecotourism –  Shipping company C.E.O. 50 – – Cargo shipping route – Cruise-ship terminal Oil tanker route  Energy company manager 100 Oil and gas deposits Oil platform Wind farm – Deep-sea mining (b) Non-use ocean stakeholders (token-based characters)  Mayor 100 – Coastal city Announce laws, collect taxes, pay subsidies Found another city  Environmentalist 20 Coral reefs, whales, mangroves Marine protected areas Propose environmental laws Sabotage  Scientist 20 Fish stocks, deep-sea habitats, deep-sea minerals – Investigate background information Technological innovations  Journalist 20 – – Announce game events, investigate stories –  Soul of the Seas – Coral reefs, deep-sea habitats, polar habitats – Decide on events, influence players – Name . Starting power points . Personal ocean map . High-impact use . Medium-impact use . Low-impact use . Development option . (a) Ocean users (tile-based characters)  Small-scale fisher 20 – – Fishing – Buy further boats Whale watching (with tourism)  Commercial fisher 30 Pelagic and groundfish stocks Bottom-trawl fishing Open-ocean fishing – Certified sustainable fishing (low-impact activity)  Aquaculture farmer 30 Mangroves Shrimp farm Fish farm – Integrated aquaculture (low-impact activity)  Tourism entrepreneur 20 – Mass tourism Ecotourism –  Shipping company C.E.O. 50 – – Cargo shipping route – Cruise-ship terminal Oil tanker route  Energy company manager 100 Oil and gas deposits Oil platform Wind farm – Deep-sea mining (b) Non-use ocean stakeholders (token-based characters)  Mayor 100 – Coastal city Announce laws, collect taxes, pay subsidies Found another city  Environmentalist 20 Coral reefs, whales, mangroves Marine protected areas Propose environmental laws Sabotage  Scientist 20 Fish stocks, deep-sea habitats, deep-sea minerals – Investigate background information Technological innovations  Journalist 20 – – Announce game events, investigate stories –  Soul of the Seas – Coral reefs, deep-sea habitats, polar habitats – Decide on events, influence players – Given are name of the character (bold type gives short name used elsewhere in this article), amount of power points at the beginning of the game, personal ocean map with spatial information provided to player, possible ocean uses with high, medium and low environmental impact (for non-use characters: build options and other, interaction-based activities), and development option at a later stage in the game. Open in new tab Table 1. Game characters and their basic activities (a) tile-based characters (ocean users) and (b) token-based characters (non-use ocean stakeholders). Name . Starting power points . Personal ocean map . High-impact use . Medium-impact use . Low-impact use . Development option . (a) Ocean users (tile-based characters)  Small-scale fisher 20 – – Fishing – Buy further boats Whale watching (with tourism)  Commercial fisher 30 Pelagic and groundfish stocks Bottom-trawl fishing Open-ocean fishing – Certified sustainable fishing (low-impact activity)  Aquaculture farmer 30 Mangroves Shrimp farm Fish farm – Integrated aquaculture (low-impact activity)  Tourism entrepreneur 20 – Mass tourism Ecotourism –  Shipping company C.E.O. 50 – – Cargo shipping route – Cruise-ship terminal Oil tanker route  Energy company manager 100 Oil and gas deposits Oil platform Wind farm – Deep-sea mining (b) Non-use ocean stakeholders (token-based characters)  Mayor 100 – Coastal city Announce laws, collect taxes, pay subsidies Found another city  Environmentalist 20 Coral reefs, whales, mangroves Marine protected areas Propose environmental laws Sabotage  Scientist 20 Fish stocks, deep-sea habitats, deep-sea minerals – Investigate background information Technological innovations  Journalist 20 – – Announce game events, investigate stories –  Soul of the Seas – Coral reefs, deep-sea habitats, polar habitats – Decide on events, influence players – Name . Starting power points . Personal ocean map . High-impact use . Medium-impact use . Low-impact use . Development option . (a) Ocean users (tile-based characters)  Small-scale fisher 20 – – Fishing – Buy further boats Whale watching (with tourism)  Commercial fisher 30 Pelagic and groundfish stocks Bottom-trawl fishing Open-ocean fishing – Certified sustainable fishing (low-impact activity)  Aquaculture farmer 30 Mangroves Shrimp farm Fish farm – Integrated aquaculture (low-impact activity)  Tourism entrepreneur 20 – Mass tourism Ecotourism –  Shipping company C.E.O. 50 – – Cargo shipping route – Cruise-ship terminal Oil tanker route  Energy company manager 100 Oil and gas deposits Oil platform Wind farm – Deep-sea mining (b) Non-use ocean stakeholders (token-based characters)  Mayor 100 – Coastal city Announce laws, collect taxes, pay subsidies Found another city  Environmentalist 20 Coral reefs, whales, mangroves Marine protected areas Propose environmental laws Sabotage  Scientist 20 Fish stocks, deep-sea habitats, deep-sea minerals – Investigate background information Technological innovations  Journalist 20 – – Announce game events, investigate stories –  Soul of the Seas – Coral reefs, deep-sea habitats, polar habitats – Decide on events, influence players – Given are name of the character (bold type gives short name used elsewhere in this article), amount of power points at the beginning of the game, personal ocean map with spatial information provided to player, possible ocean uses with high, medium and low environmental impact (for non-use characters: build options and other, interaction-based activities), and development option at a later stage in the game. Open in new tab Non-use game characters are represented by a single token on the game map and can act out more creative interactions with other characters (e.g. information exchange, advice, technological cooperation, and social influencing). The Mayor governs a coastal city and represents one of the central characters in the game (cf. Figure 1), negotiating with all other characters their use of the coastal city. The Scientist is allowed to examine other players’ character sheets and the event cards and can provide some characters with new ocean use options later in the game (sustainable fisheries, deep-sea mining, and integrated aquaculture). The Environmentalist aims to protect the ocean by lobbying and designating marine protected areas, which restrict ocean uses. The Soul of the Seas character acts as a “personification of the ocean”, tasked to protect unique ocean habitats, and can select ocean areas or facilities affected by game events. The Journalist announces game events and self-investigated background stories to the group. Each character is described in a character sheet, which provides (i) a short background text about the character, (ii) the personal goal of the character, (iii) an overview of interactions with other characters, (iv) the possible actions and incomes from activities, and (v) future development options that can be realized later in the game (Figure 2). The character goals serve to explain the motivation of the character and facilitate identification with the role (players remain in the game after reaching their goal). The texts include diverse, ambiguous hints to possible egoistic or cooperative in-game behaviours, but no instruction towards sustainable behaviour. Six of the characters also receive a personal ocean map, which shows the distribution of relevant ocean resources or habitats (fish stocks, oil and gas deposits, coral reefs, mangrove forests, deep-sea habitats, and whales). Figure 2. Open in new tabDownload slide Example of Ocean Limited character sheet with information given to players, for one of the 11 game characters (Small-scale Fisher). Sheets include background information about the character, a personal goal, overview of interactions with other characters, possible actions and incomes from activities, and future development options. Figure 2. Open in new tabDownload slide Example of Ocean Limited character sheet with information given to players, for one of the 11 game characters (Small-scale Fisher). Sheets include background information about the character, a personal goal, overview of interactions with other characters, possible actions and incomes from activities, and future development options. Figure 3. Open in new tabDownload slide Ocean Limited played by high school students at test game 3. Picture shows the game map, ocean use tiles, character sheets, power points (different types of beans stored in glasses), personal notes of the players, and game round timer and counter (hourglass). Figure 3. Open in new tabDownload slide Ocean Limited played by high school students at test game 3. Picture shows the game map, ocean use tiles, character sheets, power points (different types of beans stored in glasses), personal notes of the players, and game round timer and counter (hourglass). Game events and ocean sustainability content Important challenges to marine sustainability, for example different types of marine pollution, overfishing, invasive species, destruction of habitats such as coral reefs, and the impacts of climate change (Bollmann et al., 2010; United Nations, 2017; IPCC, 2019) are incorporated through 20 different game events (Table 2). In the game events, external drivers (e.g. climate) of ocean systems, and technical accidents of human uses, impact the ocean and affect the economic activities and income of the players. Event impacts generally become more severe in the course of the game, and in later rounds, progressively stronger climate change impacts take place. Many events are linked to ocean uses, occurring where specific tiles have been placed on the game map and affecting other users within a certain radius. Some characters, for example small-scale and commercial fishers, are impacted by more game events than other characters (cf. Table 2). Table 2. Game events and affected game characters. Name . Round . Impacted characters . New ocean exploration technologies 1 Small-scale fisher, Commercial fisher, Aquaculture, Energy company (positive impact) Medical compounds from the ocean 1 Scientist, Journalist, Environmentalist, Mayor (positive impact) Coastal overfertilization 2 Small-scale fisher, Commercial fisher, Aquaculture, Tourism Trash on beaches 2 Tourism Toxic seafood 2 Small-scale fisher, Commercial fisher, Aquaculture, Mayor Invasive jellyfish from ballast water 2 Small-scale fisher, Commercial fisher, Tourism, Environmentalist Fish escaped from aquaculture 2 Small-scale fisher, Commercial fisher, Tourism, Environmentalist Cargo ship collision 2 Shipping Fisheries moratorium 2 Small-scale fisher, Commercial fisher Stranded whales with plastic in stomachs 3 Tourism, Environmentalist El Niño 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism Fish stock collapse 3 Small-scale fisher, Commercial fisher Oil tanker spill 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Shipping Oil drilling accident 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Energy Fish stock distribution shifts 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Environmentalist Ice melt and sea-level rise 3 Energy, Mayor, Shipping Flash flood 4 Aquaculture, Tourism, Shipping, Energy, Mayor Coral bleaching 4 Small-scale fisher, Commercial fisher, Tourism Ocean acidification 5 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Environmentalist Tsunami 5 Aquaculture, Tourism, Energy, Mayor Name . Round . Impacted characters . New ocean exploration technologies 1 Small-scale fisher, Commercial fisher, Aquaculture, Energy company (positive impact) Medical compounds from the ocean 1 Scientist, Journalist, Environmentalist, Mayor (positive impact) Coastal overfertilization 2 Small-scale fisher, Commercial fisher, Aquaculture, Tourism Trash on beaches 2 Tourism Toxic seafood 2 Small-scale fisher, Commercial fisher, Aquaculture, Mayor Invasive jellyfish from ballast water 2 Small-scale fisher, Commercial fisher, Tourism, Environmentalist Fish escaped from aquaculture 2 Small-scale fisher, Commercial fisher, Tourism, Environmentalist Cargo ship collision 2 Shipping Fisheries moratorium 2 Small-scale fisher, Commercial fisher Stranded whales with plastic in stomachs 3 Tourism, Environmentalist El Niño 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism Fish stock collapse 3 Small-scale fisher, Commercial fisher Oil tanker spill 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Shipping Oil drilling accident 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Energy Fish stock distribution shifts 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Environmentalist Ice melt and sea-level rise 3 Energy, Mayor, Shipping Flash flood 4 Aquaculture, Tourism, Shipping, Energy, Mayor Coral bleaching 4 Small-scale fisher, Commercial fisher, Tourism Ocean acidification 5 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Environmentalist Tsunami 5 Aquaculture, Tourism, Energy, Mayor Short description (event name), earliest round in which the event can happen, and game characters impacted by the event. Open in new tab Table 2. Game events and affected game characters. Name . Round . Impacted characters . New ocean exploration technologies 1 Small-scale fisher, Commercial fisher, Aquaculture, Energy company (positive impact) Medical compounds from the ocean 1 Scientist, Journalist, Environmentalist, Mayor (positive impact) Coastal overfertilization 2 Small-scale fisher, Commercial fisher, Aquaculture, Tourism Trash on beaches 2 Tourism Toxic seafood 2 Small-scale fisher, Commercial fisher, Aquaculture, Mayor Invasive jellyfish from ballast water 2 Small-scale fisher, Commercial fisher, Tourism, Environmentalist Fish escaped from aquaculture 2 Small-scale fisher, Commercial fisher, Tourism, Environmentalist Cargo ship collision 2 Shipping Fisheries moratorium 2 Small-scale fisher, Commercial fisher Stranded whales with plastic in stomachs 3 Tourism, Environmentalist El Niño 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism Fish stock collapse 3 Small-scale fisher, Commercial fisher Oil tanker spill 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Shipping Oil drilling accident 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Energy Fish stock distribution shifts 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Environmentalist Ice melt and sea-level rise 3 Energy, Mayor, Shipping Flash flood 4 Aquaculture, Tourism, Shipping, Energy, Mayor Coral bleaching 4 Small-scale fisher, Commercial fisher, Tourism Ocean acidification 5 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Environmentalist Tsunami 5 Aquaculture, Tourism, Energy, Mayor Name . Round . Impacted characters . New ocean exploration technologies 1 Small-scale fisher, Commercial fisher, Aquaculture, Energy company (positive impact) Medical compounds from the ocean 1 Scientist, Journalist, Environmentalist, Mayor (positive impact) Coastal overfertilization 2 Small-scale fisher, Commercial fisher, Aquaculture, Tourism Trash on beaches 2 Tourism Toxic seafood 2 Small-scale fisher, Commercial fisher, Aquaculture, Mayor Invasive jellyfish from ballast water 2 Small-scale fisher, Commercial fisher, Tourism, Environmentalist Fish escaped from aquaculture 2 Small-scale fisher, Commercial fisher, Tourism, Environmentalist Cargo ship collision 2 Shipping Fisheries moratorium 2 Small-scale fisher, Commercial fisher Stranded whales with plastic in stomachs 3 Tourism, Environmentalist El Niño 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism Fish stock collapse 3 Small-scale fisher, Commercial fisher Oil tanker spill 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Shipping Oil drilling accident 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Energy Fish stock distribution shifts 3 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Environmentalist Ice melt and sea-level rise 3 Energy, Mayor, Shipping Flash flood 4 Aquaculture, Tourism, Shipping, Energy, Mayor Coral bleaching 4 Small-scale fisher, Commercial fisher, Tourism Ocean acidification 5 Small-scale fisher, Commercial fisher, Aquaculture, Tourism, Environmentalist Tsunami 5 Aquaculture, Tourism, Energy, Mayor Short description (event name), earliest round in which the event can happen, and game characters impacted by the event. Open in new tab Each game round, the Soul of the Seas character chooses an event card with an event to take place. For events that are primarily caused by or linked to human uses (e.g. oil platform accident and coastal eutrophication), an affected facility or ocean region is decided by rolling a dice. For external or “natural” events (e.g. flooding and extreme climate events), the Soul of the Seas chooses an affected ocean region or facility. The selection of event cards can be adjusted before a game, to focus on certain educational topics. The game map was designed to show the connectedness and real proportional size of the world oceans, whilst splitting up the continents. It is based on a Spilhaus projection (conformal “World Ocean Map in a Square”; Spilhaus, 1991) and printed in colour on polyvinyl canvas. The ocean-centred game map provides a reframing of players’ geographical knowledge and allows to depict global economic linkages (e.g. intercontinental shipping lines) and regional ocean characteristics, such as climatic zones or upwelling regions. On the background of increasing internationalization and integration of knowledge on marine systems and their human uses, both in science and policy arenas (Rice et al., 2014; Markus et al., 2018), the global scale of the game increases the potential for use in an integrated marine sustainability education. The final game covers the majority of the educational concepts for grades 9–12 defined for the principle “the ocean and humans are inextricably interconnected” in the US “Ocean Literacy” framework (NMEA, 2010). Although the game does currently not incorporate a changeable common resource pool for fish stocks, actual sizes of important fish stocks are approximated by spatial extent (number of fishable ocean cells for ocean regions), and topics such as natural variability, impacts of bottom trawling, and sustainability certification, are covered in game events and character action options. The game further incorporates the most important climate change impacts on the oceans, such as sea-level rise, polar ice melting, coral bleaching, and shifts in distribution and productivity of marine species under ocean warming, oxygen deficiency, and acidification (Doney et al., 2012; IPCC, 2019), which affect most of the ocean user groups represented in the game (cf. Allison and Bassett, 2015; Gattuso et al., 2015). An effect of player behaviour (greenhouse gas emissions through human economic activities) on the severity of climate change is currently not integrated into the game but can be part of complementary instructional materials. Ocean Limited thus achieves a comprehensive integration of global ocean goods, services, user groups, and climate change impacts, with a generalized social–ecological systems framework (cf. Figure 1) as a basis for game mechanics. The game serves as an integrative educational framework for more detailed and specific learning material on marine sustainability challenges and their solutions. Playing the game Test games We conducted eight documented test games with different groups to evaluate players’ understanding of the game world and participation in the game. Test games were conducted with students and young adults aged 14–25 in high school classes and environmental education courses, in seven locations near the German Baltic and North Sea coasts between August 2017 and June 2019 (Figure 3, Supplementary Table S1). Games were led by two or three members of the development team, who supervised and moderated the game, answered questions, observed player behaviour, interactions and discussions in the game, and recorded the game outcome (tiles on the game map and players’ power points). As power points, we use dried beans of three different kinds, and each player receives a glass or other receptacle to store power points visibly for the other players. An hourglass is used to measure and display the 10-min time limit for each round, and a horn or gong is used to announce the end of the round. Before the game, a short (∼15 min) introduction to the game, its characters, and topics is given. Players then choose one of the game characters and receive their character sheet, ocean use tiles or character token, and power points. During a “placement phase” (10 min), characters build their facilities by placing tiles onto the game map, move their tokens, and negotiate openly or secretly at any time. Afterwards, in the “event phase”, a game event is announced to all players, and its consequences (e.g. destruction or temporary disablement of facilities) are conducted on the game map. The Journalist announces further self-investigated stories or laws and contracts agreed upon by the players. At the end of each round, in the “payout phase”, the players receive power points earned this round from the bank, and taxes and subsidies among the Mayor and other players are paid. After four to five game rounds, the gamemaster can announce an “Ocean Council”, in which Environmentalists and Scientists may propose a law for marine conservation. The law is discussed and a majority vote held among the Mayors and possibly other affected characters. After about six to nine rounds (90–120 min), the last round is announced and played. It is checked which of the players have reached their personal goals, and the end-state of game tiles on the maps and power points are recorded. After the game, a moderated group discussion covers the players’ general perception of the game, conflicts and collaboration with other characters, anthropogenic and climate change impacts on the ocean, and other content learned from the game. Players’ understanding of the game world and game results We collected observations of player behaviour from game supervisors, oral and written player feedback, and teacher feedback and recorded results of the test games to evaluate if players understand basic game mechanics, engage actively in the game, identify with their role, and take up social interactions as ocean stakeholders (cf. Supplementary Material). In the first one to two rounds of each game, most players had technical questions about their character’s possible actions and interactions, especially on where to build facilities (place game tiles) and how to earn power points. Virtually all test players participated actively in the game, placing chips and talking to other players about game actions. Ocean user game characters (Shipping Company, Energy Company, Commercial Fisher, Aquaculture, and Tourism Entrepreneurs) generally started earlier to participate actively in the game. The economic ocean uses of those characters (building facilities and earning and trading power points) have been initially easier to understand for students, especially of the younger age groups, and appear to be more easily linked to every-day experiences and experience with other games. The non-use characters such as Mayors, Scientists, and Environmentalists, which require some more complex decision making, often observed the game without interfering much for the first one or two rounds in test games with high schools, but then started to increasingly adopt an active role in group discussions. Frequent observations of in-game discussions among players about the impact of dark ocean use tiles, especially in later game rounds, and mentioning of decisions among low- and high-impact uses in player feedback indicate that the majority of players understood the differences between high-impact and lower-impact ocean uses. The highest spatial densities of ocean use tiles generally occurred in coastal areas, and open ocean areas were less densely used (Figure 4). All players succeeded in earning power points during the game, and the economic characters Shipping company, Energy company, and Industrial fisher in most games were the players with the highest number of power points earned. In the games with environmental education groups, protection of the marine environment was a more common topic in player discussions, and ocean user characters used low-impact tiles earlier in the game, and slightly more often than in games with high schools. Overall, relative numbers of transparent, semi-transparent, and dark tiles at the end of each test game were remarkably constant among games with different groups (Supplementary Material), which points to a good balance between economic uses and conservation interests in the game. Figure 4. Open in new tabDownload slide Ocean Limited game map (German version) after the final round of a test game, with ocean use tiles from different characters and in different opacities (transparent, semi-transparent, and dark tiles), and game round timer and counter (hourglass, bottom left). Figure 4. Open in new tabDownload slide Ocean Limited game map (German version) after the final round of a test game, with ocean use tiles from different characters and in different opacities (transparent, semi-transparent, and dark tiles), and game round timer and counter (hourglass, bottom left). Players routinely referenced to their role in the game in first-person, and frequently mentioned interactions with other characters in their feedback after the game (Supplementary Material). The role-playing components of the game allowed it for some players to go beyond the character actions and interactions described in their briefing sheets: a Journalist started to buy and sell wind-energy facilities, and a Shipping Company CEO worked with a Scientist to invent less polluting, electric transport vessels. A Small-scale Fisher later in the game sold all his boats to another fisher and donated his power points to the Environmentalist. The players in all test groups, students from age 15 and participants in environmental education courses aged 14 and older, thus understood the game world well enough to participate actively in the game. The game succeeded to encourage peer communication about ocean uses and their impacts and create personal identification with ocean users and awareness about interdependency of users. These are important prerequisites for social learning, one of the strengths of game-based learning approaches, increasing the potential for conveying knowledge on ocean systems, and providing context for other teaching materials (Lee et al., 2013; Gordon and Baldwin-Philippi, 2014; Victoria Uribe and Utrilla Cobos, 2014; Rumore et al., 2016). Sustainability-related behaviour and decision making in the game Conflicts, collaboration, and social influencing To assess if players consider the impacts of their actions on other players and the marine environment, the game supervisors recorded the main topics of in-game discussions among players, obvious conflicts, collaboration, and formal agreements (Supplementary Material). After the second or third round, observed in-game discussions started to shift away from where and how activities can happen in the game, and began to centre on risks or negative impacts of intensive ocean uses, spatial competition among users, and the necessity to keep the ocean healthy to maintain its resources. These points were also often mentioned in player feedback after the game. Game events related to impacts of human uses or climate change often triggered controversies among the players about ocean uses. With progressing game time, ocean use characters discussed risks, negative impacts, and potential conflicts with other players before placing game tiles more frequently and made more use of their lower-impact actions in all test games. Intensifying human impacts and conflicts among users in “crowded” coastal-ocean areas mirrors real-world challenges for marine spatial planning (Portman, 2011; Clarke Murray et al., 2015). Environmentalists started to seek coalitions with Journalists, Scientists, and Mayors and increasingly succeeded in convincing other players to use more sustainable options, resorting to the “Sabotage” option only once in the test games. In five of the test games, at least one Commercial Fisher worked together with Scientists and Environmentalists to develop certified sustainable fisheries (transparent tiles). Mayors agreed among each other on different environmental laws to reduce impacts on the ocean, in the “Ocean Councils” or in direct response to game events depicting accidents in human uses and climate change impacts. For instance, ocean uses around coastal cities were restricted to low- and moderate-impact uses (transparent and semi-transparent tiles), or new ocean uses restricted globally to not more than one high-impact facility (dark tile) per coastal city, or five dark tiles in each ocean. Journalists developed and “published” news stories about sustainability topics, for example environmental impacts of maritime industries or overfishing, based on information provided by Scientists and Environmentalists. The Soul of the Seas character preferably selected facilities to be impacted by game events, which belonged to players with a high number of dark tiles. This game character thus plays a regulatory role, incorporating biodiversity and existence values of the ocean that are difficult to quantify or represent on a purely socio-economic or ecosystem service basis (Beaumont et al., 2008; Norgaard, 2010). Some of the ocean use characters demonstrated environmentally friendly behaviour clearly beyond their character role and goal, aiming at setting an example and creating a “positive peer pressure” for sustainable behaviour (Lee et al., 2013). These observations suggest that the players considered impacts of ocean uses and social interactions in their in-game actions, leading to agreements, which reflect social–ecological conflicts and trade-offs in ocean uses. Other experimental work in game environments has found communication among players to be necessary for efficient use of limited common-pool resources (e.g. Janssen et al., 2010; Finkbeiner et al. 2018). Social incentives and values have also been shown to be highly important in promoting environmental engagement and producing behavioural change (Heimlich and Ardoin, 2008; Zaval and Cornwell, 2017). Cooperative games with role-playing elements such as Ocean Limited are thus promising tools for promoting collaborative behaviour and social learning in adaptation to climate change (Wu and Lee, 2015; Rumore et al., 2016; Moreau et al., 2019). A list of existing board and computer games for coastal and marine conservation, management, and adaptation is provided with this article (Supplementary Table S2). Links to real-world governance challenges Interestingly, some of the game strategies found by the players mirror real-world marine governance developments, without being suggested by the game materials or supervisors. For instance, marine reserves were established in large, uninterrupted networks in more offshore ocean areas to reduce spatial conflicts with coastal-ocean users and needed to be adjusted as a response to climate change impacts (cf. Spalding et al., 2013). Mayors in the game often protected Small-scale Fishers from being outcompeted by the more powerful Commercial Fishers, thus considering social justice aspects of marine fisheries (FAO, 2016). When asked about “main challenges and decisions during the game”, players frequently referred to uncertainty about future game events and the impacts of other players’ actions and climate change, which are major issues for marine spatial planning and adaptive governance (Rice et al., 2014; Clarke Murray et al., 2015). The game incorporates some of the important aspects of marine ecosystem-based management: social–ecological links, consideration of scientific knowledge, biodiversity values, and uncertainty about the future (Katsanevakis et al., 2011; Long et al., 2015). If the game world provides an adequate representation of reality, insight from games can be used to assess trade-offs among uses and the state of the environment, facilitate collective learning and system understanding, and could help researchers to develop real-world governance strategies (Bousquet et al., 2002; Janssen et al., 2010; Costanza et al., 2014). Although our game’s representation of marine systems is necessarily simplified to provide an accessible and entertaining game experience for students, the above observations suggest that the game world is sufficiently realistic to teach students the cognitive and social capacities for navigating and solving real-world marine sustainability problems, such as systemic and long-term thinking (cf. Bousquet et al., 2002; Garris et al., 2002). To engage students and the public in ocean and climate topics beyond the game world, it is highly important to make them aware of their personal connections to the ocean (Plankis and Marrero, 2012; Wu and Lee, 2015). Student feedback from all age groups linked game contents to personal experience and behaviour in the real world, for example pollution, globally transported goods, consumption of fish, and energy use. Food and pollution have been found before as two prevalent aspects in linking the ocean to personal decisions among younger students (Marrero and Moore Mensah, 2010). Educating students about their own personal reliance on the ocean, and the societal actors that are vulnerable to impacts on the ocean, can lay the base for “ocean citizenship” and “sustainability as a frame of mind”, instead of creating a dichotomy of environmental conservation vs. economic exploitation (Bonnett, 1999; Fletcher and Potts, 2007). These observations suggest that Ocean Limited and other role-playing games can promote personal engagement in marine sustainability topics, and are suitable to train some of the key capacities for an education for sustainable development, for example foresighted and interdisciplinary thinking, cosmopolitan perception, empathy for other actors, and competency for planning ahead (Barth et al., 2007). Systematic assessment of game outcomes, emerging sustainability-oriented cooperation, and learning success in different player groups could be used for more detailed analyses of social and cognitive aspects of the development of environmental decision making and cooperative behaviour in students, for example combined with a computer-based assessment of players’ in-game decisions and game outcomes. An increased representation of international governance regimes (e.g. fisheries management bodies, international law of the sea, and international climate negotiations) could lead to an advanced game version for higher education (e.g. in marine resource and coastal-management studies). Supplementary data Supplementary material is available at the ICESJMS online version of the manuscript. Acknowledgements Character illustrations and icons were created by Stefanie Beulshausen, Bremen. Initial development of game mechanics was led by Christiane Hütter, Berlin. We thank the Lighthouse Foundation e.V., KlimaSail, Petrine e.V., and Henning Lange for providing opportunities for test games; Lena Meyer (Kiel) for filming and photographs; and Berit Bremer (artec Uni Bremen) and Martin Gora (Wissenschaft im Dialog, Berlin) for administrative support. We thank Sarah Carr for her compilation of serious ocean games, Gemma Carroll and Heather Welch for help with the English game translation, and Timothy Frawley, Laura Good, Elliott Hazen, Michael Flitner, and three anonymous reviewers for comments that helped to improve the final manuscript. Funding The development of Ocean Limited was funded under the “Science Year 2016–2017: Seas and Oceans” by the German Ministry of Education and Research (BMBF). References Abspoel L. , Mayer I., Keijser X., Warmelink H., Fairgrieve R., Ripken M., Abramic A. et al. 2019 . Communicating maritime spatial planning: the MSP challenge approach . Marine Policy . in press OpenURL Placeholder Text WorldCat Abt C. 1970 . Serious Games . Viking Press , New York . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Allison E. H. , Bassett H. R. 2015 . Climate change in the oceans: human impacts and responses . Science , 350 : 778 – 782 . Google Scholar Crossref Search ADS PubMed WorldCat Barth M. , Godemann J., Rieckmann M., Stoltenberg U. 2007 . Developing key competencies for sustainable development in higher education . International Journal of Sustainability in Higher Education , 8 : 416 – 430 . Google Scholar Crossref Search ADS WorldCat Bazan E. 1976 . Environmental simulation games . Journal of Environmental Education , 8 : 41 – 51 . Google Scholar Crossref Search ADS WorldCat Beaumont N. J. , Austen M. C., Atkins J. P., Burdon D., Degraer S., Dentinho T. P., Derous S. et al. 2007 . Identification, definition and quantification of goods and services provided by marine biodiversity: implications for the ecosystem approach . Marine Pollution Bulletin , 54 : 253 – 265 . Google Scholar Crossref Search ADS PubMed WorldCat Beaumont N. J. , Austen M. C., Mangi S. C., Townsend M. 2008 . Economic valuation for the conservation of marine biodiversity . Marine Pollution Bulletin , 56 : 386 – 396 . Google Scholar Crossref Search ADS PubMed WorldCat Bollmann M. , Bosch T., Colijn F., Ebinghaus R., Froese R., Gussow K., Khalilian S. et al. 2010 . World Ocean Review 1. maribus, Hamburg. Bonnett M. 1999 . Education for Sustainable Development: a coherent philosophy for environmental education? Cambridge Journal of Education , 29 : 313 – 324 . Google Scholar Crossref Search ADS WorldCat Bousquet F. , Barreteau O., d’Aquino P. 2002 . Multi-agent systems and role games: collective learning processes for ecosystem management . In Complexity and ecosystem management: The theory and practice of multi-agent systems , pp. 249 – 285 . Ed. by M. A. Janssen. E. Elgar, Cheltenham. OpenURL Placeholder Text WorldCat Cava F. , Schoedinger S., Strang C., Tuddenham P. 2005 . Science Content and Standards for Ocean Literacy: A Report on Ocean Literacy. http://cosee-ne.cosee.net/ (last accessed 13 February 2020). Charles A. 2012 . People, oceans and scale: governance, livelihoods and climate change adaptation in marine social–ecological systems . Current Opinion in Environmental Sustainability , 4 : 351 – 357 . Google Scholar Crossref Search ADS WorldCat Chawla L. , Cushing D. F. 2007 . Education for strategic environmental behavior . Environmental Education Research , 13 : 437 – 452 . Google Scholar Crossref Search ADS WorldCat Clarke Murray C. , Agbayani S., Ban N. C. 2015 . Cumulative effects of planned industrial development and climate change on marine ecosystems . Global Ecology and Conservation , 4 : 110 – 116 . Google Scholar Crossref Search ADS WorldCat Cordova D. I. , Lepper M. R. 1996 . Intrinsic motivation and the process of learning: beneficial effects of contextualization, personalization, and choice . Journal of Educational Psychology , 88 : 715 – 730 . Google Scholar Crossref Search ADS WorldCat Costanza R. , Chichakly K., Dale V., Farber S., Finnigan D., Grigg K., Heckbert S. et al. 2014 . Simulation games that integrate research, entertainment, and learning around ecosystem services . Ecosystem Services , 10 : 195 – 201 . Google Scholar Crossref Search ADS WorldCat Doney S. C. , Ruckelshaus M., Emmett Duffy J., Barry J. P., Chan F., English C. A., Galindo H. M. et al. 2012 . Climate change impacts on marine ecosystems . Annual Review of Marine Science , 4 : 11 – 37 . Google Scholar Crossref Search ADS PubMed WorldCat FAO. 2016 . The State of World Fisheries and Aquaculture . UN Food and Agriculture Organization , Rome . 204 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Finkbeiner E. M. , Micheli F., Saenz-Arroyo A., Vazquez-Vera L., Perafan C. A., Cárdenas J. C. 2018 . Local response to global uncertainty: insights from experimental economics in small-scale fisheries . Global Environmental Change , 48 : 151 – 157 . Google Scholar Crossref Search ADS WorldCat Fletcher S. , Potts J. 2007 . Ocean citizenship: an emergent geographical concept . Coastal Management , 35 : 511 – 524 . Google Scholar Crossref Search ADS WorldCat Foley M. M. , Halpern B. S., Micheli F., Armsby M. H., Caldwell M. R., Crain C. M., Prahler E. et al. 2010 . Guiding ecological principles for marine spatial planning . Marine Policy , 34 : 955 – 966 . Google Scholar Crossref Search ADS WorldCat Foster A. 2008 . Games and motivation to learn science: personal identity, applicability, relevance and meaningfulness . Journal of Interactive Learning Research , 19 : 597 – 614 . OpenURL Placeholder Text WorldCat Garris R. , Ahlers R., Driskell J. E. 2002 . Games, motivation, and learning: a research and practice model . Simulation & Gaming , 33 : 441 – 467 . Google Scholar Crossref Search ADS WorldCat Gattuso J.-P. , Magnan A., Bille R., Cheung W. W. L., Howes E. L., Joos F., Allemand D. et al. 2015 . Contrasting futures for ocean and society from different anthropogenic CO2 emissions scenarios . Science , 349 : aac4722 . Google Scholar Crossref Search ADS PubMed WorldCat Gordon E. , Baldwin-Philippi J. 2014 . Playful civic learning: enabling lateral trust and reflection in game-based public participation . International Journal of Communication , 8 : 28 . OpenURL Placeholder Text WorldCat Heimlich J. E. , Ardoin N. M. 2008 . Understanding behavior to understand behavior change: a literature review . Environmental Education Research , 14 : 215 – 237 . Google Scholar Crossref Search ADS WorldCat IPCC. 2019 . IPCC Special Report on the Ocean and Cryosphere in a Changing Climate [ Pörtner H.-O., Roberts D.C., Masson-Delmotte V., Zhai P., Tignor M., Poloczanska E., Mintenbeck K., Alegría A., Nicolai M., Okem A., Petzold J., Rama B., Weyer N.M. (Ed.)], Geneva, 755p. in press. Janssen M. A. , Holahan R., Lee A., Ostrom E. 2010 . Lab experiments for the study of social-ecological systems . Science , 328 : 613 – 617 . Google Scholar Crossref Search ADS PubMed WorldCat Katsanevakis S. , Stelzenmüller V., South A., Sørensen T. K., Jones P. J. S., Kerr S., Badalamenti F. et al. 2011 . Ecosystem-based marine spatial management: review of concepts, policies, tools, and critical issues . Ocean & Coastal Management , 54 : 807 – 820 . Google Scholar Crossref Search ADS WorldCat Kaufman G. , Flanagan M. 2016 . Playing the System: Comparing the Efficacy and Impact of Digital and Non-Digital Versions of a Collaborative Strategy Game. In Proceedings of 1st International Joint Conference of DiGRA and FDG. Dundee, Scotland. Keijser X. , Ripken M., Mayer I., Warmelink H., Abspoel L., Fairgrieve R., Paris C. 2018 . Stakeholder engagement in maritime spatial planning: the efficacy of a serious game approach . Water , 10 : 724 . Google Scholar Crossref Search ADS WorldCat Klinger D. H. , Eikeset A. M., Davíðsdóttir B., Winter A. M., Watson J. R. 2018 . The mechanics of blue growth: management of oceanic natural resource use with multiple, interacting sectors . Marine Policy , 87 : 356 – 362 . Google Scholar Crossref Search ADS WorldCat Lee J. J. , Ceyhan P., Jordan-Cooley W., Sung W. 2013 . GREENIFY: a real-world action game for climate change education . Simulation & Gaming , 44 : 349 – 365 . Google Scholar Crossref Search ADS WorldCat Long R. D. , Charles A., Stephenson R. L. 2015 . Key principles of marine ecosystem-based management . Marine Policy , 57 : 53 – 60 . Google Scholar Crossref Search ADS WorldCat Markus T. , Hillebrand H., Hornidge A.-K., Krause G., Schlüter A. 2018 . Disciplinary diversity in marine sciences: the urgent case for an integration of research . ICES Journal of Marine Science , 75 : 502 – 509 . Google Scholar Crossref Search ADS WorldCat Marrero M. E. , Moore Mensah F. 2010 . Socioscientific decision making and the ocean: a case study of 7th grade life science students . Electronic Journal of Science Education , 14 : 1 – 27 . OpenURL Placeholder Text WorldCat Mayer I. , Zhou Q., Lo J., Abspoel L., Keijser X., Olsen E., Nixon E. et al. 2013 . Integrated, ecosystem-based marine spatial planning: design and results of a game-based, quasi-experiment . Ocean & Coastal Management , 82 : 7 – 26 . Google Scholar Crossref Search ADS WorldCat Millenium Ecosystem Assessment. 2005 . Ecosystems and Human Well-Being. World Resources Institute . Island Press , Washington . https://www.millenniumassessment.org/documents/document.356.aspx.pdf (last accessed 13 February 2020). Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Moreau C. , Barnaud C., Mathevet R. 2019 . Conciliate agriculture with landscape and biodiversity conservation: a role-playing game to explore trade-offs among ecosystem services through social learning . Sustainability , 11 : 310 – 320 . Google Scholar Crossref Search ADS WorldCat NMEA. 2010 . Ocean Literacy Scope and Sequence for Grades K-12. National Marine Educators Association. https://www.marine-ed.org/ocean-literacy/special-report. NOAA. 2013 . Ocean Literacy: The Essential Principles and Fundamental Concepts of Ocean Sciences for Learners of All Ages. National Oceanic and Atmospheric Administration, Silver Springs, MD. NOEP. 2016 . State of the U.S. Ocean and Coastal Economies 2016 Update. National Ocean Economics Program. Middlebury Institute of International Studies at Monterey, Monterey, CA. Norgaard R. B. 2010 . Ecosystem services: from eye-opening metaphor to complexity blinder . Ecological Economics , 69 : 1219 – 1227 . Google Scholar Crossref Search ADS WorldCat Osterblom H. , Crona B. I., Folke C., Nyström M., Troell M. 2016 . Marine ecosystem science on an intertwined planet . Ecosystems , 20 : 54 – 61 . Google Scholar Crossref Search ADS WorldCat Park D. K. S. , Kildow D. J. T. 2014 . Rebuilding the classification system of the ocean economy . Journal of Ocean and Coastal Economics , 4 : 1 – 39 . OpenURL Placeholder Text WorldCat Perry R. I. , Barange M., Ommer R. E. 2010 . Global changes in marine systems: a social–ecological approach . Progress in Oceanography , 87 : 331 – 337 . Google Scholar Crossref Search ADS WorldCat Perry R. I. , Ommer R. E., Barange M., Jentoft S., Neis B., Sumaila U. R. 2011 . Marine social-ecological responses to environmental change and the impacts of globalization . Fish and Fisheries , 12 : 427 – 450 . Google Scholar Crossref Search ADS WorldCat Plankis B. , Marrero M. E. 2012 . Recent ocean literacy research in United States public schools: results and implications . International Electronic Journal of Environmental Education , 1 : 1 – 31 . OpenURL Placeholder Text WorldCat Portman M. E. 2011 . Marine spatial planning: achieving and evaluating integration . ICES Journal of Marine Science , 68 : 2191 – 2200 . Google Scholar Crossref Search ADS WorldCat Rice J. , Jennings S., Charles A. 2014 . Scientific foundation: towards integration. In Governance of Marine Fisheries and Biodiversity Conservation , pp. 124 – 136 . Ed. by S. M. Garcia, A. Charles and J. Rice. John Wiley & Sons, Ltd ., Chichester . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Rumore D. , Schenk T., Susskind L. 2016 . Role-play simulations for climate change adaptation education and engagement . Nature Climate Change , 6 : 745 – 750 . Google Scholar Crossref Search ADS WorldCat Sauvé L. 1996 . Environmental education and sustainable development: a further appraisal . Canadian Journal of Environmental Education (CJEE) , 1 : 7 – 34 . OpenURL Placeholder Text WorldCat Sitzmann T. 2011 . A meta‐analytic examination of the instructional effectiveness of computer‐based simulation games . Personnel Psychology , 64 : 489 – 528 . Google Scholar Crossref Search ADS WorldCat Spalding M. D. , Meliane I., Milam A., Fitzgerald C., Hale L. Z. 2013 . Protecting marine spaces: global targets and changing approaches . Ocean Yearbook Online , 27 : 213 – 248 . Google Scholar Crossref Search ADS WorldCat Spilhaus A. 1991 . Atlas of the World with Geophysical Boundaries showing Oceans, Continents and Tectonic Plates in Their Entirety . American Philosophical Society , Philadelphia . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Swinerton E. N. 1972 . Environmental gaming simulations . The Journal of Environmental Education , 3 : 49 – 52 . Google Scholar Crossref Search ADS WorldCat UNESCO. 2018 . Issues and Trends in Education for Sustainable Development . United Nations Educational, Scientific and Cultural Organization , Paris . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC United Nations. 2017 . The Sustainable Development Goals Report 2017 . United Nations , Geneva . https://unstats.un.org/sdgs/report/2017/ (last accessed 13 February 2020). Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Vare P. , Scott W. 2007 . Learning for a change . Journal of Education for Sustainable Development , 1 : 191 – 198 . Google Scholar Crossref Search ADS WorldCat Verutes G. M. , Rosenthal A. 2014 . Using simulation games to teach ecosystem service synergies and trade-offs . Environmental Practice , 16 : 194 – 204 . Google Scholar Crossref Search ADS WorldCat Victoria Uribe R. , Utrilla Cobos S. A. 2014 . Board Games as Tool for Teaching Basic Sustainability Concepts to Design Students. The European Conference on Sustainability, Energy & the Environment 2014. Brighton. Wouters P. , Van Nimwegen C., van Oostendorp H., van der Spek E. D. 2013 . A meta-analysis of the cognitive and motivational effects of serious games . Journal of Educational Psychology , 105 : 249 – 265 . Google Scholar Crossref Search ADS WorldCat Wu J. S. , Lee J. J. 2015 . Climate change games as tools for education and engagement . Nature Climate Change , 5 : 413 – 418 . Google Scholar Crossref Search ADS WorldCat Xu Y. , Barba E., Radu I., Gandy M., MacIntyre B. 2011 . Chores are fun: understanding social play in board games for digital tabletop game design. In Proceedings of the 2011 DiGRA International Conference: Think Design Play. Utrecht. Zaval L. , Cornwell J. F. M. 2017 . Effective education and communication strategies to promote environmental engagement . European Journal of Education , 52 : 477 – 486 . Google Scholar Crossref Search ADS WorldCat © International Council for the Exploration of the Sea 2020. All rights reserved. For permissions, please email: [email protected] This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Thingstad, T Frede

doi: 10.1093/icesjms/fsaa028pmid: N/A

Abstract In linear food chains, resource and predator control produce positive and negative correlations, respectively, between biomass at adjacent trophic levels. These simple relationships become more complex in food webs that contain alternative food chains of unequal lengths. We have used a “minimum” model for the microbial part of the pelagic food web that has three such food chains connecting free mineral nutrients to copepods: via diatoms, autotrophic flagellates, and heterotrophic bacteria. Trophic cascades from copepods strongly modulates the balance between the three pathways and, therefore, the functionality of the microbial food web in services such as food production for higher trophic levels, DOM degradation, and ocean carbon sequestration. The result is a theoretical framework able to explain, not only apparent conflicts in Arctic mesocosm experiments, but also biogeochemical features of the Mediterranean. Here, the fundamental difference between Arctic and Mediterranean microbial food webs is the way they are predator driven by seasonal migration of large copepods in the Arctic, but resource driven due to the anti-estuarine circulation in the Mediterranean. In this framework, global change effects on microbial ecosystem functions are more like to come indirectly through changes in these drivers than through direct temperature effects on the microbes. Introduction The abstract to this article can be seen as a state-of-the-art summary of research in marine microbial ecology rooted in a single event >40 years ago: the 1977 blowout from the Bravo platform, releasing something like 15 000 tonnes of crude oil (Gunkel et al., 1985) into the North Sea. One important aspect of oil pollution is that it is an addition of a largely degradable carbon source to the ocean’s photic zone. In the stratified season, this is an environment where mineral nutrients, typically nitrogen, phosphorous, or iron (Moore et al., 2013), are believed to limit phytoplankton growth. Efficient growth of oil-degrading bacteria can then only occur in competition with phytoplankton, leading to a kind of Hutchinsons Paradox (Hutchinson, 1961) in disguise: “How can bacteria and phytoplankton coexist if limited by the same mineral nutrient.” The solution suggested was a strong predator control on the biomass of the best competitor (bacteria), leaving limiting resources for the inferior competitor (phytoplankton) with less predator control on their biomass (Thingstad and Pengerud, 1985). Using 100-ml laboratory chemostats, we could demonstrate experimentally how this worked (Pengerud et al., 1987) and how degradation of even a readily available carbon source like glucose could be severely restricted due to the combined controls of both bacterial biomass (through predation) and bacterial growth rate (trough mineral nutrient competition with phytoplankton). The principle was later generalized (Figure 1) using the “Killing-the-Winner” (KtW) structure (Thingstad and Lignell, 1997). Despite its simplicity, this KtW structure contains “a little bit of everything” (see, e.g. Våge et al., 2018). It combines bottom-up and top-down controls to relate resources to diversity and diversity to life strategies; it relates trade-offs between traits to resource partitioning and allows food chains to split into food webs. Fundamental biological questions like “What makes SAR 11 the world’s most abundant organism?” can therefore be discussed in a KtW framework (Thingstad et al., 2014). Today, more than four decades after the Bravo blowout, I believe that the principles of the KtW structure are fundamental also for understanding some of the basin-scale differences in the ocean ecosystem. The rest of this article is an attempt to explain why and how. Figure 1. Open in new tabDownload slide Idealized “Killing-the-Winner” structure where a “defence strategist” can coexist stably with a “competition strategist” on a single shared limiting resource. This is because biomass of the “competition strategist” (Winner) is limited by predator-control which leaves some of the "Total limiting resources" for the “defence strategist” with inferior competitive abilities. Figure 1. Open in new tabDownload slide Idealized “Killing-the-Winner” structure where a “defence strategist” can coexist stably with a “competition strategist” on a single shared limiting resource. This is because biomass of the “competition strategist” (Winner) is limited by predator-control which leaves some of the "Total limiting resources" for the “defence strategist” with inferior competitive abilities. In terms of orders of magnitude in organism size, the pelagic “virus-to-whales” food chain is split approximately in two at the level of copepods: an upper, macroscopic, “copepods-to-whales” (ca. 10−3–101 m) food web with multicellular organisms and a lower, microbial, “virus-to-copepods” (ca. 10−8–10−3 m) food web containing viruses, prokaryotes, and protists. Over sufficiently long time and space scales, the biomass distribution along the whole food chain may hypothetically approach steady state and the entire food chain will be resource driven. At shorter time and space scales, however, the ability for self-movement in organisms in the macroscopic part creates a potential for variations in abundance that depend on factors other than food availability in their immediate environment. For the microbial part, this means that grazing loss to metazoan predators can vary due to factors outside the microbial system, potentially creating cascading effects that apparently can propagate all the way through the microbial web to affect composition and dynamics in the virus community five orders of magnitude “below” (Sandaa et al., 2017). Regional differences in the abundance and behaviour of metazoan predators may therefore cause differences in structure and function of the microbial food web. This structure and function will, however, also depend on the amount of limiting nutrients available, typically nitrogen, phosphorus, iron, organic material (for heterotrophic prokaryotes), and silicate (for diatoms). How such top-down and bottom-up controls interact is not intuitively obvious. The Arctic pelagic ecosystem is an interesting case in this context. Arctic copepods have adapted to cold water and a short productive season by seasonal vertical migration and diapause in deep waters (Falk-Petersen et al., 2009). As this behaviour generates seasonal variation in the grazing pressure on microbes in the photic zone layer, one of the main conditions for trophic cascades is present. In the Mediterranean, net evaporation sets up a negative thermo-haline circulation that creates an oligotrophication gradient along the African coast (Millot and Taupier-Letage, 2005). The Arctic and Mediterranean oceans therefore appear to have fundamentally different drivers for the surface layer microbial food web, making them interesting case studies for studying the properties of top-down- and bottom-up-driven microbial food webs. To illustrate the basic concepts behind top-down and bottom-up drivers, we can use the extreme simplification of a nutrients–autotrophic flagellates–ciliates (NFC) food chain (i.e. analogous to classical nutrients–phytoplankton–zooplankton models) in Figure 2A. Using simple Lotka–Volterra equations (see Supplementary Material for mathematical assumptions), we can solve for the steady state (N*, F*, C*) as function of two external drivers: total nutrient content NT = N + F + C (Figure 2A) and loss rate δC of the ciliate community C to their copepod predators (Figure 2B). Variations in NT are subsequently discussed as “resource” or “bottom-up” driving. Similarly, variations in the loss rate δZ is discussed as “predator” or “top-down” driving. Figure 2B and C illustrate how the resource and predator driver create different steady-state correlations between microbial predators (C*) and their prey (F*) in this simple linear food chain. The general bottom-up effect is that more resources give more producers which again give more predators. Variations in NT therefore tend to produce positive prey–predator correlations in bottom-up driven systems. In top-down-driven systems, an increase in the stock of a top predator will reduce the abundance of its prey, which again will release grazing pressure for the next, lower level in the food chain (Frank et al., 2007). This produces negative correlations between predators and their–prey, and therefore lead to alternating negative and positive effects down a linear food chain, usually referred to as a “trophic cascade” (Carpenter et al., 1985). Figure 2. Open in new tabDownload slide (A) Linear NFC food chain used to illustrate the steady-state effect of (B) resource control (variations in total nutrient content NT with ciliate predation loss rate δC kept constant) and (C) predator control (variations in δC with NT kept constant) (see Supplementary Material for details). Figure 2. Open in new tabDownload slide (A) Linear NFC food chain used to illustrate the steady-state effect of (B) resource control (variations in total nutrient content NT with ciliate predation loss rate δC kept constant) and (C) predator control (variations in δC with NT kept constant) (see Supplementary Material for details). In limnology, trophic cascades have not only been of theoretical interest but have also served as a central conceptual tool in the restoration of eutrophied shallow lakes. The shallow lake case may also serve as an important reminder of the need to understand the ecological context within which such controls work. Since bottom vegetation provides refuges where the dominating meso-zooplankton (cladocerans) can hide from their predators, disappearance of this vegetation due to light limitation in the eutrophied state prevents easy restoration of the original food chain through nutrient load reduction (Scheffer et al., 1993). Based to a large extent on the high occurrence of defence structures in pelagic organisms, Verity and Smetacek (1996) argued many years ago that top-down forces where likely to be more important in marine food webs than usually recognized and that the dominating bottom-up perspective of marine ecologists had led to a biased view on how marine ecosystems work. In a more recent review, also Hessen and Kaartvedt (2014) concluded that there is an urgent need for more focus on the existence of trophic cascades in the marine environment. In a meta-analysis based on correlations in known predator–prey pairs from the macroscopic part of the food chain, Frank et al. (2007) classified North Atlantic shelf systems as top-down or bottom-up controlled. Intriguingly, systems with top-down control turned out to be located in cold-water regions, while bottom-up control seemed to be a characteristic of more temperate waters. I here argue for a somewhat similar difference in the external drivers for the photic zone microbial food web, i.e. with copepod predators being the central driver in cold Arctic waters, as opposed to a dominating resource-driven microbial food web in the warm Mediterranean Sea. The arguments are based on published observations for the west-to-east oligotrophication gradient in the Mediterranean Sea (Santinelli et al., 2012) and our use of trophic cascades to explain seemingly conflicting results in Arctic mesocosms (Larsen et al., 2015), The marine microbial food web By adding a two-step “classic” nutrients–diatoms–copepods food chain to the three-step NFC–copepods food chain in Figure 2A, we get what Wollrab et al. (2012) have termed a “pentagon” food web structure (Figure 3A). Among the interesting aspects of this pentagon are its predictions for copepod–chlorophyll correlations. Since there is a direct link between copepods and diatoms, but an intermediate ciliate link between copepods and flagellates, this pentagon predicts cascades that produce negative and positive copepod–chla correlations, respectively, depending on whether the system is diatom or flagellate dominated. Experimental support of this theoretical prediction has been found using mesocosm experiments manipulated at the copepod level (Vadstein et al., 2004). Important for our subsequent discussion, the simple pentagon structure of Figure 3A thus seems to have sufficient elements to capture essential aspects of how the flagellate—diatom balance is controlled. Figure 3. Open in new tabDownload slide (A) “Pentagon structure” with two pathways from mineral nutrients to copepods. Because of the difference in length, the cascading effect of copepods on autotrophic flagellates and diatoms is opposite. (B) “Minimum model” for the microbial food web with three alternative pathways connecting mineral nutrients to copepods. These also form two coupled pentagons with ciliates and copepods occupying the upper right corner of the left and right pentagons, respectively. Figure 3. Open in new tabDownload slide (A) “Pentagon structure” with two pathways from mineral nutrients to copepods. Because of the difference in length, the cascading effect of copepods on autotrophic flagellates and diatoms is opposite. (B) “Minimum model” for the microbial food web with three alternative pathways connecting mineral nutrients to copepods. These also form two coupled pentagons with ciliates and copepods occupying the upper right corner of the left and right pentagons, respectively. Adding also a “microbial loop” where dissolved organic material is fed into the food web through heterotrophic bacteria and their heterotrophic flagellate predators (Figure 3B), we get the “minimum” model for the microbial food web suggested originally for the Mediterranean by Thingstad and Rassoulzadegan (1999); later given a mathematical formulation and used for successful simulation of transient dynamics in mesocosm perturbation experiments (Thingstad et al., 2007). The long copepods–ciliates–heterotrophic flagellates–bacteria trophic cascade introduced by this addition has also been verified experimentally (Zöllner et al., 2009). With this, the minimum model contains three alternative food chains of different lengths connecting mineral nutrients to copepods: through diatoms (two steps), autotrophic flagellates (three steps), and heterotrophic bacteria (four steps). This three-food-chain structure can also be described as two coupled pentagons with ciliates and copepods occupying the upper right corner of a left and a right pentagon (Larsen et al., 2015). The important difference between the two pentagons is the rapid numerical response of ciliates, allowing the left pentagon to reach internal steady state over much shorter time scales than the right pentagon where variations in copepod stock may be decoupled from variations in the microbial part. Using simplifying assumptions similar to those used for the linear NFC model, the steady states of this minimum model can be solved analytically. As before, the steady states of the minimum model depend on its two external drivers, such as total limiting nutrient NT (resources) and copepod stock Z (predators), but also modified by the presence/absence of silicate and whether the supply of labile dissolved organic carbon (DOC) is smaller or larger than the bacterial carbon demand (Thingstad et al., 2007). Microbial organism size and eutrophication are correlated with small- and large-celled phytoplankton species dominating in oligotrophic and eutrophic marine systems, respectively (Irigoien et al., 2004). The minimum model reflects this, as there is a transition from left to right from dominantly predator control of the small, competitively efficient bacteria on the left side to dominantly resource control of the large, chain-forming diatoms on the right side. Reductions in NT therefore tend to reduce biomass on the right “classical” side of the model (Figure 3B), increasing the relative dominance of small-celled “competition strategists” on the left side. These mechanisms also provide a simple solution to Ryther’s seemingly counter-intuitive observation that nutrient-rich and oligotrophic systems tend to have short and long food chains, respectively (Ryther, 1969). Using a qualitative and intuitive approach to the cascading effects, the negative correlation in predator–prey pairs along each linear food chain produces negative correlation between copepods and diatoms, as well as between copepods and bacteria (odd-numbered steps along linear food chains) but positive correlation between copepods and flagellates (even numbered food chains to both auto- and heterotrophic flagellates). This generates two reciprocal states of the food web: a flagellate-dominated food web for high copepod levels (High-Z) and one that is either diatom-dominated or bacteria-dominated for low copepod levels (Low-Z). Whether the Low-Z state of the minimum model becomes dominated by bacteria or by diatoms depends on the availability of easily degradable organic carbon and silicate. Note that Figure 4 illustrates states where the cascades have established. Transients such as where a large diatom spring bloom is grazed down by a large copepod stock are not represented here. Analysis of such transient states requires the dynamic mathematical version of the model (Thingstad et al., 2007). The classification scheme in Figure 4 has allowed a unifying interpretation of population dynamics in mesocosm experiments that otherwise appeared to give conflicting results (Table 1). Figure 4. Open in new tabDownload slide Trophic cascades from copepods (Z) determining the balance among the bacteria, autotrophic flagellates and diatoms. In the High-Z situation to the left, the food web becomes flagellate dominated and differences in the availability of DOC and Si have little food web effects. The Low-Z situation to the right is more complicated since the diatom vs. bacteria outcome is influenced by the availability of silicate and labile DOC, favouring diatoms and bacteria, respectively. An additional complication has been identified in the size structure of the diatom community where ciliate grazing on sufficiently small diatoms (dotted arrow) was found to shift the dominance towards bacteria (see Table 1 for mesocosm experiments corresponding to the three different outcomes). Figure 4. Open in new tabDownload slide Trophic cascades from copepods (Z) determining the balance among the bacteria, autotrophic flagellates and diatoms. In the High-Z situation to the left, the food web becomes flagellate dominated and differences in the availability of DOC and Si have little food web effects. The Low-Z situation to the right is more complicated since the diatom vs. bacteria outcome is influenced by the availability of silicate and labile DOC, favouring diatoms and bacteria, respectively. An additional complication has been identified in the size structure of the diatom community where ciliate grazing on sufficiently small diatoms (dotted arrow) was found to shift the dominance towards bacteria (see Table 1 for mesocosm experiments corresponding to the three different outcomes). Table 1. Summary of mesocosm experiments interpreted using the minimum model in Figure 3B. Experiment . Location . Dominating pathway . Bact. lim.a . Comments . High copepod initial situation (High-Z)  PAME II (Larsen et al., 2015) Kongsfjorden, Early Arctic summer Autotrophic flagellates M No effect of glucose because of M-limited bacteria  MicroPolar (Tsagaraki et al., 2018) Kongsfjorden, Early Arctic summer Flagellate/bacteria M Copepod removal/addition Excess of organic carbon allowed for predation-resistant bacteria Low copepod initial situation (Low-Z)  PAME I (Thingstad et al., 2008; Larsen et al., 2015) Kongsfjorden, Late Arctic summer Bacteria/small diatoms K Small diatoms outcompeted when glucose added MEDEA (Thingstad et al., 2007) Isefjorden, Denmark Bacteria/large diatoms (Si limited) M Bacterial limitation shifted from K to M when large Si-limited diatoms were stimulated by Si addition MINOS (Pree et al., 2017) Raunefjorden, Norway Diatoms (large) M Diatom–copepod dynamics not well described by minimum model Experiment . Location . Dominating pathway . Bact. lim.a . Comments . High copepod initial situation (High-Z)  PAME II (Larsen et al., 2015) Kongsfjorden, Early Arctic summer Autotrophic flagellates M No effect of glucose because of M-limited bacteria  MicroPolar (Tsagaraki et al., 2018) Kongsfjorden, Early Arctic summer Flagellate/bacteria M Copepod removal/addition Excess of organic carbon allowed for predation-resistant bacteria Low copepod initial situation (Low-Z)  PAME I (Thingstad et al., 2008; Larsen et al., 2015) Kongsfjorden, Late Arctic summer Bacteria/small diatoms K Small diatoms outcompeted when glucose added MEDEA (Thingstad et al., 2007) Isefjorden, Denmark Bacteria/large diatoms (Si limited) M Bacterial limitation shifted from K to M when large Si-limited diatoms were stimulated by Si addition MINOS (Pree et al., 2017) Raunefjorden, Norway Diatoms (large) M Diatom–copepod dynamics not well described by minimum model a M and K: bacterial growth limited by mineral nutrients and labile organic carbon, respectively. Open in new tab Table 1. Summary of mesocosm experiments interpreted using the minimum model in Figure 3B. Experiment . Location . Dominating pathway . Bact. lim.a . Comments . High copepod initial situation (High-Z)  PAME II (Larsen et al., 2015) Kongsfjorden, Early Arctic summer Autotrophic flagellates M No effect of glucose because of M-limited bacteria  MicroPolar (Tsagaraki et al., 2018) Kongsfjorden, Early Arctic summer Flagellate/bacteria M Copepod removal/addition Excess of organic carbon allowed for predation-resistant bacteria Low copepod initial situation (Low-Z)  PAME I (Thingstad et al., 2008; Larsen et al., 2015) Kongsfjorden, Late Arctic summer Bacteria/small diatoms K Small diatoms outcompeted when glucose added MEDEA (Thingstad et al., 2007) Isefjorden, Denmark Bacteria/large diatoms (Si limited) M Bacterial limitation shifted from K to M when large Si-limited diatoms were stimulated by Si addition MINOS (Pree et al., 2017) Raunefjorden, Norway Diatoms (large) M Diatom–copepod dynamics not well described by minimum model Experiment . Location . Dominating pathway . Bact. lim.a . Comments . High copepod initial situation (High-Z)  PAME II (Larsen et al., 2015) Kongsfjorden, Early Arctic summer Autotrophic flagellates M No effect of glucose because of M-limited bacteria  MicroPolar (Tsagaraki et al., 2018) Kongsfjorden, Early Arctic summer Flagellate/bacteria M Copepod removal/addition Excess of organic carbon allowed for predation-resistant bacteria Low copepod initial situation (Low-Z)  PAME I (Thingstad et al., 2008; Larsen et al., 2015) Kongsfjorden, Late Arctic summer Bacteria/small diatoms K Small diatoms outcompeted when glucose added MEDEA (Thingstad et al., 2007) Isefjorden, Denmark Bacteria/large diatoms (Si limited) M Bacterial limitation shifted from K to M when large Si-limited diatoms were stimulated by Si addition MINOS (Pree et al., 2017) Raunefjorden, Norway Diatoms (large) M Diatom–copepod dynamics not well described by minimum model a M and K: bacterial growth limited by mineral nutrients and labile organic carbon, respectively. Open in new tab For some of these experiments, additional mechanisms had to be added to the minimum model to explain special effects. An illustrative example is the effect of small-celled diatoms. Adding the ability of ciliates to graze on small diatoms (the dotted line in the lower right food web of Figure 4), the model outcome shift: Instead of the Low-Z outcome with diatom dominance and mineral nutrient-limited bacteria for large, chain-forming, Si-replete diatoms (as observed in the MEDEA experiment), it shifts to bacterial dominance and carbon limitation for small, ciliate-grazed diatoms (as observed in the PAME I experiment). Another model modification affecting the trophic cascades is the formation of grazing resistant bacteria in situations replete in labile organic carbon (MicroPolar experiment, Table 1). This terminated the cascades at the heterotrophic flagellates–bacteria connection (Tsagaraki et al., 2018). There are also experiments where the minimum model does not seem to explain copepod–diatom predator–prey dynamics well (MINOS experiment; Pree et al., 2017; Table 1) possibly due to complex meso-zooplankton communities and/or diatom toxicity (Hardardottir et al., 2019). Regional differences in the external drivers select ecosystem state Arctic Ocean In the terminology used here, top-down forcing of the microbial food web from copepods occurs when variations in copepod abundance are driven by factors other than their immediate microbial food supply. Vertical positioning in the water column is a well-studied life-strategy adaptation in copepods, believed to optimize the difference between food supply and predatory loss (Fiksen and Carlotti, 1998). As both their food supply (phytoplankton) and the efficiency of their visual predators (fish larvae) are affected by light, diel and seasonal light variations are important ultimate drivers, but in shelf seas also modulated by the depth restrictions of a variable bottom topology (Aarflot et al., 2019). With characteristic time scales for microbial population changes in the order of days, the microbial food web is likely to function as a long-pass filter, not effectively transmitting the signal from diel vertical migrations in meso-zooplankton to bacteria. Seasonal signals, however, such as the stop in copepod grazing pressure from mid-summer (Levinsen et al., 2000) until spring, should give the microbial system ample time to respond. In near-natural Arctic systems, experimental evidence for this seasonal effect comes primarily from the PAME I and PAME II experiments (Table 1). In these, the initial meso-zooplankton (dominated by Calanus finmarchicus) was 3× higher in the PAME II compared with PAME I, presumably as a consequence of their timing in late and early Arctic summer, respectively. In these experiments, the top-down effects have been documented not only to the level of the size of the prokaryote community but also to the community composition of both prokaryotes and viruses (Sandaa et al., 2017). Winter diapause in deep waters is an adaptation of the large Arctic copepods to a short productive season in cold waters, allowing stage V to mature so that eggs from stage VI can be hatched in, or in front of, the food supply becoming available during the spring phytoplankton bloom (Falk-Petersen et al., 2009). Already in mid-June, feeding seems to be terminated prior to overwintering (Levinsen et al., 2000). Winter diapause has also been found in some, although not all, copepod species from the Southern Ocean investigated by Atkinson (1998). The hypothesis is therefore that top-down control of the microbial food webs is typical of high-latitude, cold-water systems; rooted, not in a microbial adaptation to such environments, but in the life-cycle adaptation of their metazoan predators. Mediterranean Sea A marine system particularly well suited for studying resource-driven microbial food webs is the Mediterranean west-to-east oligotrophication gradient. Net evaporation in the Mediterranean Sea sets up a negative thermo-haline (anti-estuarine) circulation (Millot and Taupier-Letage, 2005). Therefore, limiting elements released from particles sinking into the sub-surface counter-current (the Levantine Intermediate Water) are exported through the Gibraltar Strait. This loss of limiting nutrients (= reduction in our NT driver) generates a west-to-east oligotrophication gradient along the African coast: from mesotrophic “Atlantic” conditions in the western Alboran Sea to ultra-oligotrophic conditions in the Levantine Basin in the eastern Mediterranean (Berman et al., 1985). As expected, the phytoplankton community shifts from a considerable diatom component in the western Alboran Sea (Arin et al., 2002) to a phytoplankton community dominated by small unicellular cyanobacteria in the Levantine Basin of the Eastern Mediterranean (Raveh et al., 2015). Somewhat counter-intuitively, the oligotrophication is also accompanied by an increase in DOC eastwards along this gradient. The value of ca. 40 µM-C in the west is comparable to the ocean’s background level of recalcitrant DOC. This increases to 50–55 µM-C in the east (Santinelli et al., 2012). Apparently, consumption of DOC thus decreases faster than production as the system gets more oligotrophic. Importantly, the ca. 15 µM-C of accumulated DOC appears to be labile or semi-labile as it disappears during the return transport westwards in the aphotic Levantine intermediate water (Santinelli et al., 2012). To get a better understanding of mechanisms that may generate this, one can use the left pentagon of the minimum model (Figure 3B). There is a strong correlation between the oligotrophication and ciliate numbers as illustrated by the near-linear relationship between upper layer particulate-P and ciliate numbers along the gradient (Figure 5A and B). Using the same arguments of trophic cascades as before, the pentagon structure will give positive correlations, both between ciliate biomass (C) and the free limiting nutrient (N) and between ciliate biomass (C) and bacterial biomass (B). For mineral nutrient-limited bacteria, both biomass and growth rate will therefore be proportional (to a first linear approximation) to C and bacterial production (growth rate × biomass) therefore scales as the second power of C. Assuming a fixed bacterial yield (bacterial biomass formed per unit DOC consumed), also bacterial carbon demand of mineral nutrient-limited bacteria (BCFM) will then scale as the second power of C (BCDM ∝ C2). If autochthonous production of DOC (Ψ) and ciliates scale are proportional to NT, the relationship between Ψ and ciliates will be linear (Ψ ∝ C). The curves for BCDM and Ψ will then cross in one point (Figure 5C). This divides the system in an oligotrophic and a mesotrophic part. In the oligotrophic part, Ψ > BCDM (production > consumption), bacteria are mineral nutrient limited and DOC will accumulate. In the mesotrophic part, bacteria are carbon-limited, BCDK = Ψ, and only recalcitrant forms of DOC will accumulate. Figure 5. Open in new tabDownload slide (A) Stations of the Prosope cruise in the Mediterranean discussed in the text. Stations west of, in, and east of the Sardinian channel marked with filled, grey, and white circles, respectively. (B) Illustration of the oligotrophication as the west-to-east decline in particulate-P (x-axis) and the linearly correlated decrease in ciliate abundance (regression line: y = 73.99x − 0.43, R2 = 0.922). (C) Suggested relationship between ciliate abundance and bacterial carbon demand (log–log plot) based on the left pentagon of the minimum model [redrawn from Våge et al. (2018)]. In this model, bacterial carbon demand under mineral nutrient limitation scales as ciliates to the second power [fitted line (dotted): BCDM = 1.7 C2, R2 = 0.916], while autochthonous DOC production and therefore BCD under carbon limitation (solid line) is assumed to scale to the first power of C (fitted line BCDK = 0.32C + 0.42, R2 = 0.955). The feasible BCD is the minimum of these two. The two curves appear to cross somewhere around the Sardinian channel (grey circle), suggesting carbon-limited bacteria in the Alboran Sea to the west and mineral nutrient-limited bacteria to the east. Data from Santinelli et al. (2012) and Prosope cruise (http://www.obs-vlfr.fr/cd_rom_dmtt/pr_main.htm). Note the reversed x scales for comparison with the geographical west–east oligotrophication. Figure 5. Open in new tabDownload slide (A) Stations of the Prosope cruise in the Mediterranean discussed in the text. Stations west of, in, and east of the Sardinian channel marked with filled, grey, and white circles, respectively. (B) Illustration of the oligotrophication as the west-to-east decline in particulate-P (x-axis) and the linearly correlated decrease in ciliate abundance (regression line: y = 73.99x − 0.43, R2 = 0.922). (C) Suggested relationship between ciliate abundance and bacterial carbon demand (log–log plot) based on the left pentagon of the minimum model [redrawn from Våge et al. (2018)]. In this model, bacterial carbon demand under mineral nutrient limitation scales as ciliates to the second power [fitted line (dotted): BCDM = 1.7 C2, R2 = 0.916], while autochthonous DOC production and therefore BCD under carbon limitation (solid line) is assumed to scale to the first power of C (fitted line BCDK = 0.32C + 0.42, R2 = 0.955). The feasible BCD is the minimum of these two. The two curves appear to cross somewhere around the Sardinian channel (grey circle), suggesting carbon-limited bacteria in the Alboran Sea to the west and mineral nutrient-limited bacteria to the east. Data from Santinelli et al. (2012) and Prosope cruise (http://www.obs-vlfr.fr/cd_rom_dmtt/pr_main.htm). Note the reversed x scales for comparison with the geographical west–east oligotrophication. This model not only seems to give a reasonably good fit to the data for ciliates and BCD reported by Santinelli et al. (2012) but also locates the crossing point from carbon to mineral nutrient-limited bacterial growth to somewhere in the Sardinian channel. In this dataset, the transition between carbon-limited and mineral nutrient limited bacteria occurs at a concentration of particulate-P of ∼16 nM-P, and a ciliate abundance slightly below 1 ciliate ml−1 (Figure 5B). Importantly, this interpretation appears reasonably consistent with bioassays for bacterial growth limitation where stations with carbon limitation were found in the Alboran Sea and Sicily Strait, other stations having phosphorous-limited bacteria or giving inconclusive results (Van Wambeke et al., 2002). In these relationships, phytoplankton–bacteria competition for the limiting mineral nutrient is essential for the accumulation of degradable DOC. At higher latitudes where deteriorating light conditions are likely to release the nutrient competition long before deep-water formation, one would expect the labile DOC pool to be consumed before it is transported to the ocean's interior. DOC accumulation due to mineral nutrient limitation of the heterotrophic bacteria and due to chemical recalcitrance of course not mutually exclusive mechanisms. In regions with differences in plankton species composition, differences in circulation pattern, or in other physical conditions, the balance between recalcitrance and mineral nutrient limitation may differ from what seems to be the case in the Mediterranean. Relevance and perspectives With almost all of oceanic primary production occurring in the microbial end of the pelagic food chain, the mechanisms controlling diatom-flagellate balance are relevant to the food supply for the entire food chain. With catches in the world’s large fisheries declining since the late 1980s (Pauly et al., 2003), today’s marine fisheries cannot meet the needs of a human population expected to pass 10 billion by year 2057 (United Nations, 2019). As standard ecological theories assume ca. 10% transfer efficiency between adjacent trophic levels, a shift in harvest to lower trophic levels in the macroscopic part of the food chain gives a theoretical potential for substantial increase in sustainable catches. The ecological effects may, however, be complex (Pauly et al., 1998). The alternatives of increasing harvest at the adjacent trophic levels of planktivorous fish (Irigoien et al., 2014) or copepods (Grimaldo et al., 2011) would be expected to have opposite effects on the copepod stock. In the framework discussed here, this would tend to drive the microbial food web in the directions of flagellate-dominated High-Z states, or diatom (alternatively bacteria)-dominated low-Z states (Figure 4). Such fisheries-induced changes in top-down forcing may therefore affect not only the quality and possibly the amount of primary production but also the length and therefore transfer efficiency through the food chain supporting the harvested level. The three food chains of the minimum model also have different biogeochemical functionalities: carbon export by sinking particles such as Si-ballasted diatoms and faecal pellets is primarily associated with the right, “classical” food chain, while accumulation of degradable forms of DOC depends on mineral nutrient limitation of bacteria-restricting activity in the microbial loop on left side. The suggestion of a strong predator control of the balance between the three pathways is therefore also a suggestion of a strong predator modulation of biogeochemical functions in the photic zone ecosystem. While the minimum model contains some biological detail in its description of microbial cycling of the limiting mineral nutrient, the coupling to the production of organic carbon is intentionally kept simple. A deeper analysis of resource-driven systems would require a better mechanistic description for the relationship between NT and autochthonous production rate of labile DOC (Ψ). There are at least two important issues involved. The attractively simple assumption of a fixed stoichiometric coupling between primary production and phytoplankton uptake of the limiting nutrient was found to strongly underestimate carbon fixation as measured in mesocosms dominated by nutrient-limited diatoms. In these experiments, a model with diatom primary production proportional to diatom biomass gave a much better fit (Thingstad et al., 2007). The consequence is a decoupling of carbon fixation from Redfield stoichiometry in diatom-dominated environments (Thingstad et al., 2008). Another important issue is the transfer of this organic carbon through the microbial food web, including its release to forms available to bacteria (the labile DOC pool in the minimum model) through processes such as viral lysis, phytoplankton excretion, and sloppy feeding. Some of these mechanisms would be expected to depend primarily on biomass of a single group (e.g. phytoplankton excretion), others primarily on organisms meeting each other (e.g. sloppy feeding). Rates that involve collision frequencies are proportional to the product of two biomasses (e.g. predator and prey). If, in a resource-driven system, both of the two biomasses increase with nutrient content (NT), such rates will thus scale as the square of NT. Our Mediterranean example (Figure 5) demonstrates how a combination of linear and squared relationships may be crucial in creating shifts in resource-driven systems. Considering the rather simplistic descriptions of a complex biology used in the minimum model, its ability to quantitatively explain the connection between top-down and bottom-up forcing in mesocosm and field data admittedly came to some extent as a positive surprise. The cascading effects in the minimum model depend on its three well-defined linear food chains. Adding complexity in the form of more trophic crosslinking such as ciliates feeding directly on bacteria would tend to weaken the cascades. Intriguingly, the model’s explanatory power therefore seems to some extent to be because of, rather than despite, its simplicity. For a deeper analysis of the coupling between the microbial and macroscopic parts of the food chain, a more detailed description of the meso-zooplankton community seems, however, to be required. Biogeographical distribution of copepod traits such as ambush feeding may be important (Prowe et al., 2019). There are also important additional phylogenetic groups of mesozooplankton (e.g. rotatoria, appendicularia, and cladocera) with feeding behaviour and biogeographical distributions differing from that of copepods. A main insight from the mesocosm work is how the trophic cascades strongly modulates the system responses to bottom-up perturbations (Larsen et al., 2015). Regional characteristics of lower food web functioning are therefore likely driven by regional-specific combinations of these two drivers. The two systems discussed here have the advantages of a well-understood physics behind the Mediterranean oligotrophication gradient and a well-documented copepod prevalence of diapause towards the poles (Record et al., 2018), making the two systems ideal as “microbial laboratories” for comparing differences and interactions between the two types of drivers. With the ocean accumulating most of the heat from global warming (Lyman and Johnson, 2014), temperature sensitivity of structure and function in the microbial food web is important. In the microbial ecology literature, much of the discussion has centred on possible differences in the temperature response of different functional groups, including the possibilities that heterotrophic bacteria (Pomeroy and Deibel, 1986) or micro-zooplankton (Rose and Caron, 2007) are more affected by temperature than phytoplankton. Such differences between functional groups would make the balance between the three pathways (and therefore the microbial food web’s functionality) sensitive to temperature. Using the minimum model to analyse mesocosm dynamics at different temperatures, the need for temperature correction of the parameters has been surprisingly low (Larsen et al., 2015). This may be because temperature adaptations at the physiological and/or phylogenetic level buffer the effect at food web level. It may, however, also be rooted in the physical nature of constraints experienced by food-limited organisms. The enzymatic processes constraining organism growth at or near maximum growth rates would be expected to have “biological” Q10 values ∼2.5–3. Under food limitation, however, physical processes such as diffusion and filtration dominate. Temperature dependence then comes from water viscosity, which has a Q10 of ∼1.3 (Jumars et al., 1993). Steady-state food webs with food-limited microbes may therefore be less temperature sensitive than predicted by laboratory experiments based on food-replete growth (Thingstad and Aksnes, 2018). The suggestion here is therefore that climate-driven changes in water column stability (Yamaguchi and Suga, 2019; Lewandowska et al., 2014) and/or in life-cycle adaptations in the metazoan top predators (Edwards and Richardson, 2004) may be more important for microbial ecosystem structure and function than the direct effects of increasing temperature on microbial activity. Supplementary data Supplementary material is available at the ICESJMS online version of the manuscript. Acknowledgements There is an extensive set of experimental mesocosm work behind the theoretical framework synthesized here. All co-authors on the original articles reporting these experiments have a role not only in the data collection but also in the intellectual process of developing this framework. The Mediterranean data for Figure 5 are based on the Prosope cruise (https://doi.org/10.17600/99040060) and collected by J. Dolan (ciliates), F. van Wambeke (bacterial production) and P. Raimbault (particulate-P). Funding This work was funded by the Research Council of Norway through project The Nansen Legacy (RCN # 276730) and the Trond Mohn Foundation, project SIMPLEX (TMS2019REK02). References Aarflot J. M. , Aksnes D. L., Opdal A. F., Skjoldal H. R., Fiksen Ø. 2019 . Caught in broad daylight: topographic constraints of zooplankton depth distributions . Limnology and Oceanography , 64 : 849 – 859 . Google Scholar Crossref Search ADS WorldCat Arin L. , Moran X. A. G., Estrada M. 2002 . Phytoplankton size distribution and growth rates in the Alboran Sea (SW Mediterranean): short term variability related to mesoscale hydrodynamics . Journal of Plankton Research , 24 : 1019 – 1033 . Google Scholar Crossref Search ADS WorldCat Atkinson A. 1998 . Life cycle strategies of epipelagic copepods in the Southern Ocean . Journal of Marine Systems , 15 : 289 – 311 . Google Scholar Crossref Search ADS WorldCat Berman T. , Walline P. D., Schneller A., Rothenberg J., Townsend D. W. 1985 . Secchi disk depth record—a claim for the Eastern Mediterranean . Limnology and Oceanography , 30 : 447 – 448 . Google Scholar Crossref Search ADS WorldCat Carpenter S. R. , Kitchell J. F., Hodgson J. R. 1985 . Cascading trophic interactions and lake productivity . Bioscience , 35 : 634 – 639 . Google Scholar Crossref Search ADS WorldCat Edwards M. , Richardson A. J. 2004 . Impact of climate change on marine pelagic phenology and trophic mismatch . Nature , 430 : 881 – 884 . Google Scholar Crossref Search ADS PubMed WorldCat Falk-Petersen S. , Mayzaud P., Kattner G., Sargent J. 2009 . Lipids and life strategy of Arctic Calanus . Marine Biology Research , 5 : 18 – 39 . Google Scholar Crossref Search ADS WorldCat Fiksen O. , Carlotti F. 1998 . A model of optimal life history and diel vertical migration in Calanus finmarchicus . Sarsia , 83 : 129 – 147 . Google Scholar Crossref Search ADS WorldCat Frank K. T. , Petrie B., Shackell N. L. 2007 . The ups and downs of trophic control in continental shelf ecosystems . Trends in Ecology & Evolution , 22 : 236 – 242 . Google Scholar Crossref Search ADS PubMed WorldCat Grimaldo E. , Leifer I., Gjosund S. H., Larsen R. B., Jeuthe H., Basedow S. 2011 . Field demonstration of a novel towed, area bubble-plume zooplankton (Calanus sp.) harvester . Fisheries Research , 107 : 147 – 158 . Google Scholar Crossref Search ADS WorldCat Gunkel W. , Pedersen S., Dundas I., Eimhjellen K. 1985 . Microbiological investigations after the Bravo blowout (Ekofisk oil-field, North-Sea) . Helgolander Meeresuntersuchungen , 39 : 21 – 32 . Google Scholar Crossref Search ADS WorldCat Hardardottir S. , Hjort D. M., Wohlrab S., Krock B., John U., Nielsen T. G., Lundholm N. 2019 . Trophic interactions, toxicokinetics, and detoxification processes in a domoic acid-producing diatom and two copepod species . Limnology and Oceanography , 64 : 833 – 848 . Google Scholar Crossref Search ADS WorldCat Hessen D. O. , Kaartvedt S. 2014 . Top-down cascades in lakes and oceans: different perspectives but same story? Journal of Plankton Research , 36 : 914 – 924 . Google Scholar Crossref Search ADS WorldCat Hutchinson G. E. 1961 . The paradox of the plankton . The American Naturalist , 95 : 137 – 145 . Google Scholar Crossref Search ADS WorldCat Irigoien X. , Huisman J., Harris R. P. 2004 . Global biodiversity patterns of marine phytoplankton and zooplankton . Nature , 429 : 863 – 867 . Google Scholar Crossref Search ADS PubMed WorldCat Irigoien X. , Klevjer T. A., Rostad A., Martinez U., Boyra G., Acuna J. L., Bode A. et al. 2014 . Large mesopelagic fishes biomass and trophic efficiency in the open ocean . Nature Communications , 5 : Google Scholar OpenURL Placeholder Text WorldCat Jumars P. , Deming J., Hill P., Karp-Boss L., Dade W. 1993 . Physical constraints on marine osmotrophy in an optimal foraging context . Marine Microbial Food Webs , 7 : 121 – 161 . Google Scholar OpenURL Placeholder Text WorldCat Larsen A. , Egge J. K., Nejstgaard J. C., Di Capua I., Thyrhaug R., Bratbak G., Thingstad T. F. 2015 . Contrasting response to nutrient manipulation in Arctic mesocosms are reproduced by a minimum microbial food web model . Limnology and Oceanography , 60 : 360 – 374 . Google Scholar Crossref Search ADS PubMed WorldCat Levinsen H. , Turner J. T., Nielsen T. G., Hansen B. W. 2000 . On the trophic coupling between protists and copepods in arctic marine ecosystems . Marine Ecology-Progress Series , 204 : 65 – 77 . Google Scholar Crossref Search ADS WorldCat Lewandowska A. M. , Boyce D. G., Hofmann M., Matthiessen B., Sommer U., Worm B. 2014 . Effects of sea surface warming on marine plankton . Ecology Letters , 17 : 614 – 623 . Google Scholar Crossref Search ADS PubMed WorldCat Lyman J. M. , Johnson G. C. 2014 . Estimating global ocean heat content changes in the upper 1800 m since 1950 and the influence of climatology choice . Journal of Climate , 27 : 1945 – 1957 . Google Scholar Crossref Search ADS WorldCat Millot C. , Taupier-Letage I. 2005 Circulation in the Mediterranean Sea. In The Mediterranean Sea. Handbook of Environmental Chemistry . Ed. by Saliot A.. Springer, Berlin/Heidelberg . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Moore C. M. , Mills M. M., Arrigo K. R., Berman-Frank I., Bopp L., Boyd P. W., Galbraith E. D. et al. 2013 . Processes and patterns of oceanic nutrient limitation . Nature Geoscience , 6 : 701 – 710 . Google Scholar Crossref Search ADS WorldCat Pauly D. , Alder J., Bennett E., Christensen V., Tyedmers P., Watson R. 2003 . The future for fisheries . Science , 302 : 1359 – 1361 . Google Scholar Crossref Search ADS PubMed WorldCat Pauly D. , Christensen V., Dalsgaard J., Froese R., Torres F. 1998 . Fishing down marine food webs . Science , 279 : 860 – 863 . Google Scholar Crossref Search ADS PubMed WorldCat Pengerud B. , Skjoldal E. F., Thingstad T. F. 1987 . The reciprocal interaction between degradation of glucose and ecosystem structure—studies in mixed chemostat cultures of marine-bacteria, algae, and bacterivorous nanoflagellates . Marine Ecology-Progress Series , 35 : 111 – 117 . Google Scholar Crossref Search ADS WorldCat Pomeroy L. R. , Deibel D. 1986 . Temperature regulation of bacterial activity during the spring bloom in Newfoundland coastal waters . Science , 233 : 359 – 361 . Google Scholar Crossref Search ADS PubMed WorldCat Pree B. , Larsen A., Egge J. K., Simonelli P., Madhusoodhanan R., Tsagaraki T. M., Våge S. et al. 2017 . Dampened copepod-mediated trophic cascades in a microzooplankton-dominated microbial food web: a mesocosm study . Limnology and Oceanography , 62 : 1031 – 1044 . Google Scholar Crossref Search ADS WorldCat Prowe A. E. F. , Visser A. W., Andersen K. H., Chiba S., Kiorboe T. 2019 . Biogeography of zooplankton feeding strategy . Limnology and Oceanography , 64 : 661 – 678 . Google Scholar Crossref Search ADS WorldCat Raveh O. , David N., Rilov G., Rahav E. 2015 . The temporal dynamics of coastal phytoplankton and bacterioplankton in the Eastern Mediterranean Sea . PLoS One , 10 : e0140690 . Google Scholar Crossref Search ADS PubMed WorldCat Record N. R. , Ji R. B., Maps F., Varpe O., Runge J. A., Petrik C. M., Johns D. 2018 . Copepod diapause and the biogeography of the marine lipidscape . Journal of Biogeography , 45 : 2238 – 2251 . Google Scholar Crossref Search ADS WorldCat Rose J. M. , Caron D. A. 2007 . Does low temperature constrain the growth rates of heterotrophic protists? Evidence and implications for algal blooms in cold waters . Limnology and Oceanography , 52 : 886 – 895 . Google Scholar Crossref Search ADS WorldCat Ryther J. 1969 . Photosynthesis and fish production in the sea. The production of organic matter and its conversion to higher forms of life throughout the world ocean . Science , 166 : 72 – 76 . Google Scholar Crossref Search ADS PubMed WorldCat Sandaa R.-A. , Pree B., Larsen A., Våge S., Topper B., Topper J. P., Thyrhaug R. et al. 2017 . The response of heterotrophic prokaryote and viral communities to labile organic carbon inputs is controlled by the predator food chain structure . Viruses , 9 : 40 – 54 . Google Scholar Crossref Search ADS WorldCat Santinelli C. , Sempere R., Van Wambeke F., Charriere B., Seritti A. 2012 . Organic carbon dynamics in the Mediterranean Sea: an integrated study . Global Biogeochemical Cycles , 26 : GB4004. Google Scholar OpenURL Placeholder Text WorldCat Scheffer M. , Hosper S. H., Meijer M. L., Moss B., Jeppesen E. 1993 . Alternative equilibria in shallow lakes . Trends in Ecology & Evolution , 8 : 275 – 279 . Google Scholar Crossref Search ADS PubMed WorldCat Thingstad T. F. , Aksnes D. L. 2018 . Why growth of nutrient-limited micro-organisms should have low-temperature sensitivity . The ISME Journal , 13 : 557 – 558 . Google Scholar Crossref Search ADS PubMed WorldCat Thingstad T. F. , Bellerby R. G. J., Bratbak G., Borsheim K. Y., Egge J. K., Heldal M., Larsen A. et al. 2008 . Counterintuitive carbon-to-nutrient coupling in an Arctic pelagic ecosystem . Nature , 455 : 387 – 390 . Google Scholar Crossref Search ADS PubMed WorldCat Thingstad T. F. , Havskum H., Zweifel U. L., Berdalet E., Sala M. M., Peters F., Alcaraz M. et al. 2007 . Ability of a “minimum” microbial food web model to reproduce response patterns observed in mesocosms manipulated with N and P, glucose, and Si . Journal of Marine Systems , 64 : 15 – 34 . Google Scholar Crossref Search ADS WorldCat Thingstad T. F. , Lignell R. 1997 . Theoretical models for the control of bacterial growth rate, abundance, diversity and carbon demand . Aquatic Microbial Ecology , 13 : 19 – 27 . Google Scholar Crossref Search ADS WorldCat Thingstad T. F. , Pengerud B. 1985 . Fate and effect of allochthonous organic material in aquatic microbial ecosystems. An analysis based on chemostat theory . Marine Ecology Progress Series , 21 : 47 – 62 . Google Scholar Crossref Search ADS WorldCat Thingstad T. , Rassoulzadegan F. 1999 . Conceptual models for the biogeochemical role of the photic zone food web, with particular reference to the Mediterranean Sea . Progress in Oceanography , 44 : 271 – 286 . Google Scholar Crossref Search ADS WorldCat Thingstad T. F. , Våge S., Storesund J. E., Sandaa R.-A., Giske J. 2014 . A theoretical analysis of how strain-specific viruses can control microbial species diversity . Proceedings of the National Academy of Sciences of the United States of America , 111 : 7813 – 7818 . Google Scholar Crossref Search ADS PubMed WorldCat Tsagaraki T. M. , Pree B., Leiknes O., Larsen A., Bratbak G., Øvreås L., Egge J. K. et al. 2018 . Bacterial community composition responds to changes in copepod abundance and alters ecosystem function in an Arctic mesocosm study . ISME Journal , 12 : 2694 – 2705 . Google Scholar Crossref Search ADS PubMed WorldCat United Nations. 2019 . World Population Prospects. Comprehensive Tables, I. Department of Economic and Social Affairs, Population Division. https://population.un.org/wpp/ (last accessed 8 April 2020). Vadstein O. , Stibor H., Lippert B., Loseth K., Roederer W., Sundt-Hansen L., Olsen Y. 2004 . Moderate increase in the biomass of omnivorous copepods may ease grazing control of planktonic algae . Marine Ecology Progress Series , 270 : 199 – 207 . Google Scholar Crossref Search ADS WorldCat Verity P. , Smetacek V. 1996 . Organism life cycles, predation, and the structure of marine pelagic ecosystems . Marine Ecology Progress Series , 130 : 277 – 293 . Google Scholar Crossref Search ADS WorldCat Våge S. , Bratbak G., Egge J., Heldal M., Larsen A., Norland S., Lund Paulsen M., et al. 2018 . Simple models combining competition, defence and resource availability have broad implications in pelagic microbial food webs . Ecology Letters , 21 : 1440 – 1452 . Google Scholar Crossref Search ADS PubMed WorldCat Wambeke F. , Christaki U., Giannakourou A., Moutin T., Souvemerzoglou K. 2002 . Longitudinal and vertical trends of bacterial limitation by phosphorus and carbon in the Mediterranean Sea . Microbial Ecology , 43 : 119 – 133 . Google Scholar Crossref Search ADS PubMed WorldCat Wollrab S. , Diehl S., De Roos A. M. 2012 . Simple rules describe bottom-up and top-down control in food webs with alternative energy pathways . Ecology Letters , 15 : 935 – 946 . Google Scholar Crossref Search ADS PubMed WorldCat Yamaguchi R. , Suga T. 2019 . Trend and variability in global upper-ocean stratification since the 1960s . Journal of Geophysical Research-Oceans, 124 : 8933 – 8948 . Google Scholar Crossref Search ADS WorldCat Zöllner E. , Hoppe H. G., Sommer U., Jürgens K. 2009 . Effect of zooplankton-mediated trophic cascades on marine microbial food web components (bacteria, nanoflagellates, ciliates) . Limnology and Oceanography , 54 : 262 – 275 . Google Scholar Crossref Search ADS WorldCat © International Council for the Exploration of the Sea 2020. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. © International Council for the Exploration of the Sea 2020.

Dayton, Paul K

doi: 10.1093/icesjms/fsaa085pmid: N/A

Abstract I describe my unlikely path into marine science from a childhood in the Arizona desert and Oregon woods. Without realizing it, I developed a sense of place in nature and the value of open interdisciplinary communication among diverse scientists. My undergraduate education emphasized physiological adaptations to the environment or what might now be considered the “fundamental niche”, and my graduate thinking was inspired by a population/community based evolutionary understanding of how strong interactions define a “realized niche”. I have attempted to define strong interactions in three different ecosystems. This difficult problem is confounded by the loss of natural systems resulting from human impacts. I discuss my frustrations with eroding conservation efforts in a society that is rapidly devaluing nature and consider how we might recover our most fundamental values. I conclude that there is an urgent need to improve field-based teaching of undergraduate non-majors about nature and to be much more effective in our interactions with the general public. If we hope to have our legacy include a liveable world with natural places, we urgently need to act unilaterally to shift some of our values and reward systems towards the challenge of educating the undergraduates and especially the general public. Foreward Science is a human endeavour driven by curiosity about our world. We are proud of our accomplishments and are anxious to share our insights. Lost in the normal scientific discourse is the human dimension that drives our individual science. What inspired us to forego other careers? How did we learn about doing science? What are the natural processes we find most interesting, and how did we define our questions and methodology. To err is human; how do we learn from our errors? What are we most proud of, and why? What would we do differently if we could try again? Looking back, what were the highs and lows of our human experience doing science? How did these emotions influence our science? I look to the giants in science and wonder what they were really like as human beings? What were their long-range goals and how did they approach their basic questions? Here, I attempt to integrate my personal development with my ecological research. I discuss the three ecosystems I have studied and review some of the methods that helped understand the strong interactions and how they scale in space and time. In most cases, I have had to rely on natural history to define the appropriate questions. We will never understand the manifest complexities in community ecology, never disentangle Darwin’s tangled bank, without the benefit of the intuition and biological appreciation garnered by studying nature the way it has evolved, rather than the alternative and dismal shadow associated with accelerating human intervention (Paine, 1994). Discovering nature while learning to read My father worked outdoors on Arizona ranches, in mines and, eventually, in logging camps in southern Oregon. I spent my early years mostly alone in nature until I was unsuccessfully thrust into a one room-school in Drew, OR, a tiny logging town. As a hopeless dyslexic, I was dysfunctional and clueless in that rough environment and became the punching bag for the school bully. “Paulie, just try to see the world through his eyes” was the advice my mother offered. However, I was strong for my age, and once I learned how, I derived much more pleasure from beating the shit out of Butch rather than understanding him (forgive me dear reader for the language, but it describes the event); but for a 6-year old coming from the Arizona desert, the Oregon woods were much scarier than the bully and nature was my main adversary. At that time in my life, we and the families around us killed or grew much of the food we ate and nature was something that needed to be exploited, tamed, or modified by clearing gardens, finding food, and eliminating danger. My attitude towards nature was much like it was towards Butch, something to be conquered. Until I learned to read, much later, I avoided school and spent most of my time in different natural habitats and, without thinking about it, I acquired a rough sense of place at an early age. My mother’s advice finally took hold as I learned to empathize with nature and to understand her. At first, my sense of place lacked the sensitivity, the understanding that my mother advocated for the bully. However, as I learned to consider the plants and animals from their perspective, I developed an awareness of their individual habitats, behaviour, and environmental needs to survive, grow, and reproduce. The family began making winter trips to San Carlos Bay, near Guaymas, Mexico, where I learned to snorkel and discovered an utterly new world. By age 10, I had a good understanding of terrestrial natural history, but this marine environment was totally different, and more scary, than the bully or the woods; but there was still the challenge to understand it, and when the family returned to our roots in Tucson, AZ, near the Gulf of California, I was able to spend a great deal of time in the water learning a very different natural history integrated with the observations in Steinbeck and Ricketts (1941). At first, my objective was killing things to eat, but with the familiarity came the empathy and understanding of this system. Cousteau’s Silent World (Cousteau and Dumas, 1953) was an inspiration, and by 1956, I made my own scuba equipment from discarded tanks stolen from a junk yard, a B-29 regulator, and simple pipe from a hardware store. This rig almost killed me, but not before it gave me enough time underwater to begin to understand and empathize with the behaviour of the marine animals from their perspective and to develop a sense of place for this strange new world. By the 1960s, people were using scuba to over-exploit the large fish and badly damage the gorgonian habitats that so fascinated me and I developed an obsession with becoming a marine biologist. Eugenie Clark and Rachel Carson were marine ecologists I could relate to and, when I read Carson’s Silent Spring (Carson, 1962), I realized how important it was to develop a scientific understanding sufficient to protect the marine systems. The dyslexia prevented me from understanding abstract processes such as learning languages, or worse, mathematics, but I did understand natural history, and I hoped that might be enough for me to become a marine ecologist. Cooperation and the value of interdisciplinary research On returning to the family roots in Tucson, we spent much of our time with old family friends from the University. My grandfather had arrived in Tucson in the 1920s as a professor at the University of Arizona and then an isolated little school in the desert. In those days, some of the professors met regularly to discuss their research and ideas, and these interactions persisted through my youth. A.E. Douglas and Ed Schulman developed dendrochronology as a means of dating old trees. They were interested in sunspots and climate, but Emil Haury, an archaeologist, was fast to recognize the value of precise dating, and this precision revolutionized archaeology and is still invaluable for such things as dating the Anasazi migration. Haury and others were also excited about finding Clovis spear points in local mammoth bones demonstrating that early humans were able to kill even the largest mammals. Paul Martin, then a palynologist, inspired by the mammoth sites, used his precise understanding of Holocene climate and astute natural history to develop a theory of overkill to explain the massive Pleistocene/Holocene extinctions in North America. This too revolutionized Pleistocene/Holocene ecology by forcing us to recognize the role of humans in extinctions. Rod Hastings, the mayor of a small mining town (and a meteorologist connected with the University scientists), realized that the old archived photographs of the region showed large-scale changes, and he hooked up with Ray Turner, a brilliant desert ecologist, and together they developed a regional understanding of a changing desert biota by comparing old and recent photographs (Hastings and Turner, 1965). This too resulted in a growth industry of scientists extracting valuable data from archived photographs. This continuum of paleo to historic to recent ecological synthesis was tested and modified by Paul Martin and others at the Desert Research Lab as they developed the science of analysing packrat middens to permit a very precise understanding of the distribution of vegetation through the last 30,000 years. These techniques have been used worldwide to evaluate ecological changes from the Pleistocene through historical time scales. As I went through high school and college in Tucson in the 1950s, I knew these people as family friends, and I was able to watch this remarkable community of scientists interacting across their several disciplines as they developed a rare holistic understanding of the natural world through regular meetings. I now realize that this remarkable explosion of scientific breakthroughs in one community was unusual and was stimulated by the fact that these very diverse scientists were good friends who met regularly to discuss and debate their ideas in an open way that we rarely see in this age of specialists who are so often competitive and secretive. Today scientists rarely make time for such interactions and natural scientists are forced into research focused on small scales in space, and especially in time, because so much depends on getting results within a cycle of a single grant or perhaps even within a single progress period. Perhaps most importantly, I learned from Paul Martin the value of synthesizing large temporal and spatial scales into a very multidisciplinary overview that allows a much more integrated understanding of the holistic natural history of the system. This overview is a critical but rarely appreciated factor in identifying the most interesting questions and processes to study. Empathizing with nature to understand her Searching for a career During my undergraduate years at the University of Arizona, I received excellent ecological mentoring from Bob Bezy and other students in Chuck Lowe’s laboratory as well as from Bill Heed, a Drosophila ecologist. At this time, the field of ecology was shifting into the ecosystem emphasis promoted by the Odum’s textbook (Odum, 1953), but in Lowe’s laboratory, there was an emphasis on environmental physiology, especially the role of temperature in defining “niches”. By being exposed to both approaches, I was well grounded in an intuitive understanding of what might be considered the “fundamental niche” of optimizing the physiological needs of the organisms. At the time, I tried unsuccessfully to generalize and apply this perspective to marine systems. As an undergraduate I had flirted with archaeology and spent the summer of 1961 working on an archaeological project at Cape Krusenstern and Onion Portage on the Kobuk River in northwest Alaska. This contributed to an invitation to work at McMurdo Sound in 1963 through the end of 1964. I had expected that the cold would select for very different marine organisms but learned that organisms in polar seas were well adapted to cold. It was much colder then than it is now and the living and working conditions were very primitive. I had to learn to be independent, repair equipment, anticipate and prevent risk, and solve field related problems on my own. For example, I repaired the chain saws, generators, and even the tracks on our tracked vehicle. I remembered how to use dynamite from watching loggers in my youth and figured out how to blast holes through the ice rather than the painful chainsaw process then being used. As I gained competence doing field work, I realized that the Antarctic was not a system I wanted to tackle for a PhD thesis. Intertidal ecology: learning to define questions On my return in January 1965, I went to graduate school at the University of Washington, where I decided to work with Bob Paine on the intertidal system that seemed appropriate to the terrestrial-based type of ecology familiar to me. I drove all over the state spending every low tide trying to develop the sense of place I had for the desert and Oregon woods, but the intertidal was all new to me, and I was overwhelmed with the complexity that included competition for primary space and sunlight, many types of predation from cryptic flatworms and nemerteans, many snails, nudibranchs and crabs, grazing molluscs and crustacea, patchy predation and grazing by asteroids, and urchins, as well as interesting kleptoparasites stealing prey from snails and asteroids. More confusing, each of the many different intertidal habitats in the region was very different from the others. I was utterly overwhelmed with the seeming chaos of the system and had no idea how to begin a thesis. It was clear that I still did not really understand how science works. The ranchers, prospectors, and loggers of my youth knew a tremendous amount about the natural history of their systems, as did the Native Americans I spent time with, but for the most part they were not interested in generalizing processes. In graduate school, Gordon Orians and Bob Paine introduced me to an evolutionary rather than physiological approach to ecology. Platt’s (1964) paper on strong inference influenced my attempt to disprove hypotheses. I learned that, in ecology, our goal is to make interesting and accurate generalizations about nature based on as few relevant parameters as necessary. The idea of narrowing down the relevant parameters is critical because all nature is somehow related, but the trivial or marginally important relationships need to be weeded out so as to focus on those parameters essential to the generalization. Identifying the appropriate simplifications is critical and cannot be done without a deep sensitivity to the relevant natural history of the systems we study. Most of the elegant competition-based models of the era seemed interesting but also irrelevant to the reality that I observed as I crawled around the rocky shores. The more I explored, the more I appreciated the complexity of the system that was also difficult to relate to Paine’s (1969) keystone predator perspective that emphasized the importance of a predator reducing the impact of the top competitor in the system. This only applied in relatively rare mussel dominated intertidal habitats exposed to unusually heavy wave exposure where mussel recruitment was much more common. Indeed, few of the various intertidal habitats I visited seemed functionally similar to each other and it was difficult to generalize the processes that I observed from place to place. All of the habitats were strongly influenced by disturbance, but these disturbances ranged from extreme temperatures and desiccation to various predators, to physical bashing by drift logs to grazing and bulldozing by limpets. Desperate to start my thesis, I was overwhelmed by this seemingly chaotic world. Happily, I was lucky to be surrounded by a group of fellow graduate students who listened and asked questions and very much helped me focus on a thesis based on the most important species for which primary space would be an easily quantified potentially limiting resource and the environmental factors that controlled their distribution and abundance. There were two zones: a higher barnacle and mussel zone and a lower zone dominated by many species of algae. My 1950s era ecology education had stressed the importance of understanding successional processes, and this required a focus on recruitment (survivorship to reproduce) processes that represented a slight but important difference from the then-popular focus on competition or predation paradigms of the time. Settlement and survivorship seemed to be generally important processes, and I concentrated on facilitation, long a critical cog in the old succession literature. There was a great deal of evidence for various types of facilitation, including filamentous algae hosting many types of larvae, especially the important mussel larvae, or coralline algae chemically attracting larvae and inducing metamorphosis, many species offering protection from desiccation, etc. Indeed, facilitation worked both ways as it enhanced the predation on barnacles by whelks in limited areas when the whelks escaped desiccation during spring tides by sheltering in clones of anemones. In hindsight I realize that I was applying my mother’s advice of seeing the world through the physiological and evolutionary “eyes” of the organisms. It is relatively easy to empathize with animals as they balance their need to procure resources and avoid risks, but this was difficult with the seaweeds that were important players in my intertidal world. Their competition for space and light was obvious, and Vadas (1968) had studied the chemical defences in algae, so I was well aware of defence tactics of algae, but I struggled to see the world view of the small, sometimes filamentous little sea weeds with such bedazzlingly complicated life histories. It was hard to imagine their physiological and ecological needs. Yet, in some cases, they were important players, overgrowing other organisms or serving as nurseries for larvae of important animals such as mussels. I also realized that the physiologically optimal habitats did not necessarily reflect the actual realized habitat for the species. To be sure, many species have the strongest interactions in habitats to which they are physiologically well adapted. However, in some cases, the physiologically optimal habitat was very different from the habitat where the species was most abundant and dominant (see footnote 1 in the Supplementary data). This confusing kaleidoscope perspective emphasized the importance of testing hypotheses, not necessarily with the then-popular controlled experiments, but also by comparing observations in the field among habitats and/or across times. I struggled to define hypotheses that were amenable to crude experiments or tests across several intertidal environments. When I succeeded, these experiments demonstrated that some species played stronger roles in the community than other species and they laid the groundwork for studying multiple interactions with varying ecological roles. Most species apparently could be removed without much consequence to the community. More importantly, it was virtually impossible to generalize the strengths of these roles (or dominance as I referred to it then) across spatial and temporal gradients. Despite the insights drawn from these field experiments, they are but one tool in our tool kit as we strive to understand nature. Careful natural history studies covering large areas and observations over long-time periods offer extremely important insights about prioritizing various mechanistic processes (Able, 2016). Hastings and Turner (1965) successfully synthesized their photographs, natural history observations, and relevant literature to test many existing hypotheses about environmental forcing factors such as fire, grazing, and climate in the American and Mexican Sonora Desert. Unfortunately, even these extremely valuable data are often ignored because many ecologists demand unnecessary tests of and focus on analytical statistics with unnecessarily rigorous restrictions eliminating or devaluing the use of appropriate and important natural history observations (see footnote 2 in the Supplementary data). Antarctic benthic ecology: lessons from flawed questions After wintering over in the Antarctic, and as I began my intertidal thesis project at the University of Washington, I wanted to follow up on the example of Verne Peckham who had earlier demonstrated that scuba-based research under the ice at McMurdo Sound was feasible. With the encouragement of George Llano, the best programme manager I ever knew, I persuaded Bob Paine to front an NSF proposal to do a diving project at McMurdo. My proposal was based on remarkable early programmes by Dearborn (1965) who detailed the benthic biota of the area and Littlepage (1965) who described the coastal physical oceanographic processes. Littlepage’s thesis was decades ahead of that field and emphasized the remarkable stability in temperature and oxygen, the processes I considered important at the time. My 1966 proposal was designed to test the relative roles of predation vs. competition in light of the deep-sea ecology controversies of the era, and it was based on the use of cages designed to selectively exclude or include predators to test the roles of predation by fish and seals. I discuss this long-term programme in some detail to demonstrate the importance of learning from and responding to mistakes, to emphasize the importance of being sensitive to spatial and temporal scales and to relate a few lessons of general interest. The first few 1967 dives in wet suits were memorable. You drop into a dark hole in thick ice, pull yourself down a weighted line, the cold hits your face and stuns you, but this is quickly forgotten in the excitement. As you move below the 2–5-m thick ice your eyes adjust to the darkness you are overwhelmed with the water clarity—the bottom, the distant shore, and a few jelly fish pulsing along in the distance. It is as if you are swimming in air! We immediately discarded the assumption of a totally stable homogeneous habitat as we could see that the bottom was obviously zoned by ice disturbance that extended to depths of 30 m. Thus, we found ourselves working between 30 and 60 m, much deeper than we had anticipated. Our natural history observations persuaded us that my goal of studying fish and seal predation was totally irrelevant to the sponge dominated community below 30 m, and we had to completely drop those questions and refocus on sponges and asteroids, their most conspicuous predators. We installed some 60 cages to a depth of 60 m assuming that sponges would settle and grow and that asteroids would eat enough prey to measure consumption, and we would have clean results when we returned. Antarctic sponges turned out to be more complicated. When we returned in 1968, almost nothing had changed: no growth, no measurable predation, and brooding asteroids still had eggs that seemed to be the same stage of development as they were the year before. Still another critical assumption was spoiled by natural history. I still remember the first few dives the next season that had started with such high expectations of describing competitive relationships and predatory impacts only to realize that nothing had happened, and how acutely disappointed Gordon Robilliard and I were as we sat in the ice hut contemplating our failures. We had made over 200 deep dives the year before in marginally functional wet suits with nothing to show for it. Faced with an almost complete failure of our experiments, with the exception of a single cage that was overflowing with a fast growing competitively dominant sponge, we had to retrench once again and apply ecosystem procedures to evaluate energy flow through trophic levels to estimate sponge consumption by the various predators. With this in mind, we used crude measures of potential energy channelled into growth, reproduction, and respiration to estimate the actual consumption of the various asteroids. We had tagged enough asteroids to estimate growth, and we measured gonad indexes and respiration, which gave reasonable estimates of the energy budgets of the predators. We also had to collect and process the sponges for bomb calorimetry, done later in Paine’s laboratory by my wife, Linnea. Our paper (Dayton et al., 1974) offered the overwhelming conclusion that the sponge predators were not in any sort of steady-state relationship with their prey, another important preconceived idea of stability disproven by nature (see footnote 3 in the Supplementary data). When evaluated over decades, my long-term assumption of a stable environment also turned out to be spectacularly wrong (Dayton et al., 2019). At first, the community enjoyed a relative stasis with very little recruitment or growth. Dozens of artificial substrata were deployed in the water column at several different sites for some 30 years with virtually no sponge recruitment, despite the fact that they were removed from the benthic predators. However, in about 2000, following an environmental perturbation involving iceberg-blocking advection of large phytoplankton and sea-ice melting induced by oceanographic changes, there was a massive settlement of a wide range of sponge species on the artificial substrata but almost never on the natural substrata (Dayton, et al., 2016). Most of these were rare species implying that, when conditions were right, there was effective dispersal and recruitment. This suggests that the availability of propagules of these species had been missing for two decades and/or that the propagules were there, but the facilitating environmental factors (probably appropriate food) were limiting. Their absence on natural substrata in the presence of strong recruitment on artificial substrata implies that these propagules were vulnerable to unknown benthic predators, probably including the agglutinated foraminifera, a group ignored by most benthic ecologists. And as with all the other habitats I studied, none of the generalizations travelled well as the benthic associations at McMurdo Station were very different within a few kilometres (2–5) to the north and south. There, the differences were driven by ice conditions, especially the amount of snow that accumulated on the surface of the ice. In this sense, the local wind fields strongly influence the composition of benthic communities by affecting benthic productivity. All of these programmes were begun in the 1960s, and as my career moved along, I developed my questions by mentally asking the organism how it best maximized fitness. This usually led me to focus on recruitment processes, long the emphasis of the fishery literature, but often forgotten by those working in other systems. In my case, I focused on the species that seemed to be the most important players in the communities. The successful settlement and survival of their propagules was influenced by a myriad of physical–biological interactions that were often not apparent from the experiments (see footnote 4 in the Supplementary data). Kelp ecology: the importance of oceanographic processes Without mathematicsI never thought that I was qualified for an academic position, but I applied for, and was surprised to get, a job at the Scripps Institution of Oceanography in 1970. I had long been intrigued with subtidal kelp communities because of the apparent parallels with terrestrial forests, and at Scripps, I was able to build on one of the world’s first kelp ecology programmes led by Wheeler North. As with my thesis research supported by Bob Paine and Joe Connell, I was very fortunate to move into kelp research with a great deal of support and encouragement from North and Mike Neushul, both of whom generously shared advice, equipment, and most importantly, encouragement. I had been inspired by an early paper (McLean, 1962) demonstrating the important roles of sea otters in kelp ecology by eating the sea urchins that otherwise overgraze kelp forests. I was lucky to be able to pursue this question with research trips to the far ends of the earth in the early 1970s. Amchitka Island in the Aleutian Islands of Alaska had one of the first populations of sea otters to recover from fur harvests and the otters were known to be at their carrying capacity. There, in an area with virtually no grazers, I found a situation with very diverse kelp species and several levels of understory kelps allowing me to evaluate competitive hierarchies at different depths (Dayton, 1975). I explored kelp habitats at the other end of the earth in South America from Isla de los Estados in Argentina up the coastal fjords of Chile with the idea of studying the large kelp forests that Darwin had discussed. These kelp forests evolved without sea otters and I was interested to learn what controlled the sea urchin populations allowing the kelp forests that Darwin observed. For most of the Chilean southern coast it turned out that Loxechinus albus, the most important grazing sea urchin, was not controlled. It seemed that the abundance of giant kelp along much of the southern shores of Chile was limited by nutrients in the fjords and Loxechinus in most areas. However, in the far southern coasts of the Cape Horn Archipelago, Tierra del Fuego, and Isla de los Estados, the Loxechinus were relatively rare presumably because the strong Circumpolar Westwind Drift flushed their larvae away from shore resulting in very large kelp forests (Dayton, 1985; Friedlander et al., 2020). In southern California, I set about manipulating canopies with the idea of describing competitive hierarchies while my colleague at the time, Rick Rosenthal, recognized the value of establishing baseline transects that he helped implement, and over time the transects have proven to be gold mines. The competitive relationships I defined turned out to be idiosyncratic because the dominance hierarchies were defined by wave exposure, depth, and surface nutrients and they were extremely variable. The interaction strengths varied over short distances (hundreds of metres) in both cross-shore and long-shore dimensions. Most of the within kelp community dynamics were driven by substrata and depth, canopy competition for light, the kelps absorption of nutrients, and a strong edge-effect involving nutrient uptake and planktivorous predators. It was frustrating not to be able to generalize between different kelp forests separated even by tens of kilometres. And geographically distinct kelp forests can have utterly different interaction strengths for several oceanographic reasons, usually related to nutrient limitations or wave shock differentially impacting the giant kelp that depends on surface nutrients and is susceptible to wave shock that dislodges the plants. In both cases, but for different reasons, the understory kelps become dominant. I believe that the evolutionary patterns reflect the kelp demography, especially their recruitment biology. The effective dispersal of their gametes was limited to a metre or so because the male and female gametes had to be almost touching for fertilization to occur. This very much influenced the patch dynamics, as did the grazing by small herbivores whose identities I never learned. The same Allee Effect applied to abalones and other kelp forest invertebrates that Mia Tegner, Ed Parnell, and others in my group worked on. Because my background had focused on biological interactions rather than physical effects, I was slow to learn the importance of large-scale oceanographic processes. Fortunately, the baseline transects allowed us to define the nutrient forced impacts of the 1976 regime shift on the kelp forest (Tegner et al., 1996, 1997). Eventually Ed Parnell integrated our time series data with long-term aerial photographs of kelps to produce a very sensitive measure of regional kelp growth rates back to at least 1955. These data defined subtle differences in the cross-regime shift kelp responses to heat and nutrient disturbances due to very large-scale low-frequency oceanographic changes (Parnell, et al., 2010). Generalizing interaction strengths Hindsight helps focus research trends over a long and diverse career. My early intertidal research focused on the environmental control of dominance or what we now refer to as interaction strengths. Paine (1980) introduced the concept of interaction strength, and he published a figure of the same simplified intertidal system as seen through the perspectives of three approaches to ecology: descriptive definition of food webs, flow of potential energy via trophic links, and functional approaches based on strong interactions. He advocated the latter approach via experimental manipulations. This contrasted with my 1960-era project in the Antarctic in which my experiments had failed. To salvage the project, I had to synthesize food web data with the rough measure of energy flow to define the strong interactions using the same descriptive and ecosystem approaches that Paine would later criticize (Paine, 1980). Perhaps the most important immediate lesson here was the value of using alternative diverse methods to solve difficult problems. Unfortunately, rather than using these separate approaches such as ecosystem descriptions, food web studies, population dynamics, or evolutionary modelling to synthesize a strong holistic understanding of community ecology, these different disciplines have become more specialized and, in many cases, more isolated from each other, and importantly, isolated from natural history. A common problem with the generalizations that ecologists offer is that many are based both on preconceived ideas isolated in our specialties and inappropriate assumptions rather than on the reality derived from good natural history. The art of appropriate simplification and definitions of our hypotheses depends on a basic understanding of nature and somehow remains an art rather than a science. Good naturalists have a “feel” for the system and the ability to weed out the marginally relevant parameters realizing that all nature is trivially related. However, to be generally interesting and useful, our hypotheses and tests need to address the most important patterns and processes. Moreover, while rarely acknowledging the value of anthropomorphic thinking, naturalists intuitively employ the suggestion my mother offered so long ago as they perceive the complex interactions through the evolutionary perspective of the individual organisms. In a sense, we utilize the ancient art of storytelling as we fantasize different solutions to our questions. Remember that the human brain has evolved around storytelling. For most of human history, storytelling is how people communicated lessons and then remembered them. Scaling dispersal, settlement, growth, and survival The other theme of my career has been the struggle to understand how to scale the most important community processes in time and space. In my case, a consistent conclusion of my work was that the structures of the communities I studied reflected past disturbance and/or recruitment events. That is, the coastal communities are dominated by important species defined by long-lived individuals that comprise slowly declining populations characterized by variable mortality and episodic recruitment. Sometimes dormancy or storage effects contributed to their apparent resilience. The importance of episodic recruitment is well recognized in the fishery literature, which focuses on scales of 100 to 1000 s of kilometres, and represents a continuing issue for the coastal species I studied. This implies that the scale of resolution may be the single most important component of this research because it predetermines the questions and hypotheses as well as the procedures of the research. In 1985, I had an opportunity to spend a sabbatical year at the Australian Institute of Marine Sciences where there was an active programme evaluating the coastal oceanographic processes driving larval distribution over large scales. I wanted to integrate dispersal processes with the actual settlement and survival of sessile species. We studied the patterns and processes of recruitment of many species of oysters across the Great Barrier Reef and found the same factors of dispersal, facilitation, and predation (from the “wall of mouths” to flatworms) influenced settlement and survival, and thus the scale and temporal patterns of recruitment. The post settlement growth and survival reflected nutrients but most importantly emphasized several different types of predation (Dayton et al., 1989). I am proud of that paper, although it has received almost no attention. I never successfully tested the relative strength of the interactions across spatial or temporal gradients. That is, I found it easy to identify the strong interactions with observations and simple experiments, but very difficult to articulate, measure, or test processes defining the interaction strengths that separated fundamental from realized niches. The rest of my career focused on similar efforts to understand the evolutionary processes in time and space driving the composition of coastal benthic communities. I have had some success, but a meaningful synthesis has eluded me, implying that I have not asked the correct questions to understand scaling of the realized niche. However, it is far better to be interestingly wrong than trivially correct and my failures to solve the big questions have contributed to improved understanding of benthic community processes. It is important to take pride in clear failures that redirect and refocus the questions that lead to a deeper truth. A common but serious intellectual mistake is to find an exception to a generalization and discard the generalization rather than to understand the exception. The old adage of an “exception that proves the rule” is based on the Latin probare meaning to probe or test the rule. While not being particularly proud of my failures, I fell victim to social pressures in ecology. The powerful influence of competition-based models of the era influenced me to accept the density dependent focus of David Lack (1954) and ignore the density independent ideas of Andrewartha and Birch (1954) and miss the obvious truth that it is never an “either/or” situation. I should have better respected my undergraduate roots and also focused on environmental factors as well as the biological interactions. I believe that ecological fads put undue emphasis on quantifying obvious relationships, relying on simplified field experiments, and using very restricting and inappropriate statistics to demonstrate things I already knew. These very restrictive views of proper ecological research impeded the larger understanding I sought. This was not true for my Antarctic programme because in the beginning I did not know the natural history, but otherwise my work was low risk because mostly I knew the answers from the beginning. In hindsight I simply should have trusted my natural history observations of patterns and process and not wasted time quantifying obvious patterns and testing hypotheses when I already knew the answers. It was obvious that the interaction strengths varied over environmental gradients, I recognized the gradients, and I should have searched for environmentally induced thresholds in the interactions that I studied. But what are natural communities? Or how I fell out of the ivory tower? I based my questions on the assumption that I was studying fundamental and realized niches that reflected natural communities embedded in their specific and dynamic environments. Eventually I realized that there were virtually no natural communities left in the face of human intervention. Most natural marine wetlands have been “restored” by human development, and most of those few that have been protected are too small and isolated to experience the flushing and coastal dispersal of larvae necessary to sustain natural populations. The cascading impacts include the loss of nursery habitats for many species of fish and invertebrates as well as most coastal birds. Most importantly, ecosystem overfishing by commercial and recreational fishing has had an enormous impact on marine ecosystems leaving most marine communities with important predators functionally missing and natural benthic habitats virtually obliterated in many important regions. This realization has very much coloured my own perception of my career because it took me far too long to understand the problem, and my conservation efforts were too late and ineffective. I finally realized in the 1980s that the large reduction in some fish species in kelp forests was from fishing rather than pollution as I had supposed from my Rachel Carson era bias. I double-crossed the Smithsonian Institute to whom I had promised a kelp talk at a large event and instead laid out my concerns about fishing impacts. Afterwards, I was threatened by a couple suits I assumed were fishery lobbyists. I did not realize it at the time, but this resulted in a major change in my career. I set about collecting as much information as I could find with the limited search engines of the era. I gave countless lectures and with colleagues even wrote a review paper (Dayton et al., 1995) about environmental effects of fishing that was difficult to get published. I had the naive idea that talking about this problem would solve it, but I was disabused of this notion by the very hostile responses from some fisheries scientists who I had previously respected. This was to be expected, but I had not expected resistance from academic colleagues. This I came to understand when Mia Tegner and I were sent to a meeting of coastal ecologists, and as we had breakfast before the meeting we found ourselves sitting about a metre from a bearded fellow regaling a table of colleagues about the upcoming meeting. I could not avoid overhearing when suddenly he informed them that they would even see Paul Dayton, a real extremist whose claims were vastly exaggerated. I calmed Mia who was about to launch herself at the fellow and learned that the subtle resentment I was aware of from many academic ichthyologists was based on the fact that I was not an expert on fishes and, therefore, had no business spreading these concerns they thought had a negative impact on their credibility. I had never expected so much opposition to what I thought was a simple but important message, but importantly it also introduced me to the question of whether scientists dealing with objective facts lose their credibility when they advocate some political cause relating to what they have learned. This question continues to be a very important issue for those ecologists who want to share their results and have a voice in social dialogues. It became clear that my personal efforts had virtually no impact. It was not until Daniel Pauly (Pauly et al., 1998) and RAM Myers (Myers et al., 1997; Myers and Worm, 2003) collected and analysed large amounts of data and, importantly, knew how to get the information into the scientific and public discussions that the tide of public and political awareness began to change. This experience came full circle when a colleague and I agreed to evaluate a proposed salt-work project in a Mexican lagoon used by grey whales, and we found ourselves pilloried by conservation groups. I was personally opposed to the development but agreed to help research the impact on the whales because I was very interested in the region. The money I earned supported Enric Sala, a postdoc who has gone on to a very successful career in conservation activities. As we learned that the proposed project would have virtually no impact on the whales, our integrity and competence were aggressively attacked by individuals from various environmental organization. This and equally sleazy activities about alleged Antarctic pollution have persuaded me that many environmental organizations are as deceitful as the other side, and I reluctantly distanced myself from the conservation movement. However, it remains an inconvenient truth that people have heavily impacted essentially all of the habitats in the biosphere. Consider the massive apparent global loss of insects demonstrating that Rachel Carson’s Silent Spring (1962) has sprung, yet very few people notice or even care as the cascading impacts on pollinating systems and the loss of the myriad insectivore networks slowly changes the world around us. This is a huge crisis that is virtually ignored. It will be virtually impossible to understand the reasons for the loss of insects and their dispersal sources and sinks. That is, how do we separate habitat loss, GMO crops, and insecticides from climate change as our biosphere careens into its unhappy future? Despite this, I suspect most ecologists believe that they are studying natural systems. And worse, unlike the 1960s, the public does not seem to care. Defining and implementing our values As I have aged, I have wondered about the real value of all of this work. Is there a need for us to reconsider our values as ecologists struggling for recognition and support? Over the last few decades, the simplistic recognition of our scientific contributions has been formalized such that our academic promotions and success in our field is being evaluated by counting publications and where they are published irrespective of what they actually contribute. When pressed to evaluate the importance of our contributions, the establishment and the new driving forces of science quantify importance by counting citations and producing an “H” index (see Hirsch, 2020). This is a critical change from the time when science drove the science. Today, sophisticated tools, complicated, often irrelevant meta-analyses, and the conceived standards of prestigious journals seem to define our sense of good science. Many of our awards and formal recognitions seem to relate to “old boy clubs” more than the lasting quality of our science. Scientists are quick to game this system by adding authors to each other’s papers and finding ways to get their papers cited. All citations are not equal, but it is rare to see the lasting importance of a paper recognized by our administrators or peers, especially a recent paper that has not been seen long enough to be fully appreciated. And we recognize that the H value heavily depends upon working in a popular discipline (pity those who work in important but obscure disciplines), cultivating influential friends (spending time on the seminar circuit, going to meetings, running for offices in professional societies, etc.), and enjoying a certain amount of longevity. The latter surely has a large role in H values; consider, for example that Robert MacArthur, one of the most influential ecologists of my era, has an H value of only 42 because he died young. We all well know how hollow these criteria really are, yet even as we complain about it, we meekly continue to work within this flawed value system; but at the end of the day we can ask is this really how we want to define our legacy? Our selves? An H value? I am sure that most would say no, but again, we know what it takes to get a grant or have our papers accepted, get recognition, and be promoted, so we simply play this game we do not like. It is very important to realize that, in the big picture, we define the rules of the game when we review proposals and manuscripts, serve as editors, and write recommendations. In each case, there is the opportunity to serve as mentors rather than gatekeepers. We have the ability to recover our values and redefine our standards with honest reviews that recognize genuinely important ideas and results. In the long run, most of our work falls by the wayside or in the rare best case contributes to the evolution of our discipline. And as with most foundations, the strictly science-based impact of our papers should, in principle, be subsumed by future research. A much more lasting legacy involves the people we have influenced because they have the potential to continue to be creative scientists and mentors and influential citizens. Many ecologists mentor and take great pride in excellent graduate students in their groups, and personally, I define my career by the success of my students. There is a modest amount of recognition and reward for good graduate mentoring, but our reward systems are heavily focused on the amount of money we bring in plus counting publications, citations, H values, and altmetrics. Unfortunately, excellent mentoring of undergraduates is rarely acknowledged and academe punishes those who focus their time on teaching or attempting to educate the public, or doing important public service. Yet it is the non-major undergraduates that are the most important group of citizens that we need to inform and inspire, not necessarily to join our laboratories, but simply to care. My own efforts to reach undergraduates became increasingly disappointing as it was very difficult to extract their minds from their phones. This was especially true in classes with hundreds of students—a norm at almost all of our research institutions. If we hope to have our legacy include a liveable world with natural places and concerned citizens, we urgently need to shift some of our values and reward systems towards the challenge of educating both the undergraduates and especially the general public, exposed as they now are to increasingly narrow, simplified, and often misleading information. It is worth noting here that the bearded fellow who disapproved of my advocacy is one the most important mentors to the general public with his brilliant books. There is a desperate need for ecologists to be more proactive with the public. This institutional shift in focus, as well as subtle changes in value systems within ecology, has resulted in an erosion of the recognition of the great importance of natural history. Indeed, the value of ecology in general, and natural history in particular, has been eroded within academe by scientific elitism against natural sciences. Students have little opportunity to learn classic subjects in zoology and botany such as invertebrate zoology (including entomology!), mammalogy, herpetology, ornithology, ichthyology, phycology, plant physiology, and systematics. As a result of modern biology curricula, many first-year graduate students do not know the life history, anatomy, developmental biology, and evolution of their own study organisms. And, appallingly, I consider this to be true of some of their professors! Without this grounding, it is no wonder that the respect for natural history has been lost. It is a poignant observation that, while we lose biodiversity, we also lose the knowledge of what it is. A role model for success In this regard, my all-time ecological hero is Ken Norris, a long-time professor of Natural History at the University of California, Santa Cruz. Norris enjoyed a successful and diverse research career in science, and he trained good graduate students, but by far his greatest contribution was to establish a cultural appreciation of nature at a major university. He did this by arranging to get the students into nature on field courses in many fascinating and diverse natural settings where he taught them to build their love of nature on a solid field-based understanding. Many of these students have gone on to successful research and academic careers; however, a very large number of these students enjoyed careers outside of science, always remembering their field trips with Norris and maintaining a deep appreciation and understanding of the environment. Norris very early recognized the serious nature of the human encroachment of natural systems, and he dreamed of creating a large system of protected natural areas. He sold his dream to Mildred Mathias and Bill Mayhew, two University of California colleagues, and the three spent the rest of their careers building the dream of a system of University-controlled natural systems that now numbers well over 40 large landholdings exclusively to be used for education and field research. This involved a tremendous public relations effort that was successful largely because Norris was able to harness the enthusiasm of his former students and colleagues to educate University administrators on all the campuses, and more challenging, to inspire the Regents of the University to support this system. Most academic institutions around the world have stopped offering essentially all of the natural history-based courses. Yet, largely as a result of his influence, his University of California, Santa Cruz, now annually supports ∼1000 17–19-year-old first-year undergraduates in field trips, courses, and internships in these reserves. To be sure, some of these students major in ecology, but most of them go on to other careers never forgetting their understanding, appreciation, and love of nature. Looking forward Most ecologists have probably enjoyed their own efforts to better understand the evolution and maintenance of the various ecosystems that they study, and probably most have shared my frustrations and satisfactions with our results, and hope to continue searching for new insights and questions to better define and generalize the processes they study. I hope that colleagues also consider the more general values we cherish and that they consider how we might protect what is left of our natural world. Circling back to my mother’s concern, consider how your grandchildren will see the world when they are your age. Consider the changes in nature over your life, and imagine a planet teeming with people but without nature as we knew it. Education is our most valuable tool, not only for our ecology students but also for the general public that needs to implement the changes. Sadly, universities themselves are evaluated by high-profile research results and financial success and their faculties are judged by the narrow metrics of career advancement. Most universities have responded by ignoring or discarding the old values of mentoring critical thinking and a broad education in favour of high-profile research activities that often involve pandering to commercial interests rather than general education. Universities define themselves by biomedical and technological advances and the natural sciences are scorned as “old fashioned”. Administrators do not care that many students are anxious to translate their love of nature into science while the universities themselves focus on translating science into revenue producing patents and products. As a result, most university faculties now lack professors able to teach natural history subjects, or worse, any interest in offering them as they continue to focus on money and impact. Yet when natural history courses are offered, the students come! How many citations equates to the implementation of a programme training over a thousand freshmen a year taking natural history courses in the field? What does it take to recover these values? These changes will not come from above; they must be forced by those of us in the trenches who care. If ecologists hope to fight this trend, the battle begins at home with our colleagues, deans, and university leadership. We need to engage and redirect the risk management offices that so often have responded to litigation by making it so difficult to do and teach field science. Somehow, we need to encourage these people sitting in their comfortable risk averse worlds to facilitate rather than block our efforts to address so many urgent global environmental problems. More importantly, we need to stop complaining or blaming others for the failures and we need to make an urgent effort to teach natural history at all levels from our laboratories to undergraduate classrooms, to volunteering to talk to grade school classes and the general public. It is discouraging to watch the public believe the misinformation they get from social media; yet we should recognize the power and influence of social media and try to use it to our advantage by implementing new approaches that go beyond our staid traditional science-speak. We need to find new voices that are passionate and understandable and most of all, convincing. All of us have a tremendous amount of passion for our work. We have dedicated our careers to interesting research, and we work very hard to do it well. We know much more than we communicate, and we need to share our wisdom, and especially our passion, more broadly. We desperately need to enthuse and educate the general public because ordinary citizens no longer trust science, to some extent because they do not understand it. Rather than shunning our colleagues who attempt to simplify and explain the results of their work and results to the mass media, we all need to become comfortable sharing our emotions and especially our enthusiasm with stortelling techniques that non-scientists can relate to. The public is responsive to honest passion and personal stories about what inspired us to go into science, what keeps us awake at night and what makes us stand in awe, and what we value. Most people hang on to their childhood pleasures of hearing good stories, and all of us are awash in great stories! We just need to share them. We have an obligation “to disseminate what we discover clearly, interestingly, and impartially … so as to encourage those writers and elementary teachers whose profession it is to bring the findings to as wide an audience as possible” (Hutchinson, 1983). This essay has discussed some of my experiences and love of nature, the evolution of some of my questions and my values, and I have talked about problems in science and society that keep me awake at night and make me apprehensive for my grandchildren’s future, but I have failed to address what I consider the single most serious problem: the size of the human population. This is the source of most environmental and social crises. How can we deal with the spectre of a denatured planet without dealing with the growing human population? How might ecologists respond to this crisis? First, while not the focus of this essay, it seems essential to recognize that the crisis exists and realize the terrifying fact that Paul Ehrlich’s Population Bomb (1968) has already exploded and, combined with human greed, is the root cause of most global problems. This is the most serious issue the world faces, and ironically there are various solutions, yet it remains politically incorrect to discuss the crisis of human overpopulation. Instead, we focus on various derivative problems. We certainly cannot solve a problem if we do not talk about it, and every ecologist, yea, every thinking person, should talk about overpopulation as often as possible. Supplementary data Supplementary material is available at the ICESJMS online version of the manuscript. Acknowledgements Over many years I have started several drafts of my response to this invitation, but each try was embarrassingly naive, and I let each slide; but Howard Browman gently continued to prod me and since one of the objectives of the food for thought is to explain how we developed our careers, I opted for this path and he has been a wonderful mentor helping me write something very different from what I am used to writing. I also thank the many people who have helped me with my awkward thought process and prose, and I especially thank my family and my own students who have done such a wonderful job mentoring me! Food for Thought articles are essays in which the author provides their perspective on a research area, topic, or issue. They are intended to provide contributors with a forum through which to air their own views and experiences, with few of the constraints that govern standard research articles. This Food for Thought article is one in a series solicited from leading figures in the fisheries and aquatic sciences community. The objective is to offer lessons and insights from their careers in an accessible and pedagogical form from which the community, and particularly early career scientists, will benefit. The International Council for the Exploration of the Sea (ICES) and Oxford University Press are pleased to make these Food for Thought articles immediately available as free access documents References Able K. W. 2016 . Natural history: an approach whose time has come, passed, and needs to be resurrected . ICES Journal of Marine Science , 73 : 2150 – 2155 . Google Scholar Crossref Search ADS WorldCat Andrewartha H. G. , Birch L. C. 1954 . The Distribution and Abundance of Animals . University of Chicago Press, Chicago . 793 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Carson R. 1962 . Silent Spring . Houghton Mifflin, Boston. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Cousteau J.-Y. , Dumas F. 1953 . The Silent World . Harper and Brothers, New York . 266 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Dayton P. K. , Thrush S. F., Agardy M. T., Hofman R. J. 1995 . Environmental effects of marine fishing . Aquatic Conservation: Marine and Freshwater Ecosystems , 5 : 205 – 232 . Google Scholar Crossref Search ADS WorldCat Dayton P. K. , Robilliard G. A., Paine R. T., Dayton L. B. 1974 . Biological Accommodation in the Benthic Community at McMurdo Sound, Antarctica . Ecological Monographs , 44 : 105 – 128 . Google Scholar Crossref Search ADS WorldCat Dayton P. K. 1975 . Experimental studies of algal canopy interactions in a sea otter-dominated kelp community at Amchitka Island, Alaska . Fishery Bulletin , 73 : 230 – 237 . Google Scholar OpenURL Placeholder Text WorldCat Dayton P. K. 1985 . The structure and regulation of some South American kelp communities . Ecological Monographs , 55 : 447 – 468 . Google Scholar Crossref Search ADS WorldCat Dayton P. K. , Carleton J. H., Mackley A. G., Sammarco P. W. 1989 . Patterns of settlement, survival and growth of oysters across the Great Barrier Reef . Marine Ecology Progress Series , 54 : 75 – 90 . Google Scholar Crossref Search ADS WorldCat Dayton P. K. , Jarrell S. C., Kim S., Ed Parnell P., Thrush S. F., Hammerstrom K., Leichter J. J. 2019 . Benthic responses to an Antarctic regime shift: food particle size and recruitment biology . Ecological Applications , 29 : 1 – 20 . Google Scholar Crossref Search ADS WorldCat Dayton P. K. , Jarrell S. J., Kim S., Thrush S. F., Hammerstrom K., Slattery M., Parnell E. 2016 . Surprising episodic recruitment and growth of Antarctic sponges: implications for ecological resilience . Journal of Experimental Marine Biology and Ecology , 482 : 38 – 55 . Google Scholar Crossref Search ADS WorldCat Dearborn J. H. 1965 . Ecological and faunistic investigations of the marine benthos at McMurdo Sound, Antarctic. PhD dissertation, Stanford University, Stanford California. Ehrlich P. R. 1968 . The Population Bomb . Ballantine Books, New York . 201 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Friedlander A. M. , Ballesteros E., Bell T. W., Caselle J. E., Campagna C., Goodell W., Hüne M., et al. 2020 . Kelp forests at the end of the earth: 45 years later . PLoS One , 15 : e0229259 .https://doi.org/ 10.1371/journal.pone.0229259 Google Scholar Crossref Search ADS PubMed WorldCat Hastings J. R. , Turner R. M. 1965 . The Changing Mile . The University of Arizona Press, Tucson, AZ . 317 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Hirsch J. E. 2020 . Superconductivity, what the H? The emperor has no clothes . Physics and Society , 49 : 4 – 9 . Google Scholar OpenURL Placeholder Text WorldCat Hutchinson G. E. 1983 . Marginalia: what is science for? American Scientist , 71 : 639 – 644 . Google Scholar OpenURL Placeholder Text WorldCat Lack D. 1954 . The Natural Regulation of Animal Numbers . Oxford University Press, Oxford, England . 343 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Littlepage J. L. 1965 . Oceanographic investigations in McMurdo Sound, Antarctica . Antarctic Research Series , 5 : 1 – 37 . Google Scholar OpenURL Placeholder Text WorldCat McLean J. H. 1962 . Sublitteral ecology of kelp beds of the open coast area near Carmel, California Biology Bulletin , 122 : 95 – 114 . Google Scholar Crossref Search ADS WorldCat Myers R. A. , Hutchings J. A., Barrowman N. J. 1997 . Why do fish stocks collapse? The example of cod in Atlantic Canada . Ecological Applications , 7 : 91 – 106 . Google Scholar Crossref Search ADS WorldCat Myers R. A. , Worm B. 2003 . Rapid worldwide depletion of predatory fish communities . Nature , 423 : 280 – 283 . 10.1038/nature01610 . Google Scholar Crossref Search ADS PubMed WorldCat Odum E. P. 1953 . Fundamentals of Ecology . Saunders, Philadelphia . 383 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Paine R. T. 1969 . A note on trophic complexity and community stability . American Naturalist , 103 : 91 – 93 . Google Scholar Crossref Search ADS WorldCat Paine R. T. 1980 . Food webs: linkage, interaction strength and community infrastructure . Journal of Animal Ecology , 39 : 667 – 685 . Google Scholar OpenURL Placeholder Text WorldCat Paine R. T. 1994 . Marine rocky shores and community ecology: an experimentalist’s perspective. In Excellence in Ecology , 4th edn. Ed. by Kinne O.. Ecology Institute , Oldendorf/Luhr, Germany Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Parnell P. E. , Miller E. F., Cody C. E. L., Dayton P. K., Carter M. L., Stebbinsd T. D. 2010 . The response of giant kelp (Macrocystis pyrifera) in southern California to low-frequency climate forcing . Limnology and Oceanography , 55 : 2010 , 2686 – 2702 . Google Scholar Crossref Search ADS WorldCat Pauly C. , Christensen V., Dalsgaard J., Froese R., Torres F., 1998 . Fishing down marine food webs . Science , 279 : 860 – 863 . Google Scholar Crossref Search ADS PubMed WorldCat Platt J. R. 1964 . Strong inference . Science , 146 : 347 – 353 . Google Scholar Crossref Search ADS PubMed WorldCat Steinbeck J. , Ricketts E. F. 1941 . Sea of Cortez: A Leisurely Journal of Travel and Research, with a Scientific Appendix Comprising Materials for a Source Book on the Marine Animals of the Panamic Faunal Province . The Viking Press, New York . 598 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Tegner M. J. , Dayton P. K., Edwards P. B., Riser K. L. 1996 . Is there evidence for long-term climatic changes in southern California kelp forests? California Cooperative Oceanic Fisheries Investigations Report , 37 : 111 – 126 . Google Scholar OpenURL Placeholder Text WorldCat Tegner M. J. , Dayton P. K., Edwards P. B., Riser K. L. 1997 . Large-scale, low frequency oceanographic effects on kelp forest succession: a tale of two cohorts . Marine Ecology Progress Series , 146 : 117 – 134 . Google Scholar Crossref Search ADS WorldCat Vadas R. L. 1968 . The ecology of Agaraum and the kelp bed. PhD thesis, University of Washington, Seattle. 282 pp. © International Council for the Exploration of the Sea 2020. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. © International Council for the Exploration of the Sea 2020.

Waples, Robin S

doi: 10.1093/icesjms/fsaa061pmid: N/A

Abstract How much of your scientific career has unfolded as you planned, and how much has been shaped by blind luck? I suspect the latter has been more important than many of us realize, or at least acknowledge, but as Louis Pasteur said, “Chance favors only the prepared mind”—implying that we have at least some control over how random events affect our lives. Here, I discuss how large and small chance events have affected the trajectory of my scientific career. Introduction What if one could adapt Steven Jay Gould’s idea and play your life’s tape over again—what would be different, and what would be the same? It is tempting to think of the long arc of one’s career as being the result of foresight, persistence, and hard work. In reality, however, random events large and small shape our lives more than we think, or at least more than we generally acknowledge. Below I recount several instances where serendipity has intervened to affect my scientific career. What should I do when I grow up? I did not have a good answer to that question for a long time. Unlike Charles Darwin or E. O. Wilson, I was not a passionate naturalist as a kid. Growing up in Iowa, I spent a lot of time outdoors, but mostly to dig a tunnel, go swimming or ride my bike, have a snowball fight, find a mud puddle to wrestle in, or engage in politically incorrect activities involving cap pistols. This lack of a clear career trajectory lasted through college, where I majored in American Studies because it allowed me to take a smorgasbord of fascinating courses from people like Margaret Mead (who came up once a week from New York), Charles Reich (his Law School course evolved into The Greening of America), Vincent Scully (legendary lecturer and critic of American architecture), and Erich Segal (classics professor who wrote Love Story in his spare time). If I had been paying attention, I could have taken a course in something called “ecology” by G. Evelyn Hutchinson, who practically invented the field—but I was not interested in science at the time. After college, my first real job was at Punahou School in Honolulu, teaching English and coaching water polo. The players on the team were not much younger than me, and they knew all the best places on the island to explore—especially in and around the ocean. Had I stayed a few years longer at Punahou, a young Barry Obama might have shown up in my class. However, I soon moved to the outer islands so I could devote more time to my new passions: body surfing and skin diving. By 1974, I was living in Australia, where I spent as much time as possible under the waters of the Great Barrier Reef and evolved from hunting fish with a speargun to stalking them with a camera. My first publication was actually an underwater photograph that appeared in The Ocean World of Jacques Cousteau. A popular saying that emerged from Berkeley in the 1960s was “Don’t trust anyone over 30” (Bartleby.com, 1989). When I reached that pivotal age in 1977, I was back in the United States following a brother’s wedding and finding it difficult to ignore the WSIDWIGU question any longer. I considered going back to teaching, but demographics were unfavourable: the baby-boomer surge was over and teachers were being laid off. Plan B was to become a marine biologist, but that option was problematical because the only science course I had taken in college was Astronomy. Fortunately, I was still a Hawaiian resident, so I enrolled at the University of Hawaii and began 2 years of undergraduate science courses so I could be a credible applicant to graduate school. And here is where serendipity first intervened: my randomly assigned curriculum advisor was Jim Shaklee, who taught ichthyology and happened to be a wizard at using protein electrophoresis to study allozymes (variant forms of enzymes, distinguished based on differing sequences of amino acids). I took Jim’s excellent course and, short of money, asked about a summer job; he did not have a “job”, but I could do a volunteer project in his laboratory and he would teach me electrophoresis. (The financial problem was solved with another stroke of luck; my chemistry laboratory partner was leaving town and I inherited his lucrative, night-time job in Waikiki serving wine to sunburned tourists.) The project we settled on, suggested by Jack Randall at the Bishop Museum, was to figure out whether two forms of a shallow-water lizardfish (genus Synodus) represented one or two species. This was a perennial problem in systematics: do observed differences between morphotypes merely reflect natural levels of variation within a species? Or are the forms fundamentally different types of organism? Protein electrophoresis has clear potential to inform this type of problem: amino acids are coded for by sequences of DNA bases (the “genetic code”), so different allozymes can be inferred to reflect different genes. The idea of using a new genetic method to solve a puzzle that had stumped world-famous ichthyologists (Jordan and Evermann 1905; Gosline and Brock 1960) was exhilarating to a neophyte scientist. The lizardfish were relatively easy to collect, and soon I had several specimens of each morphotype. The procedure involved saturating wicks of filter paper with extracts from four tissues (muscle, liver, heart, eye), loading them onto gels made from potato starch, and subjecting them to electric current. Proteins with different amino-acid sequences migrated in different directions and/or at different rates, and at the end you could visualize where each sample had migrated to by bathing a slice of the gel in a solution that contained reactants for the enzyme and a linking dye. This created dark bands on the gel that magically appeared before your eyes as the reaction progressed. When bands on the first set of gels began to emerge, the result was unmistakable: two species!—the two morphotypes differed consistently at about half their genes! At that moment I had the answer to my WSIDWIGU question: I wanted to study the systematics and population genetics of fish. And that is largely what I have done for the last ∼40 years. But what would my scientific career be like if I had been assigned a different curriculum advisor at University of Hawaii? Even if I had remained interested in marine science, the focus of my research (and hence what I ended up working on) likely would have been quite different. Uncontrolled controls Chance interceded again soon after I started the lizardfish project. Jim Shaklee impressed upon me the importance of having a control on each gel that would produce bands of known mobility. For the controls I chose a common lizardfish in another genus, Saurida gracilis, which all authorities agreed was a single, polytypic species distributed widely throughout the Indo-Pacific. I collected Saurida from various habitats around Oahu, and each time I ran Synodus experiments I took a new Saurida specimen out of the freezer, extracted tissue samples, and loaded them on the same gels. This produced some puzzling results. When I did replicate samples of the same Synodus specimens on different days, the relative positions of the Synodus and control bands did not remain constant. After many frustrating days spent resampling numerous Synodus specimens failed to resolve the problem, for lack of a better idea I decided to examine the controls in more detail by loading multiple Saurida specimens on the same gels. This produced an astounding result: the S. gracilis “controls” represented not one, not two, but three distinct species, each characterized by fixed differences at ten or more genes! Once the various specimens could be sorted genetically into three groups, it was apparent that they had finely partitioned the near-shore marine environment: specimens in group A were all found in very shallow (<2 m) brackish or muddy water; those in group B occurred a little deeper (generally 3–10 m) on coral or nearby sandy patches; and specimens in group C were found in similar habitats to group B, but generally at depths of 10 m or more. Given this startling finding, I set aside the Synodus project to focus on Saurida. With the three groups of specimens unambiguously defined genetically, I found that what appeared to be continuous variation at several morphometric characters turned out to be mixtures of discrete or semi-discrete distributions. For example, in the overall collection of ∼70 Saurida individuals, the number of pelvic fin rays ranged from 11 to 15, with the type of bell-shaped distribution that often characterizes variation within a species (Figure 1a). It turns out, however, that most individuals from group A have 12 fin rays, most from group B have 13, and most from group C have 14 (Figure 1b). After defining the groups based on independent genetic characters, multivariate morphometric data could be used to classify new individuals (e.g. type specimens from museums) for which genetic data were not available. Using this approach, I was able to show in my first scientific paper (Waples, 1981) that group B represented the “true” S. gracilis, that specimens from group A belonged to a species (Saurida nebulosa), that long ago (mistakenly, it turns out) had been synonomized with S. gracilis, and that group C individuals were new to science and hence were given the name Saurida flamma, after the flame-coloured bands on their mouth. All of this only transpired as a chance consequence of deciding to use this common species as a control in a study designed for other purposes. Figure 1. Open in new tabDownload slide Top: distribution of pectoral fin ray counts for a collection of shallow-water lizardfishes (genus Saurida) from Hawaii, all reputed to be Saurida gracilis. Middle: after genetic analyses sorted the specimens into three groups (A, B, C), the overall distribution of pectoral fin rays was revealed to be a mixture of three semi-discrete distributions. Subsequent analyses revealed the valid scientific names for each group, as shown in the legend. Bottom: the new species, Saurida flamma (group C), named for the flame-coloured bands on its mouth. Photo copyright Keoki Stender, by permission. Figure 1. Open in new tabDownload slide Top: distribution of pectoral fin ray counts for a collection of shallow-water lizardfishes (genus Saurida) from Hawaii, all reputed to be Saurida gracilis. Middle: after genetic analyses sorted the specimens into three groups (A, B, C), the overall distribution of pectoral fin rays was revealed to be a mixture of three semi-discrete distributions. Subsequent analyses revealed the valid scientific names for each group, as shown in the legend. Bottom: the new species, Saurida flamma (group C), named for the flame-coloured bands on its mouth. Photo copyright Keoki Stender, by permission. Eventually I did return to the Synodus problem and teamed up with Jack Randall to revise the genus in Hawaii, including descriptions of four new species (Waples and Randall, 1988). Confronting your data Even under the best of circumstances biological data are messy, so luck as well as skill is usually involved when clear patterns emerge. Artefacts can creep into your data in so many ways that scepticism and careful scrutiny are needed at all steps of data collection and analysis. One small data problem I discovered by chance illustrates this pervasive issue. In 1986, I arrived in Seattle to work as a postdoc for the US National Marine Fisheries Service (NMFS; aka NOAA Fisheries) and soon started a genetic monitoring programme for Snake River Chinook salmon (Oncorhynchus tshawtscha) and steelhead (anadromous Oncorhynchus mykiss) that is still ongoing (Waples et al., 1993; Van Doornik et al., 2013). At that time, monitoring involved collecting samples for protein electrophoresis from young-of-the-year juveniles. For the smallest fish (<60 mm), it was difficult to get enough heart and eye to produce reliable results, often leading to missing data for some of the 30–40 variable gene loci. On allozyme gels, heterozygotes are often harder to score because their activity is spread across two or more bands and they can be easily missed with poor-quality samples. For a project focusing on Chinook salmon, I wanted to see whether the amount of missing data in an individual was correlated with its heterozygosity, which would indicate a potential bias. I did not find a significant heterozygosity-missing data correlation, but I did find an odd result. Most individuals had no missing data, some were missing data for 1–3 loci, and a few had as many as five or six missing data points, with the latter group largely explained by the failure of one tissue to produce viable results. Curiously, I also found a small group of individuals with missing data for 21 or 22 gene loci. What could cause such a result? It was not due to complete failure of experiments to work on a given day, as these odd individuals were sprinkled among other normal individuals on many gels assayed at different times. I pulled some of the odd specimens from the freezer and, after a closer examination, it was clear that they were steelhead, not Chinook salmon. The two species are generally easy to distinguish, but small specimens can be mistaken for each other during field collections. But steelhead and Chinook salmon have been separated for ∼10 million years and have substantial genetic differences, so how could this contamination not have been noticed before? A check with the laboratory staff—all of whom had several years of experience scoring salmon gels—clarified that the offending specimens had been noted, but the way the data were recorded did not reflect that. When species X was being analysed and one or more oddballs appeared on a gel, the laboratory staff would note that “aha, that is an allele from species Y”. At that point, the oddballs would be “zeroed out”, meaning that their data were recorded as missing—but only for the gene loci currently being assayed. There was no formal procedure to flag those individuals as imposters and systematically remove all their data. This meant that, for the substantial fraction of loci for which species X and species Y shared alleles, individuals of species Y would be scored as if they were species X. The consequence of this was that frequencies of common alleles shared by the two species would be inflated for species X, whereas frequencies of rare alleles at the same loci would be underestimated. As a result of this chance discovery, a more robust procedure was implemented to deal with inadvertent mixtures of species in field samples. In this case, the practical consequences of the errors were limited, as only a small fraction of the samples were steelhead rather than Chinook salmon and the effect on estimated allele frequencies was modest. However, this represents only one small example of more general issues about data quality that can have profound consequences. For example, a paper published in Proceedings of the National Academy of Sciences of the United States of America (Ottmann et al., 2016) claiming that sibling groups of larval rockfish (Sebastes sp.) travel together for many months was later retracted (see https://www.pnas.org/content/114/52/E11336) when it was discovered that the small groups of “siblings” were actually a different species of rockfish. Compared to differences between species, differences among the few specimens of the second species were so small that the analyses the authors performed concluded that they had to be siblings. They had not checked for the presence of multiple species in their samples, even though 60 species of Sebastes are found along the west coast of the United States. Irrepressible effects of Ne It is often said that effective population size (Ne) is one of the most important parameters in evolutionary biology, and I have been known to make similar statements myself. That might be true, but Ne is also insidious because it manifests itself in diverse and unexpected ways—as was made clear to me soon after I moved to Seattle. A major focus of our laboratory was the analysis of mixed-stock salmon fisheries using a form of genetic mixture analysis (Utter et al., 1987; Shaklee et al., 1999). I had become interested in a related problem, which was whether linkage disequilibrium (LD; non-random associations of alleles at different gene loci) could be used to detect the mixtures of salmon populations. It was known that samples that include individuals from more than one population generate mixture LD, with magnitude that depends on the mixture fraction and how large the genetic differences are among populations (Nei and Li, 1973). Following interbreeding, the LD signal decays over time but still is potentially detectable for several generations. I wanted to know what statistical power one might have to detect salmon mixtures using LD, given empirical data on genetic differences among Chinook salmon populations. For this effort, I recruited the help of Peter Smouse, who had done seminal work on mixture LD in indigenous tribes from South America (Smouse and Neel, 1977). We simulated many in silico mixtures of salmon populations, and because we explicitly modelled reproduction, we had to stipulate a population size. We used a Wright–Fisher random reproductive success model, modified to account for salmon age structure, and with a wide range (20-fold) of effective population sizes. As expected, we found reduced statistical power for weakly differentiated populations, longer time after the interbreeding event, and unequal mixture fractions. Unexpectedly, however, we also found that these patterns were often dwarfed by the Ne effect, with smaller effective sizes producing more LD and much higher statistical power (Waples and Smouse, 1990; Figure 2). By three generations of random mating following an admixture event, most of the remaining LD in the mixed population could be attributed to drift. Figure 2. Open in new tabDownload slide Power to detect mixtures of salmon populations based on linkage disequilibrium (LD). across all pairwise combinations of eight gene loci. Power is the percentage of tests of the null hypothesis (H0: LD = 0) that are rejected. Results are from computer simulations that randomly interbred equal numbers of individuals from two populations in generation 0. Δ is a measure of genetic differentiation between the populations, and sample size was N = 100 individuals. Power is shown as a function of the number of generations following the interbreeding event and the effective number of breeders each year in each simulated population (Nb). Reproduced from Waples and Smouse (1990). Figure 2. Open in new tabDownload slide Power to detect mixtures of salmon populations based on linkage disequilibrium (LD). across all pairwise combinations of eight gene loci. Power is the percentage of tests of the null hypothesis (H0: LD = 0) that are rejected. Results are from computer simulations that randomly interbred equal numbers of individuals from two populations in generation 0. Δ is a measure of genetic differentiation between the populations, and sample size was N = 100 individuals. Power is shown as a function of the number of generations following the interbreeding event and the effective number of breeders each year in each simulated population (Nb). Reproduced from Waples and Smouse (1990). This unexpected result alerted me to the powerful effects of Ne on population genetic data, a theme I have pursued in many subsequent studies. With a little detective work, I found a paper by Bill Hill (1981) that showed how one could estimate Ne based on the amount of LD in a sample and a paper that described a similar approach based on temporal changes in allele frequency (Nei and Tajima, 1981). At the time, it was thought that genetic methods for estimating Ne would only be useful for species (e.g. Drosophila) with populations too large to enumerate. However, the genetic signal these methods are sensitive to is proportional to 1/Ne, which means that the methods have more precision for small populations. I had ideas about how to refine these methods for application to species of conservation concern and was just starting to develop them (Waples, 1989; Waples and Teel, 1990). At this point, however, chance intervened once again to change my career trajectory, to such an extent that any further efforts to pursue the study of genetic estimators of Ne had to be deferred for over a decade. Endangered Species Act interludes In 1990, the lid was about to blow off the pressure cooker of salmon conservation and management in the US Pacific Northwest. A decade before, concerns about declining salmon populations were forestalled for a time by passage of the Northwest Power Act, which led to development of the Columbia River Basin Fish and Wildlife Program, at the time considered “the most ambitious and costly effort at biological restoration on the planet” (Lee and Lawrence, 1985, p 433). A major goal of the Fish and Wildlife Program was to double salmon and steelhead abundance within 10 years. Unimpressed by this prediction, the salmon populations themselves continued to decline, and in 1990, early drafts of a report (subsequently published as Nehlsen et al., 1991) documenting over 200 at-risk salmon stocks were circulating within the region. That year our agency, which has stewardship responsibility for marine and anadromous species under the US Endangered Species Act (ESA), received petitions to list several groups of Columbia River Basin salmon populations as threatened or endangered under the ESA. To that point I had paid little attention to the ESA and did not even realize that the Act affords legal protection to any entity that meets the ESA’s definition of “species”, which includes named subspecies and (for vertebrates) “distinct population segments” (DPSs). Grizzly bears, bald eagles, and alligators were listed as DPSs in the contiguous United States, even though they were more abundant elsewhere, and the ESA salmon petitions sought listings based on the DPS provision. But the term “DPS” does not have a clear biological meaning, and the ESA provides no guidance on how to identify DPSs. When NMFS policy staff asked our laboratory for scientific guidance on the validity of the ESA salmon petitions, my response was that someone needed to define what a DPS of salmon was. One thing I knew for sure: it was not my responsibility, as my job description said nothing about the ESA. The problem was, in 1990, nobody at our Center had anything related to the ESA in their job description, yet somebody had to take charge of the issue. How that someone became me hinged on another random event. The ability to list population-level units was provided for in the original (1973) implementation of the ESA, and the current DPS language dates from 1978 amendments. In 1990, most of the DPS listings (including those for the three iconic species mentioned above) had been carried out by the US Fish and Wildlife Service (USFWS), which has ESA responsibility for terrestrial species, but each DPS listing determination had been done on an ad hoc basis, with no formal policy guidance, so the record of past determinations did not allow one to predict with any certainty how the agencies might handle a new DPS evaluation in the future. This was particularly troublesome for salmon: each of the Pacific salmon species comprises many hundreds of separate populations, which potentially could be grouped into DPSs in a nearly infinite number of different ways. To address the lack of consistency in prior DPS determinations, and to deal with the Pandora’s Box of endangered species issues for Pacific salmon that had just been opened up, in June 1990, the USFWS and NMFS convened a workshop in Washington, DC. The goals were to develop (i) an overarching DPS policy that would apply to all species and (ii) consistent with provisions of the broader policy, more specialized guidance for the complex issues involving salmon. Attendees included population biologists and geneticists, policy staff, and lawyers from both agencies. Another geneticist from our center was invited to attend but had a conflict, so I was sent instead. Following the meeting, efforts by USFWS to develop a broad DPS policy faltered. However, the 1990 ESA salmon petitions had tight legal deadlines and our agency could not afford to wait to develop a framework for evaluating salmon DPSs. Because I had attended the Washington, DC, meeting and was working on salmon, I was fingered as a likely suspect to draft a scientific paper that would, it was hoped, form the basis for formal policy guidance by our agency. Lawyers at the DPS workshop provided some useful background information for context: (i) legislative discussions leading up to passage of the ESA made it clear a major goal was conservation of biodiversity; (ii) the ESA itself stipulates that listing determinations be scientifically based; and (iii) it was recognized that the ability to list populations could be abused (if, for example the squirrels in a city park were listed as a DPS because they were isolated from other squirrels by urbanization), so the agencies were directed to use the DPS provision sparingly. Early drafts emerging from USFWS following the workshop were unfocused and provided a laundry list of options, reflecting the range of views discussed at the meeting: a DPS might be a, or b, or c, or d, or and so on.… I did not see how this would provide any meaningful guidance to future users, nor did I see how it would resolve the “squirrels in a city park” issue. It seemed to me that what was needed was a simple, two-part test with the criteria joined by “and” rather than “or”. It was clear that a “distinct” population segment must involve substantial reproductive isolation, but by itself that is not sufficient, as city park squirrels might meet that test. The need for a second criterion becomes obvious if one thinks about one of the major goals of endangered species conservation—avoiding extinctions because they are irreversible. Extinctions are permanent because they represent loss of the genetic blueprint for making a specific type of organism. Therefore, to satisfy the second criterion, a DPS should represent a major component of genetic diversity within the species as a whole. Accordingly, I drafted a scientific document outlining these ideas, fleshed out with several practical considerations for application to salmon. I had no idea how these things worked within government agencies; I expected the draft to disappear somewhere in the beaurocracy and never be seen again. But the draft was received well locally and also at headquarters—and even the lawyers seemed to like it. After the paper was favourably peer reviewed, a draft ESA salmon policy based on the science paper was published (NMFS, 1991a) and this was used to guide responses to the 1990 salmon petitions. After public review and comment, both the science paper (Waples, 1991) and the salmon DPS policy (NMFS, 1991b) were finalized. Several years later, a joint interagency DPS policy was finally published (USFWS and NMFS, 1996), which employed a two-part test similar to that used to define salmon DPSs. This was just the start of my salmon-ESA involvement. I became head of a group of scientists charged with the decade-long task of developing the scientific basis for ESA listing determinations for all US West Coast species of Pacific salmon, as well as steelhead and anadromous cutthroat trout, Oncorhynchus clarkia. At the same time, we had to evaluate the likely consequences of various management/conservation actions, such as operation of dams and hatcheries, that could affect listed populations. In the early-2000s, we initiated formal ESA recovery planning for listed populations and formed a series of teams to develop science-based recovery goals consistent with long-term viability. These were all-consuming tasks that occupied ∼150% of my time. Eventually, although I approached the Event Horizon more than once, I was able to escape the powerful gravitational pull of the ESA—at least to the extent that I could focus on other things for a change. Parentage analysis without parents The most pleasant serendipitous outcome in my scientific career has been the opportunity to collaborate and publish with my son, Ryan, but the path that led to that result was far from linear. I did not try to steer my offspring’s interest towards (or away from) science. However, one summer, faced with the prospect of a bored teenager moping around the house, I brought home my copy of A Primer of Population Biology (Wilson and Bossert, 1971) and suggested that Ryan might want to look it over. He gave a non-committal grunt but later acknowledged that he did read the book and that it might even have played a small role in shifting his main interest from chemistry to biology, which he ended up majoring in college. Even during his undergraduate years, but especially after he graduated and spent several years claiming to be considering applying to graduate school, I tried to get Ryan to learn computer programming as an essential skill of a modern biologist. Like many parental suggestions, this one was routinely ignored until I repackaged it as an interesting problem and challenged him to find the answer through simulations. The problem arose from a family holiday tradition. On an agreed-upon day, we all met after breakfast to pick names out of a hat. We then dispersed, each to buy a gift for the randomly chosen family member, and reconvened at lunch to exchange gifts. Sometimes one of us drew our own name, so we had to redo the draw. The problem I posed to Ryan: figure out the probability that at least one person will draw their own name, and how that probability changes with the number of names in the hat, n (which varied depending on whether Ryan or his sister Jade had a significant other at the time). The probability of having to redraw is easy to work out by hand for small numbers (1/2 for n = 2; 2/3 for n = 3; 5/8 for n = 4), but this rapidly becomes very tedious for n > 5. At the time I programmed in several Stone-Age languages (Fortran, Pascal, Basic), but Ryan decided to teach himself Python, which was a fortuitous choice that facilitated his subsequent forays into bioinformatics. Before long, he had produced results: after some gyrations for small numbers of participants, the probability of having to redraw converges rapidly on a value a bit over 0.63 (Figure 3). That value seemed curious, but when I mentioned this exercise to my mathematician brother-in-law, he was excited: “This is the famous hat-check problem! All the gentlemen going to the theater check their hats and get a ticket with a number, but after the performance the attendant is nowhere to be found, so hats are passed out at random. The probability that at least one person gets their own hat converges on 1 − 1/e ≈ 0.6321.” Figure 3. Open in new tabDownload slide The gift-exchange (aka “hat-check”) problem. A hat contains the names of n participants, who must buy a gift for the person with the name they draw from the hat. A redraw is required if anyone draws their own name. What is the probability of a redraw, and how does it change with n? Filled circles are from numerical simulations; the dotted line shows the theoretical expectation that the probability converges on 1 − 1/e for large n. Figure 3. Open in new tabDownload slide The gift-exchange (aka “hat-check”) problem. A hat contains the names of n participants, who must buy a gift for the person with the name they draw from the hat. A redraw is required if anyone draws their own name. What is the probability of a redraw, and how does it change with n? Filled circles are from numerical simulations; the dotted line shows the theoretical expectation that the probability converges on 1 − 1/e for large n. Before long, Ryan’s new programming skills came in handy in relation to a topic that had attracted my attention, which was understanding the evolutionary responses by salmon to major anthropogenic changes to their environments (Waples et al., 2008, 2017). In the late-2000s, colleagues and I collaborated on a salmon and climate change project, a core feature of which was developing an individual-based model that allows for both evolution and phenotypic plasticity (Reed et al., 2010, 2011). This model included an option to have the amount of additive genetic variance in a population decline if Ne dropped ˂500—in accordance with the “50–500” rule, the later part of which holds that an effective size of ∼500 is needed to ensure that long-term loss of genetic variation by drift is balanced by the creation of new variation by mutation (Franklin, 1980). I wanted to test how this option was working in the model by tracking both Ne and additive genetic variance over time. The standard textbook formula for computing inbreeding effective size (Crow and Denniston, 1988) depends on three parameters: the number of potential parents (N) and the mean (⁠ k¯ ⁠) and variance (Vk) in number of offspring per parent: Ne=k¯N−2k¯−1+Vkk¯(1) The way our programme was coded, however, it was not easy to identify all potential parents in a given generation and count the number of offspring produced by each that survived to return as adults. However, it was easy to “ask” each offspring who its two parents were, and by integrating across all offspring one could calculate k¯ and Vk. But this method only provided information about parents that actually produced at least one offspring. What about the parents that produced no offspring? These null parents should be included in total N, but how many of these were there? The method I used to calculate the mean and variance of offspring number provided no information about this class of parents. To assess the effects of null parents on inbreeding Ne, I created offspring distributions in which some parents, by chance, produced zero offspring. I then calculated Ne using (1), both with and without the null parents. Results were surprising: there was no effect of null parents. Whether null parents were included or not affected all the key parameters (N, k- ⁠, and Vk), but they changed in such a way that Ne was unchanged. To explore this analytically, I took simple expressions for the mean and variance (⁠ k¯ = Σki/S and Vk = Σki2/S − k¯2) and inserted them into (1). After a little rearrangement, the formula for inbreeding Ne reduces to this simple expression (Waples and Waples, 2011): Ne=2S-2∑ki22S-1,(2) where ki is the number of offspring produced by the ith parent and S is the number of offspring that have been assigned to parents. Expressed this way, it is clear that inbreeding Ne does not depend on N; the only unknown in (2) is Σki2 = the sum of squares of offspring number. Null parents make no contribution to Σki2 and hence none to inbreeding Ne. This simple relationship does not hold for variance Ne, except in the special case where S = N. Although genetic methods to assign offspring to parents are now routinely applied to natural populations (Jones et al., 2010), analyses become complicated when only some of the potential parents can be sampled. Equation (2) is quite versatile in this respect, as it is not affected by either the number of parents or the number sampled. I enlisted Ryan’s help to develop an algorithm to infer the vector of parental contributions (the ki values), given a set of correctly specified sibling relationships. This allowed us to calculate Σki2 and hence Ne from (2) without sampling any parents at all—that is, by conducting parentage analysis without parents. Ryan was also able to show that, for a given set of inferred sibling relationships, the estimate of Ne obtained using (2) is the same as that produced by Wang’s (2009) sibship method (Ackerman et al., 2017). Equation (1) or similar versions had been in widespread use for over a half century, but I only stumbled on the simpler and quite useful (2) when it was not possible to obtain the data I wanted by conventional means. This exercise was enriched by the programming skills of Ryan, which trace their origins to curiosity about a problem related to holiday gift exchanges. Conclusion Sometimes Lady Luck grabs you by the throat and can direct your life for a decade or more; for me, the chance assignment of Jim Shaklee as my advisor and the fateful 1990 meeting about the ESA that I was not supposed to attend fall into that category. When opportunities like this arise, you should be prepared to step up and make the most of them. In baseball parlance, when Fortune hangs a curveball in your wheelhouse, jump on it! But sprinkled throughout a life are many more chance events that make only small ripples and are easy to miss if you are not paying attention. Several occurrences like this that have enriched my scientific career are described above. Although these events are difficult to categorize and hard to generalize about, in many cases they present initially as annoying problems (e.g. the poorly behaved controls on the Synodus gels; the cluster of individuals missing data for about half their gene loci; the powerful effects of genetic drift that complicated the intended analyses; the difficulty in getting computer code written by someone else to produce the specific output you want). Often there is a silver lining to these annoyances, if one only takes the time to look. In situations like this, one can hope to increase the chances of a serendipitous outcome by adopting the philosophy of Niels Bohr: “How wonderful that we have met with a paradox. Now we have some hope of making progress”. It is not reasonable to expect that you will be rewarded with insights as momentous as those of Bohr regarding Quantum Mechanics, but consistently adopting this perspective can lead to important contributions in the long run. This is particularly true in the analysis of empirical (or even simulated) data. All the time you can muster to poke, prod, and examine your data from every possible angle will often be repaid by the discovery of anomalies that would not have been noticed otherwise. At worst, you might identify a problem and improve the quality of your data. If you are lucky, you will discover something new that leads down a novel and interesting path. Although I could retire at any time, I am still active in research because I am still discovering new things and still learning from collaborations with (mostly) younger scientists—and who knows when serendipity might manifest itself again? Food for Thought articles are essays in which the author provides their perspective on a research area, topic, or issue. They are intended to provide contributors with a forum through which to air their own views and experiences, with few of the constraints that govern standard research articles. This Food for Thought article is one in a series solicited from leading figures in the fisheries and aquatic sciences community. The objective is to offer lessons and insights from their careers in an accessible and pedagogical form from which the community, and particularly early career scientists, will benefit. The International Council for the Exploration of the Sea (ICES) and Oxford University Press are pleased to make these Food for Thought articles immediately available as free access documents References Ackerman M. W. , Hand B. K., Waples R. K., Luikart G., Waples R. S., Steele C., Garner B. A. et al. 2017 . Effective number of breeders from sibship reconstruction: empirical evaluations using hatchery steelhead . Evolutionary Applications , 10 : 146 – 160 . Google Scholar Crossref Search ADS PubMed WorldCat Barlteby.com. 1989 . Jack Weinberg. Respectfully Quoted: A Dictionary of Quotations. https://www.bartleby.com/73/1828.html (last accessed 24 February 2019). Crow J. F. , Denniston C. 1988 . Inbreeding and variance effective population numbers . Evolution , 42 : 482 – 495 . Google Scholar Crossref Search ADS PubMed WorldCat Franklin I. R. 1980 . Evolutionary change in small populations. In Conservation Biology: An Evolutionary–Ecological Perspective , pp. 135 – 150 . Ed. by Soule ´ M. E., Wilcox B. A. Sinauer Associates, Sunderland, MA, USA. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Gosline W. A. , Brock V. E. 1960 . Handbook of Hawaiian Fishes . Univ. Hawaii Press , Honolulu . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Hill W. G. 1981 . Estimation of effective population size from data on linkage disequilibrium . Genetical Research , 38 : 209 – 216 . Google Scholar Crossref Search ADS WorldCat Jones A. G. , Small C. M., Paczolt K. A., Ratterman N. L. 2010 . A practical guide to methods of parentage analysis . Molecular Ecology Resources , 10 : 6 – 30 . Google Scholar Crossref Search ADS PubMed WorldCat Jordan D. S. , Evermann B. W. 1905 . The aquatic resources of the Hawaiian Islands. Part I. The shore fishes . Bulletin of the United States Fish Commission , 23 : 1 – 575 . Google Scholar OpenURL Placeholder Text WorldCat Lee K. N. , Lawrence J. 1985 . Adaptive management: learning from the Columbia River Basin Fish and Wildlife Program . Environmental Law , 16 : 431 . Google Scholar OpenURL Placeholder Text WorldCat Nehlsen W. , Williams J. E., Lichatowich J. A. 1991 . Pacific salmon at the crossroads: stocks at risk from California, Oregon, Idaho, and Washington . Fisheries , 16 : 4 – 21 . Google Scholar Crossref Search ADS WorldCat Nei, M. and Tajima, F. 1981. Genetic drift and estimation of effective population size. Genetics, 98 : 625 – 640 . Nei M. , Li W.-H. 1973 . Linkage disequilibrium in subdivided populations . Genetics , 75 : 213 – 219 . Google Scholar PubMed OpenURL Placeholder Text WorldCat NMFS. 1991 a. Federal Register , 56 : [13 March 1991]: 10542 . NMFS. 1991 b. Federal Register , 56 : [20 November 1991]: 58612 . Ottmann D. , Grorud-Colvert K., Sard N. M., Huntington B. E., Banks M. A., Sponaugle S. 2016 . Long-term aggregation of larval fish siblings during dispersal along an open coast . Proceedings of the National Academy of Sciences of the United States of America , 113 : 14067 – 14072 . Google Scholar Crossref Search ADS PubMed WorldCat Reed T. E. , Waples R. S., Schindler D. E., Hard J. J., Kinnison M. T. 2010 . Phenotypic plasticity and population viability: the importance of environmental predictability . Proceedings of the Royal Society of London, Series B , 277 : 3391 – 3400 . Google Scholar Crossref Search ADS WorldCat Reed T. E. , Schindler D. E., Hague M. J., Patterson D. A., Meir E., Waples R. S., Hinch S. G. 2011 . Time to evolve? Potential evolutionary responses of Fraser River sockeye salmon to climate change and effects on persistence . PLoS One , 6 : e20380 . Google Scholar Crossref Search ADS PubMed WorldCat Shaklee J. B. , Beacham T. D., Seeb L., White B. A. 1999 . Managing fisheries using genetic data: case studies from four species of Pacific salmon . Fisheries Research , 43 : 45 – 78 . Google Scholar Crossref Search ADS WorldCat Smouse P. E. , Neel J. V. 1977 . Multivariate analysis of gametic disequilibrium in the Yanomama . Genetics , 85 : 733 – 752 . Google Scholar PubMed OpenURL Placeholder Text WorldCat USFWS and NMFS. 1996 . Federal Register 61 [7 February 1996]:4722. Utter F. , Teel D., Milner G., McIsaac D. 1987 . Genetic estimates of stock compositions of 1983 chinook salmon, Oncorhynchus tshawytscha, harvests off the Washington coast and the Columbia River . Fishery Bulletin , 85 : 13 – 23 . Google Scholar OpenURL Placeholder Text WorldCat Van Doornik D. M. , Eddy D. L., Waples R. S., Boe S. J., Hoffnagle T., Berntson E. A., Moran P. 2013 . Genetic monitoring of threatened Chinook salmon populations: estimating introgression of non-native hatchery stocks and temporal genetic changes . North American Journal of Fisheries Management , 33 : 693 – 706 . Google Scholar Crossref Search ADS WorldCat Wang J. 2009 . A new method for estimating effective population sizes from a single sample of multilocus genotypes . Molecular Ecology , 18 : 2148 – 2164 . Google Scholar Crossref Search ADS PubMed WorldCat Waples R. S. 1981 . A biochemical and morphological review of the lizardfish genus Saurida in Hawaii, with the description of a new species . Pacific Science , 35 : 217 – 235 . Google Scholar OpenURL Placeholder Text WorldCat Waples R. S. 1989 . A generalized approach for estimating effective population size from temporal changes in allele frequency . Genetics , 121 : 379 – 391 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Waples R. S. 1991 . Pacific salmon, Oncorhynchus spp., and the definition of “species” under the Endangered Species Act . Marine Fisheries Review , 53 : 11 – 22 . Google Scholar OpenURL Placeholder Text WorldCat Waples R. S. , Elz A., Arnsberg B. D., Faulkner J. R., Hard J. J., Timmins-Schiffman E., Park L. K. 2017 . Human-mediated evolution in a threatened species? Juvenile life-history changes in Snake River salmon . Evolutionary Applications , 10 : 667 – 681 . Google Scholar Crossref Search ADS PubMed WorldCat Waples R. S. O. W. , Johnson P. B., Aebersold C. K., Shiflett D. M., VanDoornik D. J., Teel A. E., Cook, 1993 . A genetic monitoring and evaluation program for supplemented populations of salmon and steelhead in the Snake River Basin. Annual Report of Research , Bonneville Power Administration , Portland . 179 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Waples R. S. , Randall J. E. 1988 . A revision of the Hawaiian lizardfishes of the genus Synodus, with descriptions of four new species . Pacific Science , 42 : 178 – 213 . Google Scholar OpenURL Placeholder Text WorldCat Waples R. S. , Smouse P. E. 1990 . Gametic disequilibrium analysis as a means of identifying mixtures of salmon populations . American Fisheries Society Symposium , 7 : 439 – 458 . Google Scholar OpenURL Placeholder Text WorldCat Waples R. S. , Teel D. J. 1990 . Conservation genetics of Pacific salmon. I. Temporal changes in allele frequency . Conservation Biology , 4 : 144 – 156 . Google Scholar Crossref Search ADS WorldCat Waples R. S. , Waples R. K. 2011 . Inbreeding effective population size and parentage analysis without parents . Molecular Ecology Resources , 11 : 162 – 171 . Google Scholar Crossref Search ADS PubMed WorldCat Waples R. S. , Zabel R. W., Scheuerell M. D., Sanderson B. L. 2008 . Evolutionary responses by native species to major anthropogenic changes to their ecosystems: pacific salmon in the Columbia River hydropower system . Molecular Ecology , 17 : 84 – 96 . Google Scholar Crossref Search ADS PubMed WorldCat Wilson E. O. , Bossert W. H. 1971 . A Primer of Population Biology . Sinauer Associates , Sunderland, MA, USA . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Published by International Council for the Exploration of the Sea 2020. This work is written by a US Government employee and is in the public domain in the US. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) Published by International Council for the Exploration of the Sea 2020. This work is written by a US Government employee and is in the public domain in the US.

Hornborg,, Sara;Smith, Anthony D, M

doi: 10.1093/icesjms/fsaa077pmid: N/A

Abstract Global fisheries have for long been scrutinized in terms of ecosystem effects but only more recently for their greenhouse gas emissions. These emissions are dominated by fuel use on fishing vessels and the levels are often neglected side effects of resource overexploitation. Using a simple production model, Pella-Tomlinson, we illustrate how fuel efficiency (fuel use per unit of catch) varies with the level of exploitation and biomass depletion. For this model, fuel use per unit catch rises hyperbolically with fishing effort—it is relatively flat at low levels of effort but rises steeply as effort increases and biomass and catch decline. In light of these findings, the general fuel efficiency relationship with common fishery reference points on stock status is discussed, as well as other means of reducing fuel use and thus greenhouse gas emissions. We conclude that much may be gained by considering fuel efficiency in setting reference points for target stock biomass in fisheries and encourage further investigations. Introduction Global fisheries have for long been scrutinized in terms of ecosystem effects but only more recently for their fuel use [first global analysis by Tyedmers et al. (2005)] and associated greenhouse gas emissions (Parker et al., 2018). It has repeatedly been found that fuel use during fishing operations dominates both total energy use and these emissions associated with seafood products from capture fisheries, despite considerable international trade, and the level is determined by target stock status, species targeted, and gear used (Ziegler et al., 2016a). These factors are under management influence. Furthermore, recent analysis has shown that global emissions per landing volume have increased over time (Parker et al., 2018), attributed in part to increases in energy-intensive crustacean fisheries. These have repeatedly been shown to be more energy intensive compared to finfish fisheries (Parker and Tyedmers, 2015); in fact, even compared to all other food production systems (Pelletier et al., 2011). High levels of fuel use and emissions from the fisheries sector may not be the most important issues in global food production systems but are often neglected side effects of resource overexploitation. For example, the ratio of fuel energy input to edible protein energy output for fisheries at George’s Bank, Massachusetts, increased from 6:1 to over 36:1 between 1968 and 1988, associated with a period of severe resource depletion (Mitchell and Cleveland, 1993; Tyedmers, 2001). The energy intensity of current global fisheries may thus be seen as an effect of overexploitation—both indirectly, from depletion of traditional finfish stocks and ecosystem changes towards more invertebrate fisheries (Howarth et al., 2014), and directly, if effort reductions are not made at lower levels of stock abundance (e.g. Schau et al., 2009; Ziegler and Hornborg, 2014; Jafarzadeh et al., 2016). As long as prices are high for the catch, as for many invertebrates (Howarth et al., 2014), higher fuel costs are supported and may be masked and even sustained by fossil fuel subsidies (Ziegler and Hornborg, 2014). Parker et al.’s (2018) retrospective analysis used correlations of target species and gears to estimate greenhouse gas emissions over time, but correlations between emissions and stock status were not investigated in detail. Analyses of potential reduction in greenhouse gas emissions from the use of different reference points in management have in fact been scarce. Farmery et al. (2014) found potential for large theoretical improvements for rock lobster fisheries in Australia at different catch rates, in a country with very high fuel consumption per landing from targeting high volume of crustaceans. Svedäng and Hornborg (2015) quantified theoretical improvement potentials for Swedish cod fisheries in the Baltic Sea based on different fishing effort and selectivity. However, there has been no systematic evaluation of the potential savings and trade-offs associated with fishing at different reference points and levels of stock depletion. This study addresses that issue and calls for further investigation where data are available. The relationship between stock status and greenhouse gas emissions We are interested in how greenhouse gas emissions per unit of catch or product varies across different levels of exploitation and associated biomass, or depletion. Since combustion of fuels from fishing vessels is the dominating contribution to these emissions from fisheries, fuel use and levels of greenhouse gas emissions are linearly correlated (e.g. Parker et al., 2018 multiply fuel use with one single factor to quantify greenhouse gas emissions) and may therefore be interchangeably used in a model. We choose to use a Pella–Tomlinson model (Pella and Tomlinson, 1969) rather than a complex bioeconomic model with fleet dynamics to illustrate in a relatively simple way how fishery reference points may influence greenhouse gas emissions through different fuel use requirements per unit of catch. The Pella–Tomlinson model of fish stock dynamics under fishing takes the form: dB/dt=rB/p(1−(B/K)p)−C,(1) where B is the biomass of the stock, C is the catch, p is the shape parameter of the model, and r and K are stock parameters with r representing the intrinsic rate of increase and K representing the carrying capacity. When catch is zero, the stock will stabilize at the carrying capacity K, the unfished stock equilibrium. The shape parameter p determines where BMSY occurs as a proportion of K. Here, we use p = 0.19, resulting in BMSY at 0.4K, corresponding to the median level from Thorson et al. (2012). In the model, catch C is assumed to be related to fishing effort E and biomass B by the catch equation: C=qEBm,(2) where m is the power term on biomass and q is the “catchability” of the fishing gear, per unit of effort. This assumes that catch increases proportionally with both Bm and E. Note that (2) can be rearranged such that C/E = qBm,(3) implying that catch per unit effort (CPUE) is directly proportional to biomass B where m = 1. As effort E increases, equilibrium catch increases up to a maximum level referred to as maximum sustainable yield (MSY = rK (1/(p + 1))(1 + 1/p)) and then declines to zero at high levels of effort (E = r/(pq)). Turning to consideration of fuel use, let f represents fuel use per unit of effort, so that total fuel use F is given by F=fE.(4) Representing fuel use per unit of catch as G, this can be written as G=F/C=f/CPUE.(5) G is inversely related to biomass (and CPUE), has a minimum value of f/(qK) at B = K (E = 0), and increases as B declines below K under increasing levels of effort E. If we denote d = B/K as a measure of depletion of the stock (d = 1 is unfished and for d = 0 the stock is extirpated), and we denote the minimum possible value for G as G0, which as noted above occurs in the unfished state at B = K (and G0 = f/(qK)), then we can examine how G/G0 changes for various levels of d. Note that G0 as used above is only a theoretical construct (fuel use per unit catch at B = K where there is actually no equilibrium catch). In particular, it is not the same as the fuel use per unit of catch in the early stages of development of a fishery, where CPUE can be considerably higher than “equilibrium” CPUE, because the stock is actually being fished down, so some of the catch comes from reduction in biomass; there is a difference between equilibrium vs. transitional CPUE. The key point is that G/G0, which we denote here relative fuel use, rises hyperbolically with fishing effort. It is relatively flat at low levels of effort but rises steeply as effort increases above the level achieving MSY and biomass, catch rate and catch decline. Implications for fishery reference points Based on the relationship between stock depletion and fuel use per unit catch (or greenhouse gas emissions of the catch), Table 1 shows, for various levels of stock depletion how both relative emission level and equilibrium catch (relative to CMSY) vary across these levels of depletion and fishery reference points. The magnitude depends on model parameters, with m = 1 implies CPUE directly proportional to biomass whereas m = 0.7 includes hyperstability (average value based on Harley et al. (2001)). These results are specific to the assumed form of the modelled yield curve, which has MSY at 0.4K. Alternative fishery models can result in different positions for MSY relative to K, and detail of results would vary with other forms of the yield curve. The general nature of the trade-offs illustrated is however likely to hold for other values of MSY relative to K. We discuss below how results would vary with hyperstability in the relationship between catch rates and abundance. Table 1. Fuel use per unit of catch as a multiplier relative to the value when fishing at MSY, and catch relative to CMSY, at various levels of depletion d. Stock depletion d (1.0 = pristine stock) . Catch relative to CMSY . Fuel use per unit of catch relative to fishing at MSY at m = 1 . Fuel use per unit of catch relative to fishing at MSY at m = 0.7 . Examples of reference points/management objectives available . 1.0 0.00 0.40 0.53 No fishing 0.9 0.28 0.44 0.57 – 0.8 0.52 0.50 0.62 – 0.7 0.72 0.57 0.68 – 0.6 0.87 0.67 0.75 – 0.5 0.97 0.80 0.86 MEY 0.4 1.00 1.00 1.00 MSY 0.3 0.96 1.33 1.22 – 0.2 0.82 2.00 1.62 Limit 0.1 0.55 4.00 2.64 Hard limit/closure 0 0.00 ∞ ∞ – Stock depletion d (1.0 = pristine stock) . Catch relative to CMSY . Fuel use per unit of catch relative to fishing at MSY at m = 1 . Fuel use per unit of catch relative to fishing at MSY at m = 0.7 . Examples of reference points/management objectives available . 1.0 0.00 0.40 0.53 No fishing 0.9 0.28 0.44 0.57 – 0.8 0.52 0.50 0.62 – 0.7 0.72 0.57 0.68 – 0.6 0.87 0.67 0.75 – 0.5 0.97 0.80 0.86 MEY 0.4 1.00 1.00 1.00 MSY 0.3 0.96 1.33 1.22 – 0.2 0.82 2.00 1.62 Limit 0.1 0.55 4.00 2.64 Hard limit/closure 0 0.00 ∞ ∞ – Open in new tab Table 1. Fuel use per unit of catch as a multiplier relative to the value when fishing at MSY, and catch relative to CMSY, at various levels of depletion d. Stock depletion d (1.0 = pristine stock) . Catch relative to CMSY . Fuel use per unit of catch relative to fishing at MSY at m = 1 . Fuel use per unit of catch relative to fishing at MSY at m = 0.7 . Examples of reference points/management objectives available . 1.0 0.00 0.40 0.53 No fishing 0.9 0.28 0.44 0.57 – 0.8 0.52 0.50 0.62 – 0.7 0.72 0.57 0.68 – 0.6 0.87 0.67 0.75 – 0.5 0.97 0.80 0.86 MEY 0.4 1.00 1.00 1.00 MSY 0.3 0.96 1.33 1.22 – 0.2 0.82 2.00 1.62 Limit 0.1 0.55 4.00 2.64 Hard limit/closure 0 0.00 ∞ ∞ – Stock depletion d (1.0 = pristine stock) . Catch relative to CMSY . Fuel use per unit of catch relative to fishing at MSY at m = 1 . Fuel use per unit of catch relative to fishing at MSY at m = 0.7 . Examples of reference points/management objectives available . 1.0 0.00 0.40 0.53 No fishing 0.9 0.28 0.44 0.57 – 0.8 0.52 0.50 0.62 – 0.7 0.72 0.57 0.68 – 0.6 0.87 0.67 0.75 – 0.5 0.97 0.80 0.86 MEY 0.4 1.00 1.00 1.00 MSY 0.3 0.96 1.33 1.22 – 0.2 0.82 2.00 1.62 Limit 0.1 0.55 4.00 2.64 Hard limit/closure 0 0.00 ∞ ∞ – Open in new tab Table 1 illustrates that there is a trade-off to be considered between relative fuel use and associated emissions and fishery yield, influenced by fishery management decisions about stock reference points and risk of overfishing. d = 1 is a purely theoretical value representing an unfished baseline, corresponding to lowest possible emission levels per unit of catch—but at zero catch, the equivalent of a marine protected area closed for fishing. d = 0.4 corresponds, for this model, to the much-adopted MSY target for fisheries management (e.g. the Common Fisheries Policy in the European Union), which maximizes long-term catch but at the expense of higher fuel use per unit of catch the more the stock is being depleted compared to pristine state. d = 0.2 corresponds to a limit reference point widely used (e.g. in Australia) as a threshold to denote recruitment overfishing, and in many harvest strategies as a threshold below which fishing ceases (Rayns, 2007). Fuel use per unit of catch here is two times the level at MSY at m = 1. d = 0.1 is also used in some fishery jurisdictions (e.g. New Zealand, United States) as a “hard” limit below which a fishery will be closed, corresponding to a relative emission rate per unit of catch that is four times that at MSY at m = 1. Federally managed fisheries in Australia have an objective of maximum economic yield (MEY), with a default biomass target set at 20% above BMSY (Rayns, 2007). For BMSY at d = 0.4 in this model, BMEY would be at d = 0.48, close to d = 0.5 in the table. For a given stock and fleet, in considering Table 1, it is clear that levels of depletion below MSY make no sense in terms of either food security (maximizing catch) or emission levels, the latter rising alarmingly as stocks become increasingly depleted. Placing maximum priority on food security by maximizing catch at MSY (d = 0.4) implies however a necessary acceptance of higher emissions (and associated fuel costs) per unit of catch compared to, e.g. aiming for MEY; the latter relinquishes only 3% of maximum catch levels, while reducing emissions per unit of catch by about 20%. This may not be surprising as fuel consumption is an important variable cost of fishing operations, and MEY aims to achieve maximum economic efficiency. However, the improvement in emission levels is rather dramatic compared to the loss in production. Choosing even more precautionary management targets, such as d = 0.6, implies a 13% reduction in yield compared with a 33% improvement in emission levels, both relative to MSY. Clearly, there is no single “correct” answer in considering the trade-off between fuel use per unit of catch G and catch C in Table 1, but this analysis marks a starting point to consider such trade-offs. Variations in the stock status relationship with fuel efficiency There are several aspects of CPUE that may merit further explorations, such as hyperstability (CPUE reduces less quickly than biomass B, arising for some fisheries that target aggregating species) and hyperdepletion (CPUE falls more quickly that B). For example, hyperstability may arise through operational changes in the fishery such as choice of fishing ground, to maintain catch rates at lower abundance. In these circumstances, CPUE is not directly proportional to biomass. In a meta-analysis of 297 stocks, Harley et al. (2001) found a median value form of about 0.7, corresponding to mild-to-stronger hyperstability in CPUE vs. biomass. To see this in context, this would imply that a 50% decline in biomass would equate to only a 38% decline in CPUE. Changing m to 0.7 in the model resulted in less dramatic increase in fuel use per unit catch with degree of depletion (Table 1). For many northern hemisphere stocks that are managed on the basis of survey information about biomass, this would imply less concern about the relationship between fuel use per unit of catch and common reference points. However, many stocks are also managed without biomass data and make use of trends in CPUE to set harvest levels and determine reference points; the relationship between greenhouse gas emissions and reference points here is similar but with the added concern of higher risk of stock collapse if hyperstability is not recognized by management. However, if hyperstability at low stock abundance is achieved by changes to fishing operations, emissions per landing may still increase if fleets need to venture further away from port to fish (Hospido and Tyedmers, 2005), even if it has also been shown that distance to fishing ground may not be as important if catch rates are good (Ziegler et al., 2018). Interestingly, Parker et al. (2015) found that use of Fish Aggregation Devices (FADs) in purse seining for skipjack tuna was not associated with lower fuel use (and thus lower emissions) per unit landing. Considering the high risk of bycatch of vulnerable species in FADs (Filmalter et al., 2013), use of these may thus also be questioned from a greenhouse gas emission perspective. There are also other factors affecting variability in CPUE that managers and fishers cannot control. Between years, environmental drivers may cause changes in stock abundance (or availability) and may affect fuel use per unit catch even when effort is constant (Ramos et al., 2011). Fuel efficiency can also vary between years for the same stock without a clear driver (Avadí et al., 2018). Over time, if rough weather frequency increases with climate change, fuel usage may also increase since, e.g. strong winds requires higher fuel usage to maintain speed. Linkages between fleet behaviour, management, and emission levels Reducing f through operational efficiencies is most commonly seen in reality, e.g. when fuel prices go up (e.g. Schau et al., 2009;, Beare and Machiels, 2012). Since both fuel costs and landings are important for the profitability of fishing operations, fishers would aim to minimize the former while maximizing the latter—with different opportunities and motivating factors (Bastardie et al., 2013; Ziegler et al., 2018). Abernethy et al. (2010) showed that fishers responded to increasing fuel costs through fishing closer to shore or maximized value of landings; depending on the effect on catch rates, this may lead to either reduced or increased emission levels. There are also opportunities to improve fuel efficiency and associated emissions through improved engine, vessel, or gear design (Parente et al., 2008; Sala et al., 2011; Basurko et al., 2013), or to reduce emission levels through the use of alternative fuels (Jafarzadeh et al., 2017). Increasing q to decrease G could be achieved by utilizing a greater proportion of the catch in the form of either more by-catch species and/or sizes of target species or change in gear (e.g. Thrane, 2004); Ziegler and Valentinsson, 2008; Vázquez-Rowe et al., 2010; Hornborg et al., 2012). Supply chain interest in discarded species may, however, set a limit to interest in landing currently discarded species (van Putten et al., 2019). In fact, fuel use per unit of catch may be compromised by consumer preferences, where a fishery may choose to optimize size composition instead of volume of catch in a fishery (Hornborg et al., 2018). There are also other factors influencing q, such as selectivity, targeting practices, and skippers, which may result in different emission levels for the same stock and gear (Ruttan and Tyedmers, 2007; Ziegler et al., 2016b). Catchability is also likely to improve over time with technical advances, such as sonars, gear development, and satellite-based navigation systems. Hence, changes in f or q through fleet initiatives require new practices and investments in times when profit is deteriorating and may also be limited by management restrictions on, e.g. mesh size, quotas. The level of individual savings enabled, compared to fleet improvement through management measures to improve B or q through effort and/or gear restrictions, has to date not been explored. Future work in this field could utilize more complex age-structured or bioeconomic models to estimate MEY and MSY and investigate how greenhouse gas emission affects fisheries reference points. Including externalities in bioeconomic models is fairly standard (Pascoe et al., 2018). There is also an established way to include external costs (such as emissions) in social welfare functions by simply adding them to the private cost function. Fitting models with real data will also be an important task to establish the links between greenhouse gas emissions per unit catch and reference points. Implications for management More generally, G is influenced not only by the management targets for depletion considered above but also by other aspects of management introduced to meet other objectives in ecosystem approaches to fishing, such as reducing impacts on depleted stocks, habitats, and protected species. Sometimes, these measures may be a maladaptation—or at least raise questions on what trade-offs are being considered. As an example, demersal trawling is an energy-intensive fishing method (Parker and Tyedmers, 2015). Species-selective demersal trawling for Norway lobster Nephrops norvegicus to protect depleted gadoids increases fuel use and emissions per unit of catch since the gear is made less effective in terms of catch volume (Hornborg et al., 2012). This practice may be questioned when there is another viable and more low-emission fishing method that could be promoted instead—creeling—that in addition reduces bycatch and habitat impact (Ziegler and Valentinsson, 2008; Hornborg et al., 2017). Restrictions on use of low-emission gears may also be required to protect sensitive and charismatic species such as seabirds (Hornborg et al., 2018); differences in emission levels may then be seen as a trade-off based on different societal values. With other industries in society moving towards greener standards and regulations for greenhouse gas emissions, fishery resource managers should arguably also be involved in taking steps to minimize emissions where possible; minimizing greenhouse gas emissions may even become a legal requirement (Turrell, 2019). Given there is different scope for improvement at individual fisher and management level, industry initiatives related to reducing emissions (such as Austral Fisheries Pty Ltd, 2018) may be disadvantaged by the lack of consideration of the importance of choice of reference points in management. Fossil fuel prices are also likely to increase, and the potential effect of fleet behaviour is therefore also important to take into account in management to try to avoid unintended consequences from, e.g. changes in spatial distribution of fishing effort and effect on species and habitats. Improving current understanding of the various interactions between fleet behaviour, management measures, and greenhouse gas emissions may therefore allow for more proactive management in several ways. To this end Greenhouse gas emissions of seafood production from capture fisheries are arguably easier to manage than for many other protein production systems, whose emissions are more dominated by, e.g. land use changes and biogenic emissions (Steinfeld et al., 2006), rather than fossil energy use. Fuel use is also an important component of the economics of fishing. Considering the potential for improvements in both aspects from fishing healthy stocks illustrated here—also important to ecosystem function and long-term food security (e.g. Hilborn, 2010)—much may be gained by considering these aspects in setting reference points for target stock biomass or gear allocation in fisheries. Funding SH acknowledge funding from the European Union’s Horizon 2020 research and innovation programme (633692 SUSFANS—Metrics, Models and Foresight for European SUStainable Food and Nutrition Security) and the Swedish Research Council Formas (2016-00455). References Abernethy K. E. , Trebilcock P., Kebede B., Allison E. H., Dulvy N. K. 2010 . Fuelling the decline in UK fishing communities? ICES Journal of Marine Science , 67 : 1076 – 1085 . Google Scholar Crossref Search ADS WorldCat Austral Fisheries Pty Ltd. 2018 . https://www.australfisheries.com.au/sustainability (last accessed August 2019). Avadí A. , Adrien R., Aramayo V., Fréon P. 2018 . Environmental assessment of the Peruvian industrial hake fishery with LCA . The International Journal of Life Cycle Assessment , 23 : 1126 – 1115 . Google Scholar Crossref Search ADS WorldCat Bastardie F. , Nielsen J. R., Andersen B. S., Eigaard O. R. 2010 . Effects of fishing effort allocation scenarios on energy efficiency and profitability: an individual-based model applied to Danish fisheries . Fisheries Research , 106 : 501 – 516 . Google Scholar Crossref Search ADS WorldCat Bastardie F. , Nielsen J. R., Andersen B. S., Eigaard O. R. 2013 . Integrating individual trip planning in energy efficiency–building decision tree models for Danish fisheries . Fisheries Research , 143 : 119 – 130 . Google Scholar Crossref Search ADS WorldCat Basurko O. C. , Gabiña G., Uriondo Z. 2013 . Energy performance of fishing vessels and potential savings . Journal of Cleaner Production , 54 : 30 – 40 . Google Scholar Crossref Search ADS WorldCat Beare D. , Machiels M. 2012 . Beam trawlermen take feet off gas in response to oil price hikes . ICES Journal of Marine Science , 69 : 1064 – 1068 . Google Scholar Crossref Search ADS WorldCat Farmery A. , Gardner C., Green B. S., Jennings S. 2014 . Managing fisheries for environmental performance: the effects of marine resource decision-making on the footprint of seafood . Journal of Cleaner Production , 64 : 368 – 376 . Google Scholar Crossref Search ADS WorldCat Filmalter J. D. , Capello M., Deneubourg J. L., Cowley P. D., Dagorn L. 2013 . Looking behind the curtain: quantifying massive shark mortality in fish aggregating devices . Frontiers in Ecology and the Environment , 11 : 291 – 296 . Google Scholar Crossref Search ADS WorldCat Harley S. J. , Myers R. A., Dunn A. 2001 . Is catch-per-unit-effort proportional to abundance? Canadian Journal of Fisheries and Aquatic Sciences , 58 : 1760 – 1772 . Google Scholar Crossref Search ADS WorldCat Hilborn R. 2010 . Pretty Good Yield and exploited fishes . Marine Policy , 34 : 193 – 196 . Google Scholar Crossref Search ADS WorldCat Hornborg S. , Hobday A. J., Ziegler F., Smith A. D., Green B. S. 2018 . Shaping sustainability of seafood from capture fisheries integrating the perspectives of supply chain stakeholders through combining systems analysis tools . ICES Journal of Marine Science , 75 : 1965 – 1974 . Google Scholar Crossref Search ADS WorldCat Hornborg S. , Jonsson P., Sköld M., Ulmestrand M., Valentinsson D., Ritzau Eigaard O., Feekings J. et al. 2017 . New policies may call for new approaches: the case of the Swedish Norway lobster (Nephrops norvegicus) fisheries in the Kattegat and Skagerrak . ICES Journal of Marine Science , 74 : 134 – 145 . Google Scholar Crossref Search ADS WorldCat Hornborg S. , Nilsson P., Valentinsson D., Ziegler F. 2012 . Integrated environmental assessment of fisheries management: Swedish Nephrops trawl fisheries evaluated using a life cycle approach . Marine Policy , 36 : 1193 – 1201 . Google Scholar Crossref Search ADS WorldCat Hospido A. , Tyedmers P. 2005 . Life cycle environmental impacts of Spanish tuna fisheries . Fisheries Research , 76 : 174 – 186 . Google Scholar Crossref Search ADS WorldCat Howarth L. M. , Roberts C. M., Thurstan R. H., Stewart B. D. 2014 . The unintended consequences of simplifying the sea: making the case for complexity . Fish and Fisheries , 15 : 690 – 711 . Google Scholar Crossref Search ADS WorldCat Jafarzadeh S. , Ellingsen H., Aanondsen S. A. 2016 . Energy efficiency of Norwegian fisheries from 2003 to 2012 . Journal of Cleaner Production , 112 : 3616 – 3630 . Google Scholar Crossref Search ADS WorldCat Jafarzadeh S. , Paltrinieri N., Utne I. B., Ellingsen H. 2017 . LNG-fuelled fishing vessels: a systems engineering approach . Transportation Research Part D: Transport and Environment , 50 : 202 – 222 . Google Scholar Crossref Search ADS WorldCat Mitchell C. , Cleveland C. J. 1993 . Resource scarcity, energy use and environmental impact: A case study of the New Bedford, Massachusetts, USA, fisheries . Environmental Management , 17 : 305 – 317 . Google Scholar Crossref Search ADS WorldCat Parente J. , Fonseca P., Henriques V., Campos A. 2008 . Strategies for improving fuel efficiency in the Portuguese trawl fishery . Fisheries Research , 93 : 117 – 124 . Google Scholar Crossref Search ADS WorldCat Parker R. W. , Blanchard J. L., Gardner C., Green B. S., Hartmann K., Tyedmers P. H., Watson R. A. 2018 . Fuel use and greenhouse gas emissions of world fisheries . Nature Climate Change , 8 : 333 – 337 . Google Scholar Crossref Search ADS WorldCat Parker R. W. , Tyedmers P. H. 2015 . Fuel consumption of global fishing fleets: current understanding and knowledge gaps . Fish and Fisheries , 16 : 684 – 696 . Google Scholar Crossref Search ADS WorldCat Parker R. W. , Vázquez-Rowe I., Tyedmers P. H. 2015 . Fuel performance and carbon footprint of the global purse seine tuna fleet . Journal of Cleaner Production , 103 : 517 – 524 . Google Scholar Crossref Search ADS WorldCat Pascoe S. , Hutton T., Hoshino E. 2018 . Offsetting externalities in estimating MEY in multispecies fisheries . Ecological Economics , 146 : 304 – 311 . Google Scholar Crossref Search ADS WorldCat Pella J. J. , Tomlinson P. K. 1969 . A generalized stock production model . Inter-American Tropical Tuna Commission Bulletin, 13 : 416 – 497 OpenURL Placeholder Text WorldCat Pelletier N. , Audsley E., Brodt S., Garnett T., Henriksson P., Kendall A., Kramer K. J. et al. 2011 . Energy intensity of agriculture and food systems . Annual Review of Environment and Resources , 36 : 223 – 246 . Google Scholar Crossref Search ADS WorldCat Poos J. J. , Turenhout M. N., AE van Oostenbrugge H., Rijnsdorp A. D. 2013 . Adaptive response of beam trawl fishers to rising fuel cost . ICES Journal of Marine Science , 70 : 675 – 684 . Google Scholar Crossref Search ADS WorldCat Ramos S. , Vázquez-Rowe I., Artetxe I., Moreira M. T., Feijoo G., Zufía J. 2011 . Environmental assessment of the Atlantic mackerel (Scomber scombrus) season in the Basque Country. Increasing the timeline delimitation in fishery LCA studies . The International Journal of Life Cycle Assessment , 16 : 599 – 610 . Google Scholar Crossref Search ADS WorldCat Rayns N. 2007 . The Australian government’s harvest strategy policy . ICES Journal of Marine Science , 64 : 596 – 598 . Google Scholar Crossref Search ADS WorldCat Ruttan L. M. , Tyedmers P. H. 2007 . Skippers, spotters and seiners: analysis of the “skipper effect” in US menhaden (Brevoortia spp.) purse-seine fisheries . Fisheries Research , 83 : 73 – 80 . Google Scholar Crossref Search ADS WorldCat Sala A. , De Carlo F., Buglioni G., Lucchetti A. 2011 . Energy performance evaluation of fishing vessels by fuel mass flow measuring system . Ocean Engineering , 38 : 804 – 809 . Google Scholar Crossref Search ADS WorldCat Schau E. M. , Ellingsen H., Endal A., Aanondsen S. A. 2009 . Energy consumption in the Norwegian fisheries . Journal of Cleaner Production , 17 : 325 – 334 . Google Scholar Crossref Search ADS WorldCat Steinfeld H. , Gerber P., Wassenaar T. D., Castel V., Rosales M., Rosales M., de Haan C. 2006 . Livestock’s Long Shadow: Environmental Issues and Options . Food and Agriculture Org . http://www.fao.org/3/a0701e/a0701e.pdf (last accessed 23 April 2020). Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Svedäng H. , Hornborg S. 2015 . Waiting for a flourishing Baltic cod (Gadus morhua) fishery that never comes: old truths and new perspectives . ICES Journal of Marine Science , 72 : 2197 – 2208 . Google Scholar Crossref Search ADS WorldCat Thrane M. 2004 . Energy consumption in the Danish fishery: identification of key factors . Journal of Industrial Ecology , 8 : 223 – 239 . Google Scholar Crossref Search ADS WorldCat Thorson J. T. , Cope J. M., Branch T. A., Jensen O. P. 2012 . Spawning biomass reference points for exploited marine fishes, incorporating taxonomic and body size information . Canadian Journal of Fisheries and Aquatic Sciences , 69 : 1556 – 1568 . Google Scholar Crossref Search ADS WorldCat Turrell W. R. 2019 . Marine science within a net-zero emission statutory framework . ICES Journal of Marine Science , 76 : 1983 – 1993 . Google Scholar Crossref Search ADS WorldCat Tyedmers P. 2001 . Energy consumed by North Atlantic fisheries . Fisheries Impacts on North Atlantic Ecosystems: Catch, Effort, and National/Regional Data Sets , 9 : 12 – 34 . OpenURL Placeholder Text WorldCat Tyedmers P. H. , Watson R., Pauly D. 2005 . Fueling global fishing fleets . AMBIO: a Journal of the Human Environment , 34 : 635 – 638 . Google Scholar Crossref Search ADS WorldCat van Putten I. , Koopman M., Fleming A., Hobday A. J., Knuckey I., Zhou S. 2019 . Fresh eyes on an old issue: demand-side barriers to a discard problem . Fisheries Research , 209 : 14 – 23 . Google Scholar Crossref Search ADS WorldCat Vázquez-Rowe I. , Moreira M. T., Feijoo G. 2010 . Life cycle assessment of horse mackerel fisheries in Galicia (NW Spain): comparative analysis of two major fishing methods . Fisheries Research , 106 : 517 – 527 . Google Scholar Crossref Search ADS WorldCat Ziegler F. , Groen E. A., Hornborg S., Bokkers E. A., Karlsen K. M., de Boer I. J. 2018 . Assessing broad life cycle impacts of daily onboard decision-making, annual strategic planning, and fisheries management in a northeast Atlantic trawl fishery . The International Journal of Life Cycle Assessment , 23 : 1357 – 1367 . Google Scholar Crossref Search ADS WorldCat Ziegler F. , Hornborg S. 2014 . Stock size matters more than vessel size: the fuel efficiency of Swedish demersal trawl fisheries 2002–2010 . Marine Policy , 44 : 72 – 81 . Google Scholar Crossref Search ADS WorldCat Ziegler F. , Hornborg S., Green B. S., Eigaard O. R., Farmery A. K., Hammar L., Hartmann K. et al. 2016 a. Expanding the concept of sustainable seafood using Life Cycle Assessment . Fish and Fisheries , 17 : 1073 – 1093 . Google Scholar Crossref Search ADS WorldCat Ziegler F. , Hornborg S., Valentinsson D., Skontorp Hognes E., Søvik G., Ritzau Eigaard O. R. 2016 b. Same stock, different management: quantifying the sustainability of three shrimp fisheries in the Skagerrak from a product perspective . ICES Journal of Marine Science , 73 : 1806 – 1814 . Google Scholar Crossref Search ADS WorldCat Ziegler F. , Valentinsson D. 2008 . Environmental life cycle assessment of Norway lobster (Nephrops norvegicus) caught along the Swedish west coast by creels and conventional trawls—LCA methodology with case study . The International Journal of Life Cycle Assessment , 13 : 487 – 497 . Google Scholar Crossref Search ADS WorldCat © International Council for the Exploration of the Sea 2020. All rights reserved. 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Belcher, Anna; Cook, Kathryn; Bondyale-Juez, Daniel; Stowasser, Gabriele; Fielding, Sophie; Saunders, Ryan A; Mayor, Daniel J; Tarling, Geraint A

doi: 10.1093/icesjms/fsaa031pmid: N/A

Abstract Mesopelagic fish are an important component of marine ecosystems, and their contribution to marine biogeochemical cycles is becoming increasingly recognized. However, major uncertainties remain in the rates at which they remineralize organic matter. We present respiration rate estimates of mesopelagic fish from two oceanographically contrasting regions: the Scotia Sea and the Benguela Current. Respiration rates were estimated by measuring the enzyme activities of the electron transport system. Regression analysis of respiration with wet mass highlights regional and inter-specific differences. The mean respiration rates of all mesopelagic fish sampled were 593.6 and 354.9 µl O2 individual−1 h−1 in the Scotia Sea and Benguela Current, respectively. Global allometric models performed poorly in colder regions compared with our observations, underestimating respiratory flux in the Scotia Sea by 67–88%. This may reflect that most data used to fit such models are derived from temperate and subtropical regions. We recommend caution when applying globally derived allometric models to regional data, particularly in cold (<5°C) temperature environments where empirical data are limited. More mesopelagic fish respiration rate measurements are required, particularly in polar regions, to increase the accuracy with which we can assess their importance in marine biogeochemical cycles. Introduction The uptake of carbon dioxide (CO2) by the ocean through the biological carbon pump plays an important role in the partitioning of CO2 between the atmosphere and ocean (Kwon et al., 2009). Understanding and quantifying the processes controlling the efficiency of this pump are therefore vital for predictions of future climate. Carbon may be transported by passive sinking (the gravitational pump), physical mixing, or active transport through vertical migration of metazoans (Boyd et al., 2019). Previously, the gravitational pump was thought to be the dominant mechanism for transferring organic carbon to the deep sea. However, the importance of additional mechanisms, in particular the role of the migrating mesopelagic community, has been recognized more recently (Bianchi et al., 2013; Jónasdóttir et al., 2015; Anderson et al., 2019; Boyd et al., 2019; Pakhomov et al., 2019). Through diel (and seasonal) vertical migrations, organic carbon ingested in the epipelagic layer can be released in the mesopelagic layer through excretion, respiration, egestion and mortality (Longhurst et al., 1990; Zhang and Dam, 1997; Steinberg et al., 2000; Turner, 2002; Jónasdóttir et al., 2015; Steinberg and Landry, 2017). Acoustic estimates of mesopelagic fish biomass suggest that the global biomass of mesopelagic fish could be up to 15 gigatonnes (Gt) (Irigoien et al., 2014), dramatically higher than trawl-based estimates of 1 Gt (Gjøsaeter and Kawaguchi, 1980). Model estimates are wide ranging (1.8–15.9 Gt) with the most likely model scenarios suggesting 2–9 Gt (Anderson et al., 2019; Proud et al., 2019). As a result of their substantial global biomass, combined with large diel vertical migrations (Klevjer et al., 2016), mesopelagic fish can make a significant contribution to the biological carbon pump. Indeed, estimates of fish-mediated export (primarily estimates of respiratory flux, i.e. carbon respired at depth by the migrating community) can be up to 55% of the gravitational particulate organic carbon (POC) flux (Hidaka et al., 2001; Davison et al., 2013; Hudson et al., 2014; Ariza et al., 2015; Belcher et al., 2019). The fish-driven respiratory flux in the mesopelagic layer is, therefore, an important component of ocean carbon budgets, yet measurements of mesopelagic respiration are difficult. Obtaining live, heathy individuals from the mesopelagic through traditional net sampling techniques is not easy, resulting in a limited ability to incubate them under stress-free conditions and to obtain meaningful respiration rates. Previous studies (Hidaka et al., 2001; Hudson et al., 2014; Belcher et al., 2019) attempting to quantify fish-driven respiratory fluxes have made use of allometric relationships to estimate respiration from more easily measurable parameters such as depth, temperature and biomass. Ikeda (2016) compiled global incubation measurements of the respiration of pelagic marine fishes, while Belcher et al. (2019) focused on myctophid fishes that included both incubation experiments and respiration rate estimates from measurement of the enzyme activity of the electron transport system (ETS). However, only 36% and 47% of the collated data from Ikeda (2016) and Belcher et al. (2019), respectively, were obtained from fish whose habitat depth is deeper than 50 m, meaning that the mesopelagic fish community was poorly represented in the relationships they derived. Clarke and Johnston (1999) compiled data on metabolic rates for a wide range of teleost fish and examined the effects of body mass and temperature, although the depth at which fish were sampled was not included. The ETS method is currently the only method that can be used to estimate the respiration of fish sampled from the mesopelagic given our inability to catch and maintain them in a state where reliable respiration rates can be measured directly. For this method, nets are used to collect organisms from the mesopelagic layer and individuals are frozen immediately in liquid nitrogen. This allows measurement of the in situ enzyme activity as it is stable during the sampling process (Gómez et al., 1996). Oxygen consumption occurs at the end of the ETS through the reduction of oxygen to water. The enzyme activity of the ETS can therefore be used to measure the potential respiration based on the respiratory capacity of the ETS. Despite not being sensitive to the short-term net sampling stress and avoiding the need for incubation, the ETS method is a measure of the maximum potential respiration and, thus, the ratio between respiration and ETS activity (R:ETS) must be known. Considering the inherent difficulties of measurement, it is unsurprising that there is a lack of data on the respiration rates of mesopelagic fish (Ikeda, 2016). The empirically derived allometric relationships of Ikeda (2016) and Belcher et al. (2019) are global compilations of the available data, which are primarily from temperate and subtropical regions with little data from low temperature (<5°C) regions. As yet, there has not been sufficient data to validate these allometric methods in a robust way. In this study, we present estimates of respiration of mesopelagic fish derived from ETS activities. Our study focused on two oceanographically contrasting regions of the Atlantic, a low temperature, high productivity region of the Southern Ocean, the Scotia Sea, and a subtropical, high productivity region, the Benguela Current. We compare our ETS-derived respiration estimates with allometrically based estimates to assess their validity in these regions. Methods Data for this study were collected aboard the RRS Discovery during research cruises DY086 to the Scotia Sea in the Southern Ocean (12 November 2017–19 December 2017) and DY090 to the Benguela Current region offshore of Namibia (23 May 2018–28 June 2018), both in the Atlantic sector. During the Scotia Sea cruise, data were collected at station P3 (52.40°S, 40.06°W) to the northwest of South Georgia, and during the Benguela Current cruise, data were collected at station BN1 (18.00°S, 11.00°E). Vertical profiles of the water column at each site were made using a conductivity–temperature–depth unit (SBE 9 plus), which were used to determine in situ water temperatures and water mass properties. Net deployments and sample processing Mesopelagic fish samples were obtained using an opening and closing 25 m2 rectangular mid-water trawl net (RMT25, minimum 4 mm mesh; Baker et al., 1973; Piatkowski et al., 1994). This system consists of two nets, which can be opened and closed on command to sample specific depth horizons. Nets were deployed at 0–125, 125–250, 250–500 and 500–750 m in the Benguela Current, and at 0–250 and 250–500 m in the Scotia Sea. These deployment depths were based on the observed oceanographic structure at each study site. Nets were towed obliquely at two knots, for 20–50 min at each depth layer, and were repeated during the day and night. Once aboard, all fish caught were sorted, identified to the lowest taxonomic level possible and the composite wet mass (WM) measured to the nearest 0.01 g using a motion-compensated balance. Representative subsamples from each of the numerically dominant fish species were taken for subsequent measurement of ETS activity in the laboratory (see below). These samples were immediately flash frozen in liquid nitrogen before storage at −80°C. Respiration measurements—ETS activity Frozen whole fish samples were reweighed for WM in the laboratory, and a subsample was taken from each individual (and weighed) for ETS analysis. The ETS activity was measured kinetically following the method of Owens and King (1975) with modifications from Gómez et al. (1996). Each subsample was homogenized in a phosphate buffer using an electric homogenizer for 45–60 s. Homogenates were then centrifuged for 10 min at 4000 rpm at 0°C. 100 μL of subsample of the homogenate was mixed with 300 μl of reaction buffer (0.1 M, pH 8.5) containing substrates NADH and NADPH (saturating concentrations of 1.7 and 0.25 mM, respectively) in a 1-cm path length cuvette. All procedures were carried out on ice. 100 μL tetrazolium chloride dye, INT (2-p-iodophenyl-3-p-nitrophenyl monotetrazolium chloride, 4 mM) was added to each cuvette, and the reaction was measured continuously for 8 min at 490 nm in a Cary 60 UV–Vis spectrophotometer (Packard and Christensen, 2004). The temperature of the reaction was controlled at 11.5–12°C. In addition, for each sample, a blank assay was performed without the ETS substrates to account for the contribution of the non-enzymatic reduction of INT (Maldonado et al., 2012). Reagent blanks were also taken daily. In the kinetic assay, the INT replaces oxygen as the electron acceptor for the ETS, accepting two electrons where oxygen would accept four. The rate of formazan produced in the reduction of INT is therefore related to the oxygen consumption by a factor of two. The potential respiration rate (Φ, µmol O2 h−1) was calculated from the formazan production rate following Packard and Christensen (2004) using our measured INT extinction coefficient (at 490 nm) of 16.4 mM−1 cm−1. Respiration (R) at the experimental temperature of 12°C was then estimated using a conservative R:ETS ratio of 0.5 based on measurements made on fish (Ikeda, 1989) and values in the literature for marine zooplankton (Hernández-León and Gómez, 1996, see Discussion section for detail on range in R:ETS ratios). Total respiration rates per individual (RIND_12) at the experimental temperature of 12°C were calculated based on the wet weight of the subsample and total weight of the individual. In addition, we corrected respiration estimates to in situ temperature (ranging from 2 to 16°C) using the Arrhenius equation and an activation energy of 15 kcal mol−1 (Packard et al., 1975; Ariza et al., 2015; Hernández-León et al., 2019), giving RIND_INSITU for respiration rates per individual. These ETS-derived respiration estimates are a measure of routine respiration [i.e. between zero (resting) and maximum activity levels]. We define our ETS-derived respiration datasets as “Scotia Sea” and “Benguela”, for our respective study sites. Throughout the manuscript, where respiration rates refer to rates at 12°C, we used the subscript “12”, and where rates are for in situ temperatures, we use the subscript “INSITU”. Protein measurements As an additional determinant of biomass, the protein concentrations of the homogenates used for ETS analysis were estimated according to the method of Lowry et al. (1951), with modifications as described by Rutter (1967). Calibration curves were made from standard solutions of bovine serum albumin. Total protein per individual was estimated using the ratio of total WM to the WM of the subsample used for ETS analysis. Allometrically estimated respiration Respiration rates were also estimated based on the empirical relationships defined for pelagic marine fishes by Ikeda (2016) and for myctophid fishes by Belcher et al. (2019). These are based on data compilations of field studies, with Ikeda (2016) utilizing incubation-derived measurements (in the absence of food) of routine respiration rates and Belcher et al. (2019) utilizing both incubation- and ETS-derived measurements. We apply the regression from Ikeda (2016) (their model 1, herein referred to as Ikeda2016_INSITU) and the regression from Belcher et al. (2019) (herein referred to as Belcher2019_INSITU) to the WM of each individual fish measured at our Benguela and Scotia Sea study sites and compare these predicted respiration rates with our ETS-based respiration measurements to assess the applicability of these two regressions to our study regions. Ikeda2016_INSITU regression: Ln(RIND_INSITU)=19.491 + 0.885 × Ln(WM) −5.770 × 1000/temp−0.261 × Ln(depth),(1) where WM is the wet mass (mg) and temp is the temperature (K); depth is in metres. Belcher2019_INSITU regression: Ln(RIND_INSITU)=−1.315+0.734×Ln(WM)+0.085×T,(2) where WM is the wet mass (mg) and T is the temperature (°C). For comparison to our measurements, we adjust these respiration rate predictions to our experimental temperature of 12°C to give (RIND_12), using the Arrhenius equation and an activation energy of 15 kcal mol−1 (Packard et al., 1975; Ariza et al., 2015). Regression analysis Regression analyses of ETS-derived respiration data collected in our study were carried out using a regression fitting model for multiple predictors and a response, where data were continuous and no additive terms were allowed. Regression analysis was carried out for RIND_12 to assess the effect of WM at our experimental temperature of 12°C; Equations were of the form: Ln(RIND_12)=a0+a1×Ln(WM),(3) where a0 and a1 are regression coefficients and WM is the wet mass (mg). With only two large depth zones in the Scotia Sea (0–250 and 250–500 m), we lack sufficient depth resolution to include this variable appropriately in the model. WM and respiration data were transformed to the natural log prior to fitting the regression. Fitting was performed using the ordinary least squares method in Minitab (version 18.1). To compare the regressions of our study with that of Ikeda (2016) and Belcher et al. (2019), we recalculated the linear regressions (following the aforementioned method) from the respective datasets (adjusted to our 12°C experiment temperature) with WM only (i.e. not including depth or temperature) as a predictor. We refer to these recalculated regressions as Ikeda2016R_12 and Belcher2019R_12. We then investigated statistical differences between the mass scaling coefficients (for RIND_12) derived from our own datasets (Benguela and Scotia Sea) and the mass scaling coefficients derived from Ikeda2016R_12 and Belcher2019R_12 regressions. To do so, we calculated p-values for the interaction term of WM with dataset category (i.e. Ikeda2016R_12, Belcher2019R_12, Scotia Sea, Benguela) to see if the regression coefficients were significantly different. In addition, we performed regression analysis (as above) for all myctophid fish (termed “All Myctophid”) by collating together the ETS measurements we made on myctophid fish species in the Scotia Sea and Benguela, with Belcher2019 (both incubation and ETS data). This was done for both RIND_12 and RIND_INSITU data. Results ETS-derived respiration rates Temperatures in the upper 500 m in the Scotia Sea ranged from 0.7 to 3.5°C, compared with the Benguela region, where temperatures in the upper 750 m ranged from 4.7 to 20.6°C. In the Scotia Sea, respiration rates of Gymnoscopelus spp., Electrona antarctica and Krefftichthys anderssoni were measured, with WM ranging from 0.2 to 16.1 g. Respiration rates ranged from 45.8 to 1837.8 µl O2 individual−1 h−1 (0.139–7.447 µl O2 mg prot.−1 h−1). The mean respiration rate of mesopelagic fish measured in the Scotia Sea was 593.6 µl O2 individual−1 h−1. In the Benguela region, respiration rates of Bathylagus spp., Melamphidae spp., Gymnoscopelus spp., Cyclothone spp., Nemichthyidae spp., and Sternoptychidae spp. were measured, with WM ranging from 0.1 to 20.9 g. The mean respiration rate of all mesopelagic fish measured in the Benguela was 354.9 µl O2 individual−1 h−1 and ranged from 4.1 to 5245.8 µl O2 individual−1 h−1 (see Supplementary Material for full dataset). The relationship between respiration and mass is strongest for mass units of protein rather than WM (Figure 1). As WM is more easily measured, and to allow comparison with previous studies, we present our data in terms of units of WM (see Supplementary Figures S1–S3 for data presented in units of protein). Figure 1. Open in new tabDownload slide Respiration rates at in situ temperature (RIND_INSITU, μl O2 individual−1 h−1) of fish species measured at our study sites of the Benguela (circles) and the Scotia Sea (triangles) measured via ETS. Data are coloured by fish species. Respiration is plotted as a function of (A) the wet mass per individual (mg) or (B) protein mass per individual (mg). Note the natural logarithmic scale on both x and y axes. Respiration rates at 12°C (predicted for each individual fish from Benguela and Scotia Sea datasets) by Ikeda2016_12 range from 20.6 to 873.1 µl O2 individual−1 h−1 for the Scotia Sea data, with Belcher2019_12 predicting rates of between 44.9 and 1015.14 µl O2 individual−1 h−1. For the Benguela region, allometrically predicted respiration rates ranged between 5.8 and 680.4 µl O2 individual−1 h−1 based on Ikeda2016_12 and from 18.3 to 1170.3 µl O2 individual−1 h−1 based on Belcher2019_12. Comparing respiration rates predicted from Ikeda2016_12 and Belcher2019_12 reveals that the allometric regressions are more representative of the Benguela data (Figure 2B) than the Scotia Sea data (Figure 2A). Both the Ikeda2016_12 and Belcher2019_12 equations underestimate respiration compared with ETS estimates of respiration rates made by the present study in the Scotia Sea. Our measured respiration rates are up to 32 and 13 times higher than predicted values from Ikeda2016_12 and Belcher2019_12, respectively (medians are eight and four times greater, respectively). To assess the applicability of the Ikeda2016_12 and Belcher2019_12 regressions, we examine the residuals of the predicted respiration rates against our ETS-based respiration rate measurements (R_IND_12). Plotting these residuals against the WM (Figure 3) allows us to assess if the mass exponents of the Ikeda2016_12 and Belcher2019_12 regressions are appropriate for our datasets. The mean residuals between Scotia Sea respiration rates and predicted rates from Ikeda2016_12 and Belcher2019_12 were 1210.4 and 1047.7 µl O2 individual−1 h−1, respectively. The mean residuals calculated for Benguela respiration rates are 305.2 and 151.9 µl O2 individual−1 h−1 for Ikeda2016_12 and Belcher2019_12, respectively. All residuals highlight the greatest underestimations for fish of larger body mass. Figure 2. Open in new tabDownload slide Comparison of respiration rates at 12°C (RIND_12, μl O2 individual−1 h−1) calculated based on Ikeda2016_12 (white circles) and Belcher2019_12 (black circles) regressions and rates measured (via ETS) at our study sites (grey circles) of the (A) Scotia Sea and (B) Benguela Current. Respiration is plotted as a function of the wet mass per individual (mg). Note the natural logarithmic scale on both x and y axes. Figure 3. Open in new tabDownload slide Calculated residuals of ETS-measured respiration (RIND_12) in the Scotia Sea (blue circles) and Benguela (orange circles). Residuals are the difference between the measured data and the calculated respiration based on the regressions of (A) Ikeda2016_12 and (B) Belcher2019_12. Positive residuals indicate an underestimation by the regression. Linear regressions have been plotted through each data set (dashed lines). Regression analysis Multiple linear regression of our ETS-derived fish respiration rates (RIND_12) reveals that WM is a significant predictor for both the Scotia Sea and Benguela fish data (p < 0.05 in all cases; Table 1). The model fit for RIND_12 was better for the Benguela data, R2 of 46% compared with 36% for the Scotia Sea (Table 1). The mass exponent (a1) of the Scotia Sea is low, at 0.33, compared with the mass exponent of 0.75 for the Benguela dataset. Table 1. Regression coefficients and statistics derived from multiple regression of respiration rates RIND (µl O2 individual−1 h−1) on WM (mg). . a0 . a1 . a2 . a3 . n . R2 (%) . p-Values . Scotia Sea 4.359 (±0.556)* 0.334 (±0.066)* – – 47 36 Ln(WM) = 0.001 Benguela −0.675 (±0.610) 0.752 (± 0.079)* – – 109 46 Ln(WM) = <0.001 Belcher2019_INSITU −1.315 (±0.469)* 0.734 (±0.052)* 0.085 (±0.011)* – 74 77 T = <0.001 Ln(WM) = <0.001 Belcher2019R_12 a −0.469 (±0.185)* 0.760 (±0.030)* – – 74 90 Ln(WM) = <0.001 All Myctophid_INSITU −1.579 (±0.212)* 0.524 (±0.029)* – – 140 70 Ln(WM) = <0.001 All Myctophid_12 −0.877 (±0.258)* 0.891 (±0.036)* – – 140 82 Ln(WM) = <0.001 Ikeda2016_INSITU 19.491 (±2.491)* 0.885 (±0.021)* −5.770 (±0.752)* −0.261 (±0.032)* 102 95 All <0.001 Ikeda2016R_12 a −1.133 (±0.202)* 0.832 (±0.026)* – – 102 91 Ln(WM) = <0.001 Clarke and Johnston 1999b −5.43 0.80 (±0.13) – – 138 – – . a0 . a1 . a2 . a3 . n . R2 (%) . p-Values . Scotia Sea 4.359 (±0.556)* 0.334 (±0.066)* – – 47 36 Ln(WM) = 0.001 Benguela −0.675 (±0.610) 0.752 (± 0.079)* – – 109 46 Ln(WM) = <0.001 Belcher2019_INSITU −1.315 (±0.469)* 0.734 (±0.052)* 0.085 (±0.011)* – 74 77 T = <0.001 Ln(WM) = <0.001 Belcher2019R_12 a −0.469 (±0.185)* 0.760 (±0.030)* – – 74 90 Ln(WM) = <0.001 All Myctophid_INSITU −1.579 (±0.212)* 0.524 (±0.029)* – – 140 70 Ln(WM) = <0.001 All Myctophid_12 −0.877 (±0.258)* 0.891 (±0.036)* – – 140 82 Ln(WM) = <0.001 Ikeda2016_INSITU 19.491 (±2.491)* 0.885 (±0.021)* −5.770 (±0.752)* −0.261 (±0.032)* 102 95 All <0.001 Ikeda2016R_12 a −1.133 (±0.202)* 0.832 (±0.026)* – – 102 91 Ln(WM) = <0.001 Clarke and Johnston 1999b −5.43 0.80 (±0.13) – – 138 – – The regression models of the Benguela and Scotia Sea are of the form: Ln(RIND_12) = a0 + a1 × Ln(WM), and based on respiration data at the experimental temperature of 12°C. We include literature data, Ikeda2016_INSITU, Belcher2019_INSITU, and Clarke and Johnston (1999) for comparison (in italics), based on data at in situ temperatures. The Ikeda2016 regression is of the form: Ln(RIND_INSITU) = a0 + a1 × Ln(WM) + a2 × 1000/temp + a3 × Ln(depth), note that temperature here is represented in Kelvin. The Belcher2019 model is of the form: Ln(RIND_INSITU) = a0 + a1 × Ln(WM) + a2 × T. In addition, we include the recalculated regressions, Ikeda2016R_12 and Belcher2019R_12, with only wet mass as a predictor. The “All Myctophid” category, combines data from fishes belonging to the order Myctophiformes from the Scotia Sea, Benguela, and Belcher2019 datasets. a Regressions recalculated from routine respiration data from Ikeda 2016 (provided by T. Ikeda) and Belcher et al. (2019). Respiration data were adjusted to 12°C (see Methods section). b Respiration in mmol O2 individual−1 h−1, mass in g. * p-Value < 0.05. Open in new tab Table 1. Regression coefficients and statistics derived from multiple regression of respiration rates RIND (µl O2 individual−1 h−1) on WM (mg). . a0 . a1 . a2 . a3 . n . R2 (%) . p-Values . Scotia Sea 4.359 (±0.556)* 0.334 (±0.066)* – – 47 36 Ln(WM) = 0.001 Benguela −0.675 (±0.610) 0.752 (± 0.079)* – – 109 46 Ln(WM) = <0.001 Belcher2019_INSITU −1.315 (±0.469)* 0.734 (±0.052)* 0.085 (±0.011)* – 74 77 T = <0.001 Ln(WM) = <0.001 Belcher2019R_12 a −0.469 (±0.185)* 0.760 (±0.030)* – – 74 90 Ln(WM) = <0.001 All Myctophid_INSITU −1.579 (±0.212)* 0.524 (±0.029)* – – 140 70 Ln(WM) = <0.001 All Myctophid_12 −0.877 (±0.258)* 0.891 (±0.036)* – – 140 82 Ln(WM) = <0.001 Ikeda2016_INSITU 19.491 (±2.491)* 0.885 (±0.021)* −5.770 (±0.752)* −0.261 (±0.032)* 102 95 All <0.001 Ikeda2016R_12 a −1.133 (±0.202)* 0.832 (±0.026)* – – 102 91 Ln(WM) = <0.001 Clarke and Johnston 1999b −5.43 0.80 (±0.13) – – 138 – – . a0 . a1 . a2 . a3 . n . R2 (%) . p-Values . Scotia Sea 4.359 (±0.556)* 0.334 (±0.066)* – – 47 36 Ln(WM) = 0.001 Benguela −0.675 (±0.610) 0.752 (± 0.079)* – – 109 46 Ln(WM) = <0.001 Belcher2019_INSITU −1.315 (±0.469)* 0.734 (±0.052)* 0.085 (±0.011)* – 74 77 T = <0.001 Ln(WM) = <0.001 Belcher2019R_12 a −0.469 (±0.185)* 0.760 (±0.030)* – – 74 90 Ln(WM) = <0.001 All Myctophid_INSITU −1.579 (±0.212)* 0.524 (±0.029)* – – 140 70 Ln(WM) = <0.001 All Myctophid_12 −0.877 (±0.258)* 0.891 (±0.036)* – – 140 82 Ln(WM) = <0.001 Ikeda2016_INSITU 19.491 (±2.491)* 0.885 (±0.021)* −5.770 (±0.752)* −0.261 (±0.032)* 102 95 All <0.001 Ikeda2016R_12 a −1.133 (±0.202)* 0.832 (±0.026)* – – 102 91 Ln(WM) = <0.001 Clarke and Johnston 1999b −5.43 0.80 (±0.13) – – 138 – – The regression models of the Benguela and Scotia Sea are of the form: Ln(RIND_12) = a0 + a1 × Ln(WM), and based on respiration data at the experimental temperature of 12°C. We include literature data, Ikeda2016_INSITU, Belcher2019_INSITU, and Clarke and Johnston (1999) for comparison (in italics), based on data at in situ temperatures. The Ikeda2016 regression is of the form: Ln(RIND_INSITU) = a0 + a1 × Ln(WM) + a2 × 1000/temp + a3 × Ln(depth), note that temperature here is represented in Kelvin. The Belcher2019 model is of the form: Ln(RIND_INSITU) = a0 + a1 × Ln(WM) + a2 × T. In addition, we include the recalculated regressions, Ikeda2016R_12 and Belcher2019R_12, with only wet mass as a predictor. The “All Myctophid” category, combines data from fishes belonging to the order Myctophiformes from the Scotia Sea, Benguela, and Belcher2019 datasets. a Regressions recalculated from routine respiration data from Ikeda 2016 (provided by T. Ikeda) and Belcher et al. (2019). Respiration data were adjusted to 12°C (see Methods section). b Respiration in mmol O2 individual−1 h−1, mass in g. * p-Value < 0.05. Open in new tab The mass scaling coefficients (a1) of the recalculated regressions Ikeda2016R_12 (0.83) and Belcher2019R_12 (0.76) were significantly different (p < 0.001) from the Scotia Sea mass scaling coefficient (0.33, p < 0.001) for RIND_12. In contrast, estimates of the mass scaling coefficients of Ikeda2016R_12 and Belcher2019R_12 did not differ significantly from the Benguela mass scaling coefficient (0.75, p = 0.28 and p = 0.93, respectively). When combining all myctophid data [Myctophidae from this study and from Belcher et al. (2019)], we calculate a mass exponent of 0.89 and an R2 of 82% for RIND_12 , and a mass exponent of 0.52 and an R2 of 70% for RIND_INSITU (Figure 4). Figure 4. Open in new tabDownload slide Compilation of respiration rates of only fishes belonging to the order Myctophiformes measured in this study (Benguela: orange circles, and Scotia Sea: blue circles) with the myctophid compilation of Belcher et al. (2019) (grey). (A) Respiration rates at in situ temperatures (RIND_INSITU) and (B) respiration rates at 12°C (RIND_12). The method of respiration rate measurement is defined by filled (ETS activity) or unfilled (incubation experiment) symbols. In addition, we highlight the literature data of Belcher et al. (2019) that represent incubation studies in Antarctic waters with grey open triangles. The regression fit of these data is shown by a black line with confidence intervals (0.95) in grey shading. Discussion Methodological considerations Our results highlight that while the regressions of Ikeda2016_12 and Belcher2019_12 are adequate at predicting the respiration rates of fishes from the Benguela study site (Figure 2B), both regression models substantially underestimate the respiration rates of fishes in the Scotia Sea when compared with ETS estimates of respiration (Figure 2A). As several different methods have been used in the various literature data compilations, we must first examine possible methodological differences that may contribute to the underestimation of respiration in the Scotia Sea by the regressions of Ikeda2016_12 and Belcher2019_12. Whereas Ikeda (2016) compile respiration rates derived from incubation experiments (by incubating net-caught fish), the Belcher2019_INSITU regression is based on both ETS- and incubation-derived data [Figure 1 in erratum to Belcher et al. (2019)]. A key difference between these two methods is the feeding state of the animals. The incubated fish were not fed, but the fish sampled for respiration via ETS are in their natural feeding state and thus gut fullness is variable. As there is an increase in energy expenditure during digestion, starved animals will have lower respiration rates than those that have just fed. Therefore, ETS-derived respiration rates could be higher than the respiration rates of starved animals, since ETS activity is less sensitive to the short-term effect of starvation (Ikeda and Skjoldal, 1980; Packard et al., 1996), and thus our ETS-derived rates likely reflect the rates of fed animals. To adjust the predictions made with the Ikeda2016_12 equation to represent fed animals, we can estimate the extra energy required for respiration due to the action of feeding. Applying a specific dynamic action (SDA; the energy expended on ingestion, digestion, absorption and assimilation of food) of 2.36 (Secor, 2009) brings the predictions of the Ikeda2016_12 regression closer to our measurements, but predictions are still up to 14 times too low. Sensitivity analyses A number of assumptions were made in the estimation of respiration from ETS activity. We conduct here a sensitivity analysis to assess what changes to these assumptions would be required to make our ETS-derived data match the predictions of Ikeda2016_12. We then consider whether such changes to our assumptions are feasible given the present knowledge on the biology and physiology of these organisms: (i) R:ETS ratio: ETS is a measure of the potential respiration and, thus, it is possible that the conservative R:ETS ratio of 0.5 used to convert to respiration was not appropriate for the Scotia Sea data. The only studies measuring the respiration of mesopelagic fish via ETS (Ikeda, 1996; Ariza et al., 2015; Hernández-León et al., 2019) also use the conservative R:ETS ratio of 0.5, based on the typical range of values for zooplankton of 0.5–1 from Hernández-León and Gómez (1996) and fish (Ikeda, 1989). Hernández-León and Gómez (1996) investigated the R:ETS ratio in marine zooplankton, with most of their data falling between 0.4 and 0.6. However, there was variability around this, agreeing with the range of values measured by previous studies (0.16–2.34; Hernández-León and Gómez, 1996 and references within). Due to the difficulty in measuring the R:ETS ratio for mesopelagic fish, Ikeda (1989) incubated gobies and pomacentrids (sampled from a salt pond in Australia and not fed during the incubation) to estimate an R:ETS ratio of 0.62 and applied this to ETS activities of myctophid fishes sampled from surface waters. In addition, Schalk (1988) noted an R:ETS ratio of 0.16 measured in Pomatoschistus species in their own unpublished data. Based on the model of Packard et al. (1996), Osma et al. (2016) predicted the in vivo respiration rate of mysids from the ETS activity based on bisubstrate kinetics and measurements of kinetic constants and concentrations of the substrates NADH and NADPH. This model better takes into account the nutritional state of the organism compared with the use of a fixed value of the R:ETS ratio and is a promising alternative to incubating live animals to determine the R:ETS ratio. However, as yet, Osma et al. (2016) still recommend calibration of the predicted in vivo respiration rate with measured respiration rates. We can calculate the R:ETS ratio required to bring the Scotia Sea estimates in line with the predictions of Ikeda2016_12 by assuming that the respiration predicted by the Ikeda regression is correct and examining the ratio between this and our measured ETS activity. This results in a mean R:ETS ratio of 0.14 (median 0.09), which is at the very low end of observations in the literature (Hernández-León and Gómez, 1996). For the Benguela dataset, the mean calculated R:ETS ratio is 0.54 (median 0.30) highlighting the better agreement of Ikeda2016_12 with our ETS-derived respiration based on an R:ETS ratio of 0.5. If we must apply very different R:ETS ratios to the Benguela and Scotia Sea samples sets, it implies that environmental conditions must have a strong influence on this ratio, which no study has yet demonstrated. (ii) Temperature correction: A major difference between the Benguela and Scotia Sea regions is the temperature range experienced by fish living in the mesopelagic (0.7–3.5°C in upper 500 m of Scotia Sea compared with 4.7–20.6°C in the upper 750 m of the Benguela). All ETS assays were carried out at a laboratory temperature of 11.5–12°C, and thus, the temperature correction is larger for the Scotia Sea data. Based on the available literature, we applied the Arrhenius equation and an activation energy (Ea) of 15 kcal mol−1 to convert our measurements to in situ temperatures and to adjust the data of Ikeda (2016) and Belcher et al. (2019) to our experiment temperature of 12°C (RIND_12). This has been used for micronekton (Ariza et al., 2015; Hernández-León et al., 2019) but is originally based on the mean of values measured on zooplankton (Packard et al., 1975), which may not be ideal for mesopelagic fish. The Ea may also change with environmental condition depending on the ability of enzymes to function at different temperature ranges (Simcic and Brancelj, 2004). However, to reduce our Scotia Sea respiration estimates to match the values predicted by the Ikeda2016_12 regression, we would require an Ea of ∼40 kcal mol−1 (Q10 ∼ 12.5 for a temperature range of 2–18°C) which is not realistic (Supplementary Figure S3). If we apply a more realistic Ea of 20 kcal mol−1 [based on the range observed by Packard et al. (1975) of 11.7–21.9 kcal mol−1, Q10 ∼ 3.5 for a temperature range of 2–18°C] and also apply an SDA factor of 2.36 to the Ikeda predictions, we find better agreement between the predictions of the Ikeda2016_12 regression and our ETS measurements in the Scotia Sea (calculated median R:ETS ratio of 0.46 assuming the predicted respiration from Ikeda2016_12 is correct). However, these adjustments would result in a median R:ETS ratio of 0.85 (mean 1.5) for the Benguela dataset, which is unlikely. In addition, although these methodological adjustments improve the general overall agreement, there is still disagreement on an individual fish basis (the range in calculated R:ETS for Scotia Sea is 0.05–2.35), highlighting the high degree of individual variability in metabolic rate for a given body mass and temperature. Our sensitivity analysis suggests that, to bring the Ikeda2016_12 predictions in line with our observations, the necessary changes to the aforementioned parameters would be unrealistic given our present understanding. Although methodological factors may account for some of the differences between the regression-based predictions and our ETS-derived measurements, our data still suggest that there are regional differences in the scaling of mass with the respiration of mesopelagic fish. Mesopelagic fish respiration: applicability of global equations to regional datasets Cold temperature regions are not well represented in the existing mesopelagic fish regression models. Both Ikeda (2016) and Belcher et al. (2019) used global data to develop their regressions, with a dominance of data from lower latitudes [71% and 86% of respiration data at temperatures >5°C for Ikeda (2016) and Belcher et al. (2019), respectively]. Although our ETS-derived data sit in the cloud of myctophid respiration rate data compiled by Belcher et al. (2019) (Figure 4), comparison of the Belcher2019_12 regression and our All Myctophid regressions reveals that the addition of our myctophid data results in a lower mass scaling coefficient for data at in situ temperatures (Table 1, Figure 4B). The poor fit of the Ikeda2016 and Belcher2019 allometric regressions to the Scotia Sea dataset could relate to the consumption of lipid-rich zooplankton that predominate in cold water regions (Lee et al., 2006). Organisms respiring lipids have a low respiratory quotient [RQ; moles CO2 produced/moles O2 consumed relative to those respiring proteins or carbohydrates (RQs = 0.7, 0.8 and 1.0, respectively)]. Therefore, producing a mole of CO2 when metabolizing fat will consume 1.4 moles of O2, whereas producing 1 mole of CO2 from carbohydrate will only require 1 mole of oxygen; fat metabolism is an oxygen-hungry process. The consumption of lipid-rich prey may also result in cold water mesopelagic fishes ingesting more carbon, e.g. relative to nitrogen, than their physiology requires. One mechanism through which organisms void excess dietary carbon is by “futile cycling”, whereby excess carbon is disposed of via respiration that is decoupled from biochemical or mechanical “work” (Hessen and Anderson, 2008), resulting in elevated oxygen consumption rates. Further studies are required to examine these hypotheses. Nevertheless, environmentally driven and/or inter-species variation in diet may therefore contribute to the elevated respiration rates we measured in the Scotia Sea. The lack of data from cold water regions in the Ikeda (2016) and Belcher et al. (2019) datasets means that the potential for diet-driven increased rates of oxygen consumption in animals feeding on lipid-rich prey would not be well captured by their respective regression equations. Mesopelagic fish respiration: inter- and intra-specific variabilities The mass scaling coefficient has been shown to vary with phylogeny, although differences between taxa are not always statistically significant (Clarke and Johnston, 1999). Our data highlight a significantly lower mass scaling coefficient for the Scotia Sea data than for the global Ikeda (2016) dataset (Table 1), whereas no significant differences were found between mass scaling coefficients derived for the Benguela data and the Ikeda (2016) dataset. We can further examine the cause of the low-mass exponent of the Scotia Sea data by breaking the data down to the different species (Figure 5). Species-specific regression analysis revealed that the mass scaling coefficients for E. antarctica and K. anderssoni (RIND12, 0.74 and 0.73 respectively) agree much better with the scaling coefficient of Ikeda (2016), and the low overall mass scaling coefficient for the Scotia Sea data is driven by the lack of relationship between respiration and WM for Gymnoscopelus spp., and this likely explains the low R2 of our relationship with mass for the Scotia Sea dataset (Table 1). This lack of scaling of respiration rate with WM for Gymnoscopelus spp. could simply suggest that the size range sampled was not large enough to see this. Although there was no significant difference between the mass scaling coefficient of Ikeda2016_12 and the overall Benguela dataset, Figure 5B highlights that there are still inter-species differences in both mass scaling and mean respiration rate at the Benguela site. Our observations show that, within a given order, the metabolic rates can vary substantially for a given body mass and temperature. This is not surprising as the energetic requirements of different species vary with differences in lifestyle, e.g. activity, habitat, feeding mode, diet, swimming mode, as well as body composition (Clarke and Johnston, 1999). These differences also exist between individuals of the same species and will vary both spatially and temporally (Killen et al., 2010). Figure 5. Open in new tabDownload slide Species-specific respiration rates (RIND_INSITU, μl O2 individual−1 h−1) for (A) Scotia Sea and (B) Benguela regions (respiration estimated from ETS measurements). Respiration is plotted as a function of the wet mass per individual (mg). Note the natural logarithmic scale on both x and y axes. There is evidence that, in the Scotia Sea, most myctophids vertically migrate to some degree (e.g. Collins et al., 2012; Saunders et al., 2014, 2015a, b), and this active lifestyle may contribute to their higher metabolic rates compared with other species (Figures 1 and 5). Visual predation on copepods and other relatively large prey (e.g. euphausiids and amphipods) in the surface likely requires greater levels of activity than an ambush feeding strategy employed by many non-migratory resident mesopelagic fish (Pavlov and Kasumyan, 2002). The vertical migrations of many myctophids may therefore reflect a metabolic strategy to allow feeding in warmer epipelagic layers where food is more available to visual predators, and assimilation of this food at depth where they can remain totally inactive (Barham, 1971; Pearcy et al., 1979; Neighbours and Nafpaktitis, 1982). Conversely, Cyclothone spp. and Bathylagus spp. are predominantly found deeper in the water column and are not known to be diel vertical migrators (Sutton et al., 2008; Bernal et al., 2015). The ambush feeding strategy of non-migratory mesopelagic fish, combined with their low feeding intensity and energy requirements, likely comes at reduced metabolic demand. The lower level of activity associated with this more sedentary, deeper-dwelling lifestyle may therefore contribute to the low metabolic rate of these species. The presence/absence of a gas-filled swim bladder and energetic costs associated with this may also drive species differences in metabolic rate. Bathylagidae have low-mass-specific respiration rates relative to other animals, but this difference is less pronounced when respiration is expressed as a protein-specific rate (Supplementary Figure S2). Thus, the low respiration rates of Bathylagidae could be explained by their high water content and low protein content (Tierney et al., 2002; Schaafsma et al., 2018). Species with low protein content will have lower mass-specific respiration rates than those with high protein content. Protein is more tightly related to aerobic respiration than WM, explained by the respiratory machinery being located in the mitochondria, and thus can be an informative measure when examining inter- and intra-species differences in respiration. Adoption of protein as a mass unit for allometric regressions may help to reduce uncertainty but comes at the cost of greater time and facilities needed to make these measurements. Intra-specific variability, and the challenge of obtaining respiration measurements for mesopelagic fish, means that it is difficult to determine the species-specific drivers of metabolic rate. The differences we have observed, both between species and regionally, highlight the caution that needs to be taken when applying global derived relationships to regional datasets. This appears to be particularly true for cold temperature regions where data are sparser. Respiration is a time-consuming parameter to measure, and many studies estimate respiration allometrically using the equations available in the literature (e.g. Takahashi et al., 2009; Giering et al., 2014; Belcher et al., 2019; Pakhomov et al., 2019). The accuracy of these allometrically derived respiration rates has knock-on effects for calculations of respiratory and active flux and can thus affect our conclusions as to the importance of a particular taxa in the biological carbon pump. Given the lack of suitability of either the Belcher2019_12 or Ikeda2016_12 regressions to the respiration rates of mesopelagic fish in the Scotia Sea, we recalculate the myctophidae (vertically migrating fraction) respiratory carbon fluxes of Belcher et al. (2019) using our Scotia Sea regression: Ln(RIND_12)=4.359 (±0.556)+0.334 (±0.066)×Ln(WM).(4) We calculate the myctophid fish community respiration as outlined fully in Belcher et al. (2019). Briefly, respiration rates of myctophid fish (sampled during the Discovery 2010 expeditions to the Scotia Sea, Collins et al., 2012; Tarling et al., 2012) were estimated allometrically based on body mass. As our model (4) is for respiration at 12°C, we adjust respiration rates to the in situ respiration rate using the Arrhenius equation and an activation energy of 15 kcal mol−1 (Packard et al., 1975; Ariza et al., 2015). The in situ respiration rates of individual fish were summed for each net sample, and the daily respiratory flux by migrating myctophids estimated from the difference between day-time and night-time community respiration. Like Belcher et al. (2019), we do not take into account day-time net avoidance (Collins et al., 2012; Fielding et al., 2012) and, thus, estimates are of the maximum respiratory flux as we do not apply any corrections for lower catch efficiency during the day (i.e. total day-time community respiration is likely higher than estimated due to increased day-time biomass, which would result in a lower migratory respiratory flux). We also recalculate the myctophidae (vertically migrating fraction) respiratory carbon fluxes of Belcher et al. (2019) based on model 1 (1 given above) of Ikeda (2016). At the present time, we are unable to perform these calculations for the Benguela region as we lack sufficient coverage of net samples over multiple seasons. We find that estimates of respiratory carbon flux based on our Scotia Sea regression are 3.1–5.0 times greater than calculated by Belcher et al. (2019) and 4.0–8.3 times greater than predictions by the Ikeda2016_INSITU regression (Table 2). Based on the seasonal range of gravitational POC fluxes by Manno et al. (2014) in the Scotia Sea, Belcher et al. (2019) estimated that the myctophid respiratory carbon flux is equivalent to 9–47% and 1–2% of the gravitational POC flux at the North Scotia Sea (NSS) and Georgia Basin (GB) sites, respectively. The large range for the NSS estimate relates to the order of magnitude seasonal variability in POC flux at this site (Manno et al., 2014). Using the Ikeda2016_INSITU regression gives 7–37% and 0.8–1.4% at NSS and GB, respectively. These estimates are much lower than estimates using our Scotia Sea regression (27–143% and 3.1–5.6% at NSS and GB, respectively). Thus, even when POC fluxes are greatest, the respiration of myctophid fish alone (i.e. excluding other myctophid-driven carbon fluxes via excretion, mortality, and defaecation) could be equivalent to a minimum of 27% of the POC flux at NSS based on our new estimates. These calculations highlight (i) the importance of vertically migrating mesopelagic fish to carbon flux, at least in the Southern Ocean, and (ii) how the use of globally derived allometric regressions can result in substantial underestimates of respiratory and active fluxes in polar regions. As noted by Ikeda (2016), more data are needed from deep sea fishes to test and improve allometric models. We add to this that more data are required in regions of temperature <5°C to validate the much higher respiration rates observed at our Scotia Sea study site than predicted through allometric regression models. Table 2. Comparison of respiratory carbon fluxes (mg C m−2 d−1) calculated from the Discovery 2010 surveys in the Scotia Sea using allometric regressions; Scotia Sea, Belcher2019_INSITU and Ikeda2016_INSITU. Site . Respiratory flux mg C m−2 d−1 (% of Scotia Sea estimate) . Scotia Sea (this study) . Belcher2019_INSITU . Ikeda2016_INSITU . JR161 WSS, n (%) 0.25 0.05 (20.0) 0.03 (12.0) JR161 NSS, n (%) 0.86 0.28 (32.6) 0.22 (25.6) JR177 GB, n (%) 0.40 0.13 (32.5) 0.10 (25.0) JR177 MSS, n (%) 0.91 0.27 (29.73) 0.20 (22.0) Site . Respiratory flux mg C m−2 d−1 (% of Scotia Sea estimate) . Scotia Sea (this study) . Belcher2019_INSITU . Ikeda2016_INSITU . JR161 WSS, n (%) 0.25 0.05 (20.0) 0.03 (12.0) JR161 NSS, n (%) 0.86 0.28 (32.6) 0.22 (25.6) JR177 GB, n (%) 0.40 0.13 (32.5) 0.10 (25.0) JR177 MSS, n (%) 0.91 0.27 (29.73) 0.20 (22.0) To compare the results from the different regressions, we also express the Belcher2019 and Ikeda2016 estimates as a percentage of the Scotia Sea estimate, given in brackets (see Belcher et al. 2019 for details of calculation and Discovery 2010 surveys). Open in new tab Table 2. Comparison of respiratory carbon fluxes (mg C m−2 d−1) calculated from the Discovery 2010 surveys in the Scotia Sea using allometric regressions; Scotia Sea, Belcher2019_INSITU and Ikeda2016_INSITU. Site . Respiratory flux mg C m−2 d−1 (% of Scotia Sea estimate) . Scotia Sea (this study) . Belcher2019_INSITU . Ikeda2016_INSITU . JR161 WSS, n (%) 0.25 0.05 (20.0) 0.03 (12.0) JR161 NSS, n (%) 0.86 0.28 (32.6) 0.22 (25.6) JR177 GB, n (%) 0.40 0.13 (32.5) 0.10 (25.0) JR177 MSS, n (%) 0.91 0.27 (29.73) 0.20 (22.0) Site . Respiratory flux mg C m−2 d−1 (% of Scotia Sea estimate) . Scotia Sea (this study) . Belcher2019_INSITU . Ikeda2016_INSITU . JR161 WSS, n (%) 0.25 0.05 (20.0) 0.03 (12.0) JR161 NSS, n (%) 0.86 0.28 (32.6) 0.22 (25.6) JR177 GB, n (%) 0.40 0.13 (32.5) 0.10 (25.0) JR177 MSS, n (%) 0.91 0.27 (29.73) 0.20 (22.0) To compare the results from the different regressions, we also express the Belcher2019 and Ikeda2016 estimates as a percentage of the Scotia Sea estimate, given in brackets (see Belcher et al. 2019 for details of calculation and Discovery 2010 surveys). Open in new tab Concluding remarks It is time consuming and difficult to make respiration measurements in the field, particularly on fish collected from the mesopelagic. ETS provides a promising method for obtaining estimates of respiration from mesopelagic species, but there are still methodological considerations, especially regarding an appropriate R:ETS ratio to use. The data presented in this study demonstrate that globally derived allometric equations underestimate respiration rates of cold water mesopelagic fish. This potentially reflects the lipid-rich diets of these organisms. We have constructed a regression for myctophids (All Myctophid, Table 1) utilizing data across a range of regions and giving better representation of polar regions than previous equations. Nevertheless, even this myctophid-specific regression overestimates the respiration of the large Gymnoscopelus spp. Our data demonstrate that respiration rates can vary greatly between species, which may be related to differences in lifestyle, e.g. activity, habitat, feeding mode, diet, swimming mode, as well as body composition. We find high variability even between individuals of a given species with the same mass at the same environmental temperature. This variability means that allometric equations based solely on mass, or a combination of mass and temperature, will never be that precise in estimating respiration at an individual level. We stress that particular care should be taken when applying allometrical relationships to regional studies where the environmental conditions of that region are poorly represented in the data used to define the regression equation. Underestimations of respiration rates of mesopelagic fish in cold water regions have implications on estimates of fish-driven respiratory flux and thus the biological carbon pump. Allometric estimates of fish-driven respiratory flux in the Scotia Sea were 67–88% lower than ETS-based estimates. Measurements of micronekton respiration are thus still needed, particularly for mesopelagic dwelling species and for under-sampled regions, because their contribution to carbon flux can be large. Only with these data we can build up our global databases sufficiently to be able to estimate total respiration confidently and parameterize respiratory flux or active flux. This is especially important to global biogeochemical models because the potential contribution of mesopelagic fish to carbon flux can be substantial. Supplementary data Supplementary material is available at the ICESJMS online version of the manuscript. Acknowledgements We thank the two anonymous reviewers for their insightful comments that improved the manuscript. We are also very grateful to May Gomez, Ted Packard, and Ico Martinez at EOMAR as well as Santiago Hernández León, Laia Armengol, and Ione Medina Suarez at IOCAG, all at University of Las Palmas, Gran Canaria, for hosting authors Anna Belcher and Kathryn Cook at their laboratories to demonstrate and teach their ETS assay method. We also thank Alejandro Ariza for insightful discussions during data analysis and manuscript development. Finally, we would like to thank fellow comedians who participated in the COMICS research cruises for their invaluable support during data collection. In particular, we thank Filipa Carvalho for providing accompanying physical oceanography data. Funding This work was supported by the BAS Ecosystems programme and the NERC funded Large Grant, COMICS (NE/M020762/1 and NE/M020835/1). References Anderson T. R. , Martin A. P., Lampitt R. S., Trueman C. N., Henson S. A., Mayor D. J. 2019 . Quantifying carbon fluxes from primary production to mesopelagic fish using a simple food web model . ICES Journal of Marine Science , 76 : 690 – 701 . Google Scholar Crossref Search ADS WorldCat Ariza A. , Garijo J. C., Landeira J. M., Bordes F., Hernández-León S. 2015 . Migrant biomass and respiratory carbon flux by zooplankton and micronekton in the subtropical northeast Atlantic Ocean (Canary Islands) . Progress in Oceanography , 134 : 330 – 342 . Google Scholar Crossref Search ADS WorldCat Baker A. D. C. , Clarke M. R., Harris M. J. 1973 . The N.I.O. combination net (RMT 1 + 8) and further developments of rectangular midwater trawls . Journal of the Marine Biological Association , 53 : 167 – 184 . Google Scholar Crossref Search ADS WorldCat Barham E. G. 1971 . Deep-sea fishes: lethargy and vertical orientation. In Proceedings of an International Symposium on Biological Sound Scattering in the Ocean , pp. 100 – 118 . Ed. by Farquhar G. B.. Washington, DC . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Belcher A. , Saunders R. A., Tarling G. A. 2019 . Respiration rates and active carbon flux of mesopelagic fishes (Family Myctophidae) in the Scotia Sea, Southern Ocean . Marine Ecology Progress Series , 610 : 149 – 162 . Google Scholar Crossref Search ADS WorldCat Bernal A. , Olivar M. P., Maynou F., Luz Fernández de Puelles M. 2015 . Diet and feeding strategies of mesopelagic fishes in the western Mediterranean . Progress in Oceanography , 135 : 1 – 17 . Google Scholar Crossref Search ADS WorldCat Bianchi D. , Stock C., Galbraith E. D., Sarmiento J. L. 2013 . Diel vertical migration: ecological controls and impacts on the biological pump in a one-dimensional ocean model . Global Biogeochemical Cycles , 27 : 478 – 491 . Google Scholar Crossref Search ADS WorldCat Boyd P. W. , Claustre H., Levy M., Siegel D. A., Weber T. 2019 . Multi-faceted particle pumps drive carbon sequestration in the ocean . Nature , 568 : 327 – 335 . Google Scholar Crossref Search ADS PubMed WorldCat Clarke A. , Johnston N. M. 1999 . Scaling of metabolic rate with body mass and temperature in teleost fish . Journal of Animal Ecology , 68 : 893 – 905 . Google Scholar Crossref Search ADS WorldCat Collins M. A. , Stowasser G., Fielding S., Shreeve R., Xavier J. C., Venables H. J., Enderlein P. et al. 2012 . Latitudinal and bathymetric patterns in the distribution and abundance of mesopelagic fish in the Scotia Sea . Deep-Sea Research Part II: Topical Studies in Oceanography , 59–60 : 189 – 198 . Google Scholar Crossref Search ADS WorldCat Davison P. C. , Checkley D. M., Koslow J. A., Barlow J. 2013 . Carbon export mediated by mesopelagic fishes in the northeast Pacific Ocean . Progress in Oceanography , 116 : 14 – 30 . Google Scholar Crossref Search ADS WorldCat Fielding S. , Watkins J. L., Collins M. A., Enderlein P., Venables H. J. 2012 . Acoustic determination of the distribution of fish and krill across the Scotia Sea in spring 2006, summer 2008 and autumn 2009 . Deep-Sea Research Part II , 59–60 : 173 – 188 . Google Scholar Crossref Search ADS WorldCat Giering S. L. C. , Sanders R., Lampitt R. S., Anderson T. R., Tamburini C., Boutrif M., Zubkov M. V. et al. 2014 . Reconciliation of the carbon budget in the ocean’s twilight zone . Nature , 507 : 480 – 483 . Google Scholar Crossref Search ADS PubMed WorldCat Gjøsaeter J. , Kawaguchi K. 1980 . A review of the world resources of mesopelagic fish . FAO Fisheries Technical Paper, 193 : 1 – 134 . Google Scholar OpenURL Placeholder Text WorldCat Gómez M. , Torres S., Hernández-León S. 1996 . Modification of the electron transport system (ETS) method for routine measurements of respiratory rates of zooplankton . South African Journal of Marine Science , 16 : 15 – 20 . Google Scholar Crossref Search ADS WorldCat Hernández-León S. , Gómez M. 1996 . Factors affecting the respiration/ETS ratio in marine zooplankton . Journal of Plankton Research , 18 : 239 – 255 . Google Scholar Crossref Search ADS WorldCat Hernández-León S. , Olivar M. P., Luz M., De Puelles F., Bode A., Castellón A., López-pérez C. et al. 2019 . Zooplankton and micronekton active flux across the tropical and subtropical Atlantic Ocean . Frontiers in Marine Science , 6 : 1 – 20 . Google Scholar Crossref Search ADS WorldCat Hessen D. O. , Anderson T. R. 2008 . Excess carbon in aquatic organisms and ecosystems: physiological, ecological, and evolutionary implications . Limnology and Oceanography , 53 : 1685 – 1696 . Google Scholar Crossref Search ADS WorldCat Hidaka K. , Kawaguchi K., Murakami M., Takahashi M. 2001 . Downward transport of organic carbon by diel migratroy microneckton in the western equatorial Pacific: its quantitative and qualitative importance . Deep Sea Research Part I , 48 : 1923 – 1939 . Google Scholar Crossref Search ADS WorldCat Hudson J. M. , Steinberg D. K., Sutton T. T., Graves J. E., Latour R. J. 2014 . Myctophid feeding ecology and carbon transport along the northern Mid-Atlantic Ridge . Deep-Sea Research Part I: Oceanographic Research Papers , 93 : 104 – 116 . Google Scholar Crossref Search ADS WorldCat Ikeda T. , Skjoldal H. R. 1980 . The effect of laboratory conditions on the extrapolation of experimental measurements to the ecology of marine zooplankton VI. Changes in physiological activities and biochemical components of Acetes sibogae australis and Acartia australis after capture . Marine Biology , 58 : 285 – 293 . Google Scholar Crossref Search ADS WorldCat Ikeda T. 1989 . Estimated respiration rate of myctophid fish from the enzyme activity of the electron-transport-system . Journal of the Oceanographical Society of Japan , 45 : 167 – 173 . Google Scholar Crossref Search ADS WorldCat Ikeda T. 1996 . Metabolism, body composition, and energy budget of the mesopelagic fish Maurolicus muelleri in the Sea of Japan . Fishery Bulletin , 94 : 49 – 58 . Google Scholar OpenURL Placeholder Text WorldCat Ikeda T. 2016 . Routine metabolic rates of pelagic marine fishes and cephalopods as a function of body mass, habitat temperature and habitat depth . Journal of Experimental Marine Biology and Ecology , 480 : 74 – 86 . Google Scholar Crossref Search ADS WorldCat Irigoien X. , Klevjer T., Røstad A., Martinez U., Boyra G., Acuna J., Bode A. et al. 2014 . Large mesopelagic fishes biomass and trophic efficiency in the open ocean . Nature Communications , 5 : 3271 . Google Scholar Crossref Search ADS PubMed WorldCat Jónasdóttir S. H. , Visser A. W., Richardson K., Heath M. R. 2015 . Seasonal copepod lipid pump promotes carbon sequestration in the deep North Atlantic. Proceedings of the National Academy of Sciences of the United States of America, 112: 12122 – 12126 . Killen S. , Atkinson D., Glazier D. 2010 . The intraspecific scaling of metabolic rate with body mass in fishes depends on lifestyle and temperature . Ecology Letters , 13 : 184 – 193 . Google Scholar Crossref Search ADS PubMed WorldCat Klevjer T. A. , Irigoien X., Røstad A., Fraile-Nuez E., Benítez-Barrios V., Kaartvedt S. 2016 . Large scale patterns in vertical distribution and behaviour of mesopelagic scattering layers . Scientific Reports , 6 : 19873 . Google Scholar Crossref Search ADS PubMed WorldCat Kwon E. Y. , Primeau F., Sarmiento J. L. 2009 . The impact of remineralization depth on the air–sea carbon balance . Nature Geoscience , 2 : 630 – 635 . Google Scholar Crossref Search ADS WorldCat Lee R. F. , Hagen W., Kattner G. 2006 . Lipid storage in marine zooplankton . Marine Ecology Progress Series , 307 : 273 – 306 . Google Scholar Crossref Search ADS WorldCat Longhurst A. R. , Bedo A., Harrison G. W., Head E. J. H., Sameoto D. 1990 . Vertical flux of respiratory carbon by oceanic diel migrant biota . Deep-Sea Research , 37 : 685 – 694 . Google Scholar Crossref Search ADS WorldCat Lowry O. , Rosebrough N., Farr L., Randall R. J. 1951 . Protein measurement with the folin phenol reagent . Journal of Biological Chemistry , 193 : 265 – 275 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Maldonado F. , Packard T. T., Gómez M. 2012 . Understanding tetrazolium reduction and the importance of substrates in measuring respiratory electron transport activity . Journal of Experimental Marine Biology and Ecology , 434–435 : 110 – 118 . Google Scholar Crossref Search ADS WorldCat Manno C. , Stowasser G., Enderlein P., Fielding S., Tarling G. a. 2014 . The contribution of zooplankton faecal pellets to deep carbon transport in the Scotia Sea (Southern Ocean) . Biogeosciences Discussions , 11 : 16105 – 16134 . Google Scholar Crossref Search ADS WorldCat Neighbours M. A. , Nafpaktitis B. G. 1982 . Lipid compositions, water contents, swimbladder morphologies and buoyancies of nineteen species of midwater fishes (18 myctophids and 1 neoscopelid) . Marine Biology , 66 : 207 – 215 . Google Scholar Crossref Search ADS WorldCat Osma N. , Fernández-Urruzola I., Gómez M., Montesdeoca-Esponda S., Packard T. T. 2016 . Predicting in vivo oxygen consumption rate from ETS activity and bisubstrate enzyme kinetics in cultured marine zooplankton . Marine Biology , 163 : 1 – 14 . Google Scholar Crossref Search ADS WorldCat Owens T. G. , King F. D. 1975 . The measurement of respiratory electron-transport-system activity in marine zooplankton . Marine Biology , 30 : 27 – 36 . Google Scholar Crossref Search ADS WorldCat Packard T. T. , Devol A. H., King F. D. 1975 . The effect of temperature on the respiratory electron transport system in marine plankton . Deep Sea Research , 22 : 237 – 249 . Google Scholar OpenURL Placeholder Text WorldCat Packard T. T. , Berdalet E., Blasco D., Roy S. O., St-Amand L., Lagace B., Lee K. et al. 1996 . Oxygen consumption in the marine bacterium Pseudomonas nautica predicted from ETS activity and bisubstrate enzyme kinetics . Journal of Plankton Research , 18 : 1819 – 1835 . Google Scholar Crossref Search ADS WorldCat Packard T. T. , Christensen J. P. 2004 . Respiration and vertical carbon Flux in the Gulf of Maine water column . Journal or Marine Research , 62 : 93 – 115 . Google Scholar Crossref Search ADS WorldCat Pakhomov E. A. , Podeswa Y., Hunt B. P. V., Kwong L. E. 2019 . Vertical distribution and active carbon transport by pelagic decapods in the North Pacific Subtropical Gyre . ICES Journal of Marine Science , 76 : 702 – 717 . Google Scholar Crossref Search ADS WorldCat Pavlov D. , Kasumyan A. 2002 . Feeding diversity in fishes: trophic classification of fish . Journal of Ichthyology , 42 : S137 – S159 . Google Scholar OpenURL Placeholder Text WorldCat Pearcy W. G. , Lorz H. V., Peterson W. 1979 . Comparison of the feeding habits of migratory and non-migratory Stenobrachius leucopsarus (Myctophidae) . Marine Biology , 51 : 1 – 8 . Google Scholar Crossref Search ADS WorldCat Piatkowski U. , Rodhouse P. G., White M. G., Bone D. G., Symon C. 1994 . Nekton community of the Scotia Sea as sampled by the RMT-25 during austral summer . Marine Ecology Progress Series , 112 : 13 – 28 . Google Scholar Crossref Search ADS WorldCat Proud R. , Handegard N. O., Kloser R. J., Cox M. J., Brierley A. S. 2019 . From siphonophores to deep scattering layers: uncertainty ranges for the estimation of global mesopelagic fish biomass . ICES Journal of Marine Science , 76 : 718 – 733 . Google Scholar Crossref Search ADS WorldCat Rutter W. 1967 . Protein determination in embryos. In Methods in Developmental Biology , pp. 671 – 683 . Ed. by Wilt F. and Wessels N.. Thomas Y. Crowell Co , New York . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Saunders R. A. , Collins M. A., Foster E., Shreeve R., Stowasser G., Ward P., Tarling G. A. 2014 . Trophodynamics of Eelctrona (Myctophidae) in the Scotia Sea (Southern Ocean) . Polar Biology , 37 : 789 – 807 . Google Scholar Crossref Search ADS WorldCat Saunders R. A. , Collins M. A., Ward P., Stowasser G., Shreeve R., Tarling G. A. 2015a . Trophodynamics of Protomyctophum (Myctophidae) in the Scotia Sea (Southern Ocean) . Journal of Fish Biology , 87 : 1031 – 1058 . Google Scholar Crossref Search ADS WorldCat Saunders R. A. , Collins M. A., Ward P., Stowasser G., Shreeve R., Tarling G. A. 2015b . Distribution, population structure and trophodynamics of Southern Ocean Gymnoscopelus (Myctophidae) in the Scotia Sea . Polar Biology , 38 : 287 – 308 . Google Scholar Crossref Search ADS WorldCat Schaafsma F. L. , Cherel Y., Flores H., van Franeker J. A., Lea M. A., Raymond B., van de Putte A. P. 2018 . Review: The Energetic Value of Zooplankton and Nekton Species of the Southern Ocean . Springer , Berlin/Heidelberg . 1 – 35 pp. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Schalk P. H. 1988 . Respiratory electron transport system (ETS) activities in zooplankton and micronekton of the Indo-Pacific region . Marine Ecology Progress Series , 44 : 25 – 35 . Google Scholar Crossref Search ADS WorldCat Secor S. M. 2009 . Specific dynamic action: a review of the postprandial metabolic response . Journal of Comparative Physiology B , 179 : 1 – 56 . Google Scholar Crossref Search ADS WorldCat Simcic T. , Brancelj A. 2004 . Respiratory electron transport system (ETS) activity as an estimator of the thermal tolerance of two Daphnia hybrids . Journal of Plankton Research , 26 : 525 – 534 . Google Scholar Crossref Search ADS WorldCat Steinberg D. K. , Carlson C. A., Bates N. R., Goldthwait S. A., Madin L. P., Michaels A. F. 2000 . Zooplankton vertical migration and the active transport of dissolved organic and inorganic carbon in the Sargasso Sea . Deep Sea Research Part I: Oceanographic Research Papers , 47 : 137 – 158 . Google Scholar Crossref Search ADS WorldCat Steinberg D. K. , Landry M. R. 2017 . Zooplankton and the ocean carbon cycle . Annual Review of Marine Science , 9 : 413 – 444 . Google Scholar Crossref Search ADS PubMed WorldCat Sutton T. T. , Porteiro F. M., Heino M., Byrkjedal I., Langhelle G., Anderson C. I. H., Horne J. et al. 2008 . Vertical structure, biomass and topographic association of deep-pelagic fishes in relation to a mid-ocean ridge system . Deep-Sea Research Part II , 55 : 161 – 184 . Google Scholar Crossref Search ADS WorldCat Takahashi K. , Kuwata A., Sugisaki H., Uchikawa K., Saito H. 2009 . Downward carbon transport by diel vertical migration of the copepods Metridia pacifica and Metridia okhotensis in the Oyashio region of the western subarctic Pacific Ocean . Deep Sea Research Part I , 56 : 1777 – 1791 . Google Scholar Crossref Search ADS WorldCat Tarling G. A. , Ward P., Atkinson A., Collins M. A., Murphy E. J. 2012 . DISCOVERY 2010: spatial and temporal variability in a dynamic polar ecosystem . Deep-Sea Research Part II , 59–60 : 1 – 13 . Google Scholar Crossref Search ADS WorldCat Tierney M. , Hindell M. A., Goldsworthy S. 2002 . Energy content of mesopelagic fish from Macquarie Island . Antarctic Science , 14 : 225 – 230 . Google Scholar Crossref Search ADS WorldCat Turner J. T. 2002 . Zooplankton fecal pellets, marine snow and sinking phytoplankton blooms . Aquatic Microbial Ecology , 27 : 57 – 102 . Google Scholar Crossref Search ADS WorldCat Zhang X. , Dam H. G. 1997 . Downward export of carbon by diel migrant mesozooplankton in the central equatorial Pacific . Deep Sea Research Part II: Topical Studies in Oceanography , 44 : 2191 – 2202 . Google Scholar Crossref Search ADS WorldCat © International Council for the Exploration of the Sea 2020. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. © International Council for the Exploration of the Sea 2020.

Haarr, Marthe, Larsen;Comeau,, Michel;Chassé,, Jöel;Rochette,, Rémy

doi: 10.1093/icesjms/fsaa027pmid: N/A

Abstract Increasing ocean temperatures may affect life cycles of organisms whose biological processes are temperature-dependent. Our objective was to determine whether hatching time of American lobster (Homarus americanus), which has a 2-year reproductive cycle, has advanced in the southern Gulf of St Lawrence, Canada, in response to rising temperature. We investigated temporal trends in hatching time 1989–2014 using fisheries monitoring data. We considered two metrics: the first week of the year when ovigerous females with prehatch or hatching clutches were observed [onset-of-hatching (OH)] and the rate of change in the ratio of females with prehatch/hatching vs. developing clutches each spring fishing season [rate of clutch development (RCD)]. OH advanced by 5 weeks and RCD increased by 40% on average. Comparisons of OH and RCD to cumulative degree-days going back 2 years prior to hatching suggested an effect of higher fall temperatures during early ovarian and embryonic development. The advancement of hatching time in response to environmental conditions 6–18 months before hatching occurs could lead to a mismatch with larval prey species with shorter life cycles. These findings highlight the importance of monitoring phenology of fished species and the need for further research into potential impacts of phenological changes. Introduction Upper water (<75 m) temperature has increased by ∼0.1°C per decade since 1970 globally, and by 1°C per decade in the northwest Atlantic (Knudsen et al., 2011; Galbraith et al., 2012, 2015; Rhein et al., 2013; Loder and Wang, 2015). Changes in temperature are particularly consequential to marine life, as most marine organisms are ectothermic. Metabolism generally increases exponentially with temperature within an organism’s physiological limits, and thus rising water temperature will accelerate most physiological processes (Doney et al., 2012), such as growth, sexual maturation, embryonic development, and larval development (Waddy et al., 1995; Cha et al., 1997; Heilmayer et al., 2005). Such increases in physiological rates can in turn affect phenology, including the timing of reproductive events (Doney et al., 2012; Gerber et al., 2014). There is ample evidence from terrestrial ecosystems that climate change is resulting in altered phenologies, such as advancing breeding, nesting, and flowering events (Parmesan and Yohe, 2003; Root et al., 2003). There is also a growing body of evidence of phenological changes in marine ecosystems, such as shifts in seasonal peak abundance of zooplankton and larval fishes, phytoplankton blooms, and fish migrations (Edwards and Richardson, 2004; Sullivan et al., 2007; Schlüter et al., 2010; Asch, 2015; Asch et al., 2019; Staudinger et al., 2019). Climate-driven phenological shifts related to larval phases may be common, given over 70% of marine organisms have pelagic larval phases (Gerber et al., 2014). Changes in the timing of hatching may affect food availability during the larval phase (Vaughn and Allen, 2010; Gerber et al., 2014), potentially leading to a temporal mismatch between predatory offspring and their prey, and subsequent year-class failure (Cushing, 1990; Durant et al., 2007). Altering the timing of spawning and larval release may also alter the temperature and currents experienced by the larvae, which can further affect their survival success, development rate, and associated dispersal (Cowen and Sponaugle, 2009; Gerber et al., 2014). Investigating the relationship between water temperature and the timing of larval release is critical to understand the effects of climate change on the connectivity and recruitment of marine populations, as well as subsequent effects on conservation efforts and fisheries management. The American lobster (Homarus americanus) supports the most valuable fishery on the east coast of North America, valued annually at 1.5 billion dollars and employing 10 000 licenced harvesters in Canada alone (see Fisheries and Oceans Canada: https://www.dfo-mpo.gc.ca/fisheries-peches/sustainable-durable/fisheries-peches/lobster-homard-eng.html). There is evidence that recent increases in ocean temperature are affecting this important fishery. In the southernmost part of the species’ range, stress from high temperature and disease outbreak appears responsible for marked stock declines and collapses (Le Bris et al., 2018). Shallow nearshore lobster nursery grounds are receding as summer water temperature has increased above physiological limits for benthic lobster (>20°C; Jury and Watson, 2013; Wahle et al., 2015). In contrast, increasing abundances have been observed in the northern part of the species’ range (DFO, 2016a). There is also evidence that rising water temperature does not only affect lobster at the species’ range limits. In the Bay of Fundy, for example, size-specific female lobster fecundity has declined by ∼30% from 2008 to 2013, with increasing water temperature hypothesized as a possible cause (Koopman et al., 2015). Further effects of climate change on American lobster reproductive biology and phenology are likely given that both reproduction and growth are primarily temperature regulated in the species (Waddy and Aiken, 1995; Tlusty et al., 2008). The timing of egg hatching for the American lobster is likely influenced by temperature during the female reproductive cycle. For small/young mature females, reproduction is typically a 2-year process, where a female moults and mates one summer, stores the sperm in its seminal receptacle until the following summer when spawning occurs, then carries the eggs under its abdomen for 9–12 months before hatching, and releasing larvae during the third summer (type 1a; Aiken and Waddy, 1982; Figure 1). A smaller proportion of mature females (type 1b) have a 1-year cycle, in which moulting, mating, and spawning all occur in the same season with hatching the following summer (Aiken and Waddy, 1982; Comeau and Savoie, 2002b; Figure 1). Larger/older females may skip moulting between spawnings and spawn in consecutive years (Waddy and Aiken, 1986). Figure 1. Open in new tabDownload slide Gantt chart showing a conceptual model of the female American lobster typical 2-year (type 1a) and less common 1-year (type 1b) reproductive cycles between moulting and egg hatching. Processes shaded in dark grey are those under consideration in this study; the dotted vertical line indicates the point after which energy reserves are used for gonad development, rather than somatic growth, until the end of secondary vitellogenesis for type 1a females. Important events in the reproductive cycle are in white, whereas the onset of primary vitellogenesis in year 3 and mating of type 1b multiparous females are less certain and marked by an asterisk (*). The striped vertical bars indicate time periods of physiological diapause (i.e. in winter with temperatures <0°C in the southern Gulf of St. Lawrence). Figure 1. Open in new tabDownload slide Gantt chart showing a conceptual model of the female American lobster typical 2-year (type 1a) and less common 1-year (type 1b) reproductive cycles between moulting and egg hatching. Processes shaded in dark grey are those under consideration in this study; the dotted vertical line indicates the point after which energy reserves are used for gonad development, rather than somatic growth, until the end of secondary vitellogenesis for type 1a females. Important events in the reproductive cycle are in white, whereas the onset of primary vitellogenesis in year 3 and mating of type 1b multiparous females are less certain and marked by an asterisk (*). The striped vertical bars indicate time periods of physiological diapause (i.e. in winter with temperatures <0°C in the southern Gulf of St. Lawrence). Primary vitellogenesis, during which yolk is synthesized within the oocytes resulting in a slow increase in ovarian size, begins as early as three summers prior to hatching (Aiken and Waddy, 1980; Ennis, 1995; Waddy and Aiken, 1995; Comeau and Benhalima, 2018; Figure 1). It is only after moulting and mating that a female directs energy towards ovarian development, as prior to this she allocates energy to somatic growth (Adiyodi, 1985). Secondary vitellogenesis is shorter than primary vitellogenesis and begins in autumn in the southern Gulf of St Lawrence (sGSL) prior to the winter diapause and resumes in the spring before summer spawning (Comeau and Benhalima, 2018). It is regulated by an interaction between temperature and photoperiod (Aiken and Waddy, 1980; Waddy and Aiken, 1995). Embryonic development is also temperature-dependent (Perkins, 1972). Embryos undergo rapid development after spawning in the summer/fall and can reach 50–80% of development before going into diapause in the winter (Gendron and Ouellet, 2009). They resume development in the spring, followed by hatching and larval release between May and September (Ennis, 1995; Gendron and Ouellet, 2009). The pelagic larvae go through three moults in the water column over a period of 2–8 weeks, depending on temperature, before becoming competent to settle on the benthos (Ennis, 1995). The objective of this study was to determine whether there is evidence that increases in water temperature have modified the timing of hatching of American lobster in sGSL, Canada, from 1989 to 2014. We used a coupled ice-ocean hydrodynamic model to obtain bottom temperature, and fisheries monitoring data to assess temporal trends in (i) the rate of clutch maturation through spring and (ii) the onset of the hatching period, both at the population (i.e. site) level rather than for individual females/clutches. We compared interannual variation in the rate of clutch maturation and the onset of egg hatching each spring to seasonal (fall–winter and spring–summer) cumulative degree-days (CDDs) up to 2 years prior to hatching to determine (i) whether temperature has influenced hatching time and (ii) during which portion of the reproductive cycle, incorporating both ovarian and embryonic development, temperature is most influential. Methods Monitoring of ovigerous females in the sGSL There are no available historical or time-series data that have been collected specifically to assess reproductive timing in American lobster, and therefore limited data with which to investigate potentially changing phenologies in the species. However, fisheries monitoring data from the sGSL do allow some investigation of this question. At-sea sampling has been carried out during the spring lobster fishing season (May-–June) in areas 23, 24, and 26A (Figure 2) since 1989 (Mallet et al., 2006). Data collected include sex, condition (missing claws, shell hardness), carapace length (CL), and location of capture for all lobsters, as well as clutch stage of ovigerous females (Mallet et al., 2006). Clutch stage is based on embryo development and is categorized on a scale from 1 to 4 (Figure 3). During stage 4, eggs will hatch over several days to weeks (Tlusty et al., 2008). From 1989 to 2003, stages 3 and 4 were not distinguished, but grouped as clutches with well-developed embryos. After 2004, all four stages were distinguished. Stage 3 clutches are typically within a week of commencing hatching (MLH and RR, unpublished data). Figure 2. Open in new tabDownload slide Map of the southwestern Gulf of St Lawrence located in eastern Canada showing the four study areas (grey polygons) divided based on lobster sampling locations (black circles) and mean summer temperatures. The map also indicates the boundaries of different lobster fishing areas (black line). Figure 2. Open in new tabDownload slide Map of the southwestern Gulf of St Lawrence located in eastern Canada showing the four study areas (grey polygons) divided based on lobster sampling locations (black circles) and mean summer temperatures. The map also indicates the boundaries of different lobster fishing areas (black line). Figure 3. Open in new tabDownload slide Visual clutch staging scheme. A stage 1 clutch is newly spawned; clutch appears black or olive green, and no part of the embryo is visible (i.e. eggs consist primarily of yolk). A stage 2 clutch is further developed but still immature (i.e. not close to hatching); the overall appearance of the clutch is lighter, the embryo’s eye spots are visible within the eggs and individual eggs are clearly two toned in colour with one portion consisting of the embryo and the other of yolk. Stage 3 clutches are mature and close to hatching; overall the clutch appears tan to orange in colour, and the embryos now take up most of the space inside the eggs (i.e. very little to no yolk is visible). A stage 4 clutch is in the process of hatching and can be recognized by primarily dark eggs without yolk and clearly visible embryos, the presence of prezoeae (newly hatched prelarvae), and (later in the hatching period) empty egg casings and adhesive material (the clutch appears “mossy”). Figure 3. Open in new tabDownload slide Visual clutch staging scheme. A stage 1 clutch is newly spawned; clutch appears black or olive green, and no part of the embryo is visible (i.e. eggs consist primarily of yolk). A stage 2 clutch is further developed but still immature (i.e. not close to hatching); the overall appearance of the clutch is lighter, the embryo’s eye spots are visible within the eggs and individual eggs are clearly two toned in colour with one portion consisting of the embryo and the other of yolk. Stage 3 clutches are mature and close to hatching; overall the clutch appears tan to orange in colour, and the embryos now take up most of the space inside the eggs (i.e. very little to no yolk is visible). A stage 4 clutch is in the process of hatching and can be recognized by primarily dark eggs without yolk and clearly visible embryos, the presence of prezoeae (newly hatched prelarvae), and (later in the hatching period) empty egg casings and adhesive material (the clutch appears “mossy”). We used clutch stage data from 58 fishing ports (1126 sampling trips) to investigate temporal trends in the timing of hatching between 1989 and 2014. The exact timing of the at-sea sampling varied interannually because of factors such as ice coverage and storm days (Mallet et al., 2006). There was a trend for sampling to extend slightly later (5 d) into the year as the study progressed from 1989 to 2014. We were generally able to assess temporal trends in spring clutch development of ovigerous females during the latter half of May until the end of June (Table 1). Table 1. Summary of sampling conditions in each of our four study areas, including the number of years with adequate data to estimate the two metrics of the timing of hatching (OH and RCD), the timing of the sampling period, as well as temperature conditions in terms of CDDs (3.4°C threshold) in spring–summer (April–September) and fall–winter (October–March) months, showing both average conditions and temporal trends. Area . Number of years adequate data OHa . Number of years adequate data RCDb . Annual sampling intensity (# weeks) . Start annual sampling (week #)c . End annual sampling period (week #)c . CDD spring/summerd . CDD fall/winterd . SCB 14 13 x = 5.4 x = 19.0 x = 25.7 x = 690 x = 150 Min = 2 Min = 18 Min = 24 Max = 9 Max = 20 Max = 27 Slope = −0.68 Slope = 3.12 ENB 14 8 x = 4.2 x = 19.6 x = 25.3 x = 896 x = 234 Min = 1 Min = 18 Min = 23 Max = 9 Max = 23 Max = 27 Slope = −2.05 Slope = 3.53 The eastern NS 24 21 x = 5.2 x = 19.9 x = 26.6 x = 1 308 x = 329 Min = 2 Min = 18 Min = 25 Max = 10 Max = 22 Max = 28 Slope = −2.65 Slope = 3.69 The NPEI 25 23 x = 6.9 x = 19.0 x = 26.3 x = 721 x = 257 Min = 2 Min = 18 Min = 25 Max = 9 Max = 21 Max = 28 Slope = −2.02 Slope = 3.40 Area . Number of years adequate data OHa . Number of years adequate data RCDb . Annual sampling intensity (# weeks) . Start annual sampling (week #)c . End annual sampling period (week #)c . CDD spring/summerd . CDD fall/winterd . SCB 14 13 x = 5.4 x = 19.0 x = 25.7 x = 690 x = 150 Min = 2 Min = 18 Min = 24 Max = 9 Max = 20 Max = 27 Slope = −0.68 Slope = 3.12 ENB 14 8 x = 4.2 x = 19.6 x = 25.3 x = 896 x = 234 Min = 1 Min = 18 Min = 23 Max = 9 Max = 23 Max = 27 Slope = −2.05 Slope = 3.53 The eastern NS 24 21 x = 5.2 x = 19.9 x = 26.6 x = 1 308 x = 329 Min = 2 Min = 18 Min = 25 Max = 10 Max = 22 Max = 28 Slope = −2.65 Slope = 3.69 The NPEI 25 23 x = 6.9 x = 19.0 x = 26.3 x = 721 x = 257 Min = 2 Min = 18 Min = 25 Max = 9 Max = 21 Max = 28 Slope = −2.02 Slope = 3.40 a OH was the first calendar week when ovigerous females with prehatch and/or hatching clutches were observed. b RCD was the rate of increase in the ratio of ovigerous females with prehatching/hatching: developing clutches through the spring each year. c The start and end of the sampling period are given in calendar weeks. d Slopes show the interannual trends in seasonal CDDs. SCB: southern Chaleur Bay. Open in new tab Table 1. Summary of sampling conditions in each of our four study areas, including the number of years with adequate data to estimate the two metrics of the timing of hatching (OH and RCD), the timing of the sampling period, as well as temperature conditions in terms of CDDs (3.4°C threshold) in spring–summer (April–September) and fall–winter (October–March) months, showing both average conditions and temporal trends. Area . Number of years adequate data OHa . Number of years adequate data RCDb . Annual sampling intensity (# weeks) . Start annual sampling (week #)c . End annual sampling period (week #)c . CDD spring/summerd . CDD fall/winterd . SCB 14 13 x = 5.4 x = 19.0 x = 25.7 x = 690 x = 150 Min = 2 Min = 18 Min = 24 Max = 9 Max = 20 Max = 27 Slope = −0.68 Slope = 3.12 ENB 14 8 x = 4.2 x = 19.6 x = 25.3 x = 896 x = 234 Min = 1 Min = 18 Min = 23 Max = 9 Max = 23 Max = 27 Slope = −2.05 Slope = 3.53 The eastern NS 24 21 x = 5.2 x = 19.9 x = 26.6 x = 1 308 x = 329 Min = 2 Min = 18 Min = 25 Max = 10 Max = 22 Max = 28 Slope = −2.65 Slope = 3.69 The NPEI 25 23 x = 6.9 x = 19.0 x = 26.3 x = 721 x = 257 Min = 2 Min = 18 Min = 25 Max = 9 Max = 21 Max = 28 Slope = −2.02 Slope = 3.40 Area . Number of years adequate data OHa . Number of years adequate data RCDb . Annual sampling intensity (# weeks) . Start annual sampling (week #)c . End annual sampling period (week #)c . CDD spring/summerd . CDD fall/winterd . SCB 14 13 x = 5.4 x = 19.0 x = 25.7 x = 690 x = 150 Min = 2 Min = 18 Min = 24 Max = 9 Max = 20 Max = 27 Slope = −0.68 Slope = 3.12 ENB 14 8 x = 4.2 x = 19.6 x = 25.3 x = 896 x = 234 Min = 1 Min = 18 Min = 23 Max = 9 Max = 23 Max = 27 Slope = −2.05 Slope = 3.53 The eastern NS 24 21 x = 5.2 x = 19.9 x = 26.6 x = 1 308 x = 329 Min = 2 Min = 18 Min = 25 Max = 10 Max = 22 Max = 28 Slope = −2.65 Slope = 3.69 The NPEI 25 23 x = 6.9 x = 19.0 x = 26.3 x = 721 x = 257 Min = 2 Min = 18 Min = 25 Max = 9 Max = 21 Max = 28 Slope = −2.02 Slope = 3.40 a OH was the first calendar week when ovigerous females with prehatch and/or hatching clutches were observed. b RCD was the rate of increase in the ratio of ovigerous females with prehatching/hatching: developing clutches through the spring each year. c The start and end of the sampling period are given in calendar weeks. d Slopes show the interannual trends in seasonal CDDs. SCB: southern Chaleur Bay. Open in new tab Study areas and temperature data The sGSL was divided into four areas (Figure 2) based on spatial variation in seasonal CDDs (Table 1; J. Chassé, DFO, pers. comm. 2015), with outer boundaries of each area (distance from shore) being determined by the locations from which ovigerous females were sampled (Comeau et al., 2008). The four areas were the south shore of Chaleur Bay (SCB), eastern New Brunswick (ENB), the Northumberland Strait (NS), and the north shore of Prince Edward Island (NPEI; Figure 2). All data originating from a same area were pooled. In the two largest areas (NS and NPEI), 4–13 ports were sampled annually, whereas in the two smaller areas (SCB, ENB), 2–3 ports were sampled annually. Between 600 and 1100 traps were hauled weekly for an average 4–7 weeks annually in the different areas. For each area, years with fewer than 3 weeks sampled were excluded from analyses. An average of 250 and 1300 ovigerous females were sampled weekly and annually, respectively. Although the range of years sampled was 1989–2014, not every year was sampled in each area; the total number of years sampled ranged from 8 to 25 (Table 1). The average travelled distance for lobsters in the sGSL is <10 km a year (Comeau and Savoie, 2002a; Bowlby et al., 2007), thus significant movement of females between study areas was likely not a frequent occurrence. Ocean temperature data were obtained from a coupled ice-ocean modelling system. The ocean circulation model is based on the Nucleus for European Modelling of the Ocean (Madec, 2016) and the setup is described in Brickman and Drozdowski (2012). The ice model is LIM2 (Madec et al., 1998; Goosse and Fichefet, 1999) and includes thermodynamic and rheology components. The coupled model domain covers the Gulf of St Lawrence at a horizontal resolution of 1/12° and 46 layers of variable thickness in the vertical. It is a prognostic model, meaning that the temperature and salinity fields are free to evolve with time and are only constrained through open boundary conditions, freshwater runoff, and surface forcing. Monthly temperature and salinity climatologies were used to initialize the model and set the open boundary conditions. The model is driven with the National Centers for Environmental Prediction atmospheric forcing (winds, heat fluxes), as well as tides and river runoff from the 78 main rivers discharging within the model domain. The model was calibrated to reproduce the main features of the system, like the seasonal cycle of temperature, circulation, and sea ice (Chassé et al., 2014a). Simulations have been carried out for 1948–2015 and provide a long time-series of simulated ocean variables over the domain. For our analysis, bottom temperatures were averaged daily within each study area (one datum per day per study area) to provide time-series starting 2 years prior to the biological data and cover different time periods potentially consequential to hatching time. Indices for the timing of egg hatching Given that sampling was restricted to the commercial fishing season, we were unable to directly assess temporal changes in the peak larval hatching period of July and August (Ennis, 1995; Waddy and Aiken, 1995; Miller et al., 2016) as the fishing seasons end prior to this. As such, we assessed temporal changes in the timing of hatching through two indirect metrics: (i) the change in ratio of ovigerous females with stages 3 + 4 (prehatch and hatching) to stages 1 + 2 (developing) clutches each spring and (ii) the first week in spring when females with prehatch/hatching clutches were observed. The latter is a coarse measure of hatching time and will be referred to as the “onset-of-hatching” (OH). This index was corrected for year–area combinations with prehatch/hatching clutches observed on the first sampling date by adjusting to first sampling week minus one and for year–area combinations with no hatching observed by adjusting to the final sampling week plus one. The rate of increase in the occurrence of females with prehatch/hatching clutches relative to females with developing clutches (i.e. the slope of the ratio prehatch/hatching: developing vs. date) was used as an indicator of the site-level “rate of clutch development” (RCD) in the spring following the winter diapause each year. Based on the premise that a more rapid progression from developing to prehatch/hatching clutches in the spring should result in earlier hatching of larvae, we suggest that change in RCD across years reflects population-level changes in the hatching period. For each year, we calculated the ratio of ovigerous females with prehatch/hatching to developing clutches for each sampling week in each area, and then took the slope of log-transformed ratios over time as the RCD for that particular area and year. For weeks when only prehatch/hatching clutches were observed, we substituted a value of 1 for the zero count of developing clutches to allow a ratio to be estimated. Similarly, for weeks when no prehatch/hatching clutches were observed we substituted 0 counts with 0.5 to ensure a ratio >0; 0.5 was chosen rather than 1 as a single female with a prehatch/hatching clutch was observed several times in the dataset and the substituted value needs be smaller than the range of observed values. The earliest sampling week in any given year was week 18 (early May), but we added week 15 (mid-April) as a forced zero to reflect the fact that all clutches are in diapause in the developmental phase (stage 2) through winter. Week 15 was chosen as modelled bottom temperature then consistently averaged ∼0°C (−1.7° to 0.9°), that is no embryonic development would be occurring. We set the ratio of prehatch/hatching to developing clutches at this forced zero to 0.0010, to be just below the lowest observed ratio of 0.0011. We only calculated the RCD for year–area combinations with a minimum of three sampling weeks and R2 > 0.4; the latter excluded 6 of 70 data points. Statistical analyses Evidence of an advancing hatching period between 1989 and 2014 was investigated using linear regressions, where RCD and OH were the dependent variables regressed against year, with geographic area set as a random factor. Effects of temperature were compared using similar linear models with additional parameters reflecting CDDs experienced by lobsters over four broad time periods that may be important to ovarian and embryonic development: (i) fall–winter 1.5 years preceding hatching (primary vitellogenesis with a transition to secondary vitellogenesis), (ii) spring–summer the year preceding hatching (late secondary vitellogenesis and spawning), (iii) fall–winter the year preceding hatching (early embryonic development), and (iv) spring prior to hatching (late embryonic development). We built and compared 32 models (including a null model with no temperature term) for each of the 2 hatching metrics, based on all combinations of the 4 temperature parameters and an area term. Models were compared using the corrected akaike information criterion (AICc) to determine which thermal periods (if any) are the most influential on hatching time. Area was used as a random term in these models as well (intercepts assumed random, slopes assumed fixed) as our aim was to assess general trends for the sGSL, and grouping the data in areas enabled us to account for some of the variability in our dependent variables that might be related to differences in biotic and abiotic conditions in these areas. We used 3.4°C as the threshold for degree-days, given embryonic development below this temperature is limited (Perkins, 1972). Model residuals were tested for normality using Shapiro–Wilk W goodness-of-fit tests and generally did not violate this assumption (p < 0.05). Results Our results suggest that female lobsters have been hatching their eggs earlier in the season between 1989 and 2014 in the sGSL, as there has been a significant increase in the spring RCD (F1,86.95 = 14.52; R2 = 0.12, p = 0.0003; Figure 4a) and a significant advancement of the OH (F1,79.32 = 35.16; R2 = 0.34, p < 0.0001; Figure 4b) over the study period. Based on the model slopes, RCD occurred 1.4 times more rapidly, and OH 5 weeks earlier in 2014 compared to 1989. Figure 4. Open in new tabDownload slide Temporal trends in two indices of the timing of hatching 1989–2014 in four study areas in the southern Gulf of St Lawrence: (a) RCD, indicated by the rate of change in ratios of ovigerous females with mature vs. immature clutches (stages 3–4 vs. 1–2) through the spring fishing season each year (F1,86.95 = 14.52; p = 0.0003); (b) onset-of-hatching, indicated by the first calendar week when ovigerous females with mature or hatching clutches were observed each year (F1,79.32 = 35.16; p < 0.0001). Figure 4. Open in new tabDownload slide Temporal trends in two indices of the timing of hatching 1989–2014 in four study areas in the southern Gulf of St Lawrence: (a) RCD, indicated by the rate of change in ratios of ovigerous females with mature vs. immature clutches (stages 3–4 vs. 1–2) through the spring fishing season each year (F1,86.95 = 14.52; p = 0.0003); (b) onset-of-hatching, indicated by the first calendar week when ovigerous females with mature or hatching clutches were observed each year (F1,79.32 = 35.16; p < 0.0001). Modelled bottom temperature in the sGSL shows a significant increase in the number of degree-days in the fall between 1989 and 2014 (year: F1,96 = 64.62, p < 0.0001; area: F3,96 = 160.24, p < 0.0001; area × year: F3,96 = 0.08, p = 0.97). In contrast, the number of degree-days in the spring has not changed over the same period (year: F1,96 = 0.0025, p = 0.96; area: F3,96 = 86.94, p < 0.0001; area × year: F3,96 = 0.28, p = 0.84), and the number of degree-days in the summer has actually somewhat decreased (year: F1,96 = 8.23, p = 0.005; area: F3,96 = 541.08, p < 0.0001; area × year: F3,96 = 0.79, p = 0.50; Figure 5; Table 1). The temperature increase during the fall has been pronounced, representing 20–60% more CDDs from 1989 to 2014 in different areas, in contrast to a 5–15% reduction in the summer. As temperatures during winter consistently did not surpass 3.4°C, the resulting in constant zero-valued CDDs was not included as model predictors. Figure 5. Open in new tabDownload slide Temporal trends (1989–2014) in CDDs > 3.4°C in spring (April–June), summer (July–September), and fall (October–December); winter (January–March is not shown as CDD never exceeded 0). There are clear spatial differences in CDD in all three seasons (spring: F5,144 = 70.67, p < 0.0001; summer: F5,144 = 318.00, p < 0.0001; fall: F5,144 = 168.48, p < 0.0001), but only fall CDD shows an increase over the study period (F1,144 = 87.44, p < 0.0001); spring CDD shows no temporal trends (F1,144 = 0.21, p = 0.65); summer CDD shows a slight negative trend (F1,144 = 13.81, p = 0.0003); all these temporal trends, or lack thereof, are consistent among areas (i.e. no significant areas × year interaction term; spring: F5,144 = 0.32, p = 0.90; summer: F5,144 = 0.78, p = 0.56; fall: F5,144 = 0.39, p = 0.86). Figure 5. Open in new tabDownload slide Temporal trends (1989–2014) in CDDs > 3.4°C in spring (April–June), summer (July–September), and fall (October–December); winter (January–March is not shown as CDD never exceeded 0). There are clear spatial differences in CDD in all three seasons (spring: F5,144 = 70.67, p < 0.0001; summer: F5,144 = 318.00, p < 0.0001; fall: F5,144 = 168.48, p < 0.0001), but only fall CDD shows an increase over the study period (F1,144 = 87.44, p < 0.0001); spring CDD shows no temporal trends (F1,144 = 0.21, p = 0.65); summer CDD shows a slight negative trend (F1,144 = 13.81, p = 0.0003); all these temporal trends, or lack thereof, are consistent among areas (i.e. no significant areas × year interaction term; spring: F5,144 = 0.32, p = 0.90; summer: F5,144 = 0.78, p = 0.56; fall: F5,144 = 0.39, p = 0.86). The model that best explained interannual variation in RCD included the parameters CDD during spring–summer 1 year prior to hatching (i.e. secondary vitellogenesis and spawning) and CDD during fall–winter prior to hatching (i.e. early embryogenesis). This model composed 21% of the AICc weight of the 32 models compared (Table 2). Overall, the model was significant (F2,68 = 3.86, p = 0.026) with R2 = 0.10. It showed a positive relationship between CDD during early embryogenesis and RCD (F1,68 = 2.76, p = 0.007), indicating warmer water during the first months after spawning results in a more rapid RCD leading to hatching the following spring. The model also showed a negative relationship between CDD during secondary vitellogenesis and spawning and RCD (F1,68 = −1.61, p = 0.11), suggesting a warmer summer the year of spawning results in slower RCD, and presumably later hatching, the following year (Table 2). CDD during early embryogenesis accounted for considerably more of the variation in RCD explained by the model than did CDD during spawning (75 and 25%, respectively). The second-best model (AICc weight = 17%, Delta < 2) included only CDD during early embryogenesis (Table 2). Table 2. AIC model selection for spatial and temporal variation in the RCD in relation to temperature during different phases of the reproductive cycle. Modelsa . Parameter estimateb . kc . AICc . Δd . AICc weighte (%) . CDD spawning −4.646e−5 3 −219.61 0.00 20.9 CDD early embryogenesis 0.000283 CDD early embryogenesis 0.000017 2 −219.19 0.42 16.9 CDD early embryogenesis 0.000242 3 −218.37 1.25 11.2 CDD late embryogenesis −0.000121 CDD gametogenesis 0.000144 2 −217.52 2.10 7.3 CDD spawning −5.570e−5 4 −217.35 2.26 6.7 CDD early embryogenesis 0.000282 CDD late embryogenesis 4.024e−5 Modelsa . Parameter estimateb . kc . AICc . Δd . AICc weighte (%) . CDD spawning −4.646e−5 3 −219.61 0.00 20.9 CDD early embryogenesis 0.000283 CDD early embryogenesis 0.000017 2 −219.19 0.42 16.9 CDD early embryogenesis 0.000242 3 −218.37 1.25 11.2 CDD late embryogenesis −0.000121 CDD gametogenesis 0.000144 2 −217.52 2.10 7.3 CDD spawning −5.570e−5 4 −217.35 2.26 6.7 CDD early embryogenesis 0.000282 CDD late embryogenesis 4.024e−5 a The RCD was indicated by the change in ratios of ovigerous females with prehatch/hatching (stages 3–4) vs. developing (stages 1–2) clutches through the spring each year. Temperature considered was CDDs > 3.4°C over 6-month periods spring/summer (April–September) and fall/winter (October–March) starting from the spring of sampling immediately prior to larvae hatching (summer months excl.) and going back to the fall/winter 3 years prior when the onset of ovarian development began. b Parameter estimates (coefficients) are given for temperature indices only; intercepts are not shown. c k indicates the number of parameters in each model (the number of variables plus intercept). d The best-fit model is indicated by the lowest AICc value (Δ = 0). e AICc weights indicate the relative support received by the different models based on the data. Only the top 5 out of the 32 models compared are shown, yet weights were calculated in relation to all 32 models compared (all combinations of 4 seasons and area terms). Open in new tab Table 2. AIC model selection for spatial and temporal variation in the RCD in relation to temperature during different phases of the reproductive cycle. Modelsa . Parameter estimateb . kc . AICc . Δd . AICc weighte (%) . CDD spawning −4.646e−5 3 −219.61 0.00 20.9 CDD early embryogenesis 0.000283 CDD early embryogenesis 0.000017 2 −219.19 0.42 16.9 CDD early embryogenesis 0.000242 3 −218.37 1.25 11.2 CDD late embryogenesis −0.000121 CDD gametogenesis 0.000144 2 −217.52 2.10 7.3 CDD spawning −5.570e−5 4 −217.35 2.26 6.7 CDD early embryogenesis 0.000282 CDD late embryogenesis 4.024e−5 Modelsa . Parameter estimateb . kc . AICc . Δd . AICc weighte (%) . CDD spawning −4.646e−5 3 −219.61 0.00 20.9 CDD early embryogenesis 0.000283 CDD early embryogenesis 0.000017 2 −219.19 0.42 16.9 CDD early embryogenesis 0.000242 3 −218.37 1.25 11.2 CDD late embryogenesis −0.000121 CDD gametogenesis 0.000144 2 −217.52 2.10 7.3 CDD spawning −5.570e−5 4 −217.35 2.26 6.7 CDD early embryogenesis 0.000282 CDD late embryogenesis 4.024e−5 a The RCD was indicated by the change in ratios of ovigerous females with prehatch/hatching (stages 3–4) vs. developing (stages 1–2) clutches through the spring each year. Temperature considered was CDDs > 3.4°C over 6-month periods spring/summer (April–September) and fall/winter (October–March) starting from the spring of sampling immediately prior to larvae hatching (summer months excl.) and going back to the fall/winter 3 years prior when the onset of ovarian development began. b Parameter estimates (coefficients) are given for temperature indices only; intercepts are not shown. c k indicates the number of parameters in each model (the number of variables plus intercept). d The best-fit model is indicated by the lowest AICc value (Δ = 0). e AICc weights indicate the relative support received by the different models based on the data. Only the top 5 out of the 32 models compared are shown, yet weights were calculated in relation to all 32 models compared (all combinations of 4 seasons and area terms). Open in new tab The model that best explained variation in OH included the parameters CDD during the fall–winter prior to spawning (i.e. primary vitellogenesis with a transition to secondary vitellogenesis ∼1.5 years prior to OH) and CDD during the spring–summer 1 year prior to hatching (i.e. secondary vitellogenesis and spawning; Table 3). This model composed 50% of the AICc weight of the 32 models compared (Table 3). Overall, the model was highly significant (F2,79 = 9.94, p < 0.0001) with R2 = 0.20. The model showed a negative relationship between OH and CDD during primary vitellogenesis with a transition to secondary vitellogenesis (F1,79 = −4.26, p < 0.0001), indicating that higher temperature during the fall–winter prior to spawning results in earlier OH. The model also showed a positive relationship between OH and CDD during secondary vitellogenesis and spawning (F1,79 = 3.82, p < 0.0001), indicating that higher temperature at this time delays OH the following year (Table 3). CDD during primary vitellogenesis with a transition to secondary vitellogenesis accounted for slightly more of the variance in OH explained by the model than did CDD during secondary vitellogenesis and spawning (57 and 43%, respectively). Table 3. AIC model selection for trends in OH in relation to temperature during different phases of the reproductive cycle. Modelsa . Parameter estimateb . kc . AICc . Δd . AICc weighte(%) . CDD gametogenesis −0.022914 3 401.43 0.00 49.7 CDD spawning 0.005620 CDD gametogenesis −0.023081 4 403.60 2.16 16.9 CDD spawning 0.005012 CDD late embryogenesis 0.002822 CDD gametogenesis −0.021342 4 403.65 2.21 16.5 CDD spawning 0.005716 CDD early embryogenesis −0.002032 CDD gametogenesis −0.019378 3 405.71 4.27 5.9 CDD late embryogenesis 0.017390 CDD gametogenesis −0.021637 5 405.88 4.45 5.4 CDD spawning 0.005127 CDD early embryogenesis −0.001857 CDD late embryogenesis 0.002695 Modelsa . Parameter estimateb . kc . AICc . Δd . AICc weighte(%) . CDD gametogenesis −0.022914 3 401.43 0.00 49.7 CDD spawning 0.005620 CDD gametogenesis −0.023081 4 403.60 2.16 16.9 CDD spawning 0.005012 CDD late embryogenesis 0.002822 CDD gametogenesis −0.021342 4 403.65 2.21 16.5 CDD spawning 0.005716 CDD early embryogenesis −0.002032 CDD gametogenesis −0.019378 3 405.71 4.27 5.9 CDD late embryogenesis 0.017390 CDD gametogenesis −0.021637 5 405.88 4.45 5.4 CDD spawning 0.005127 CDD early embryogenesis −0.001857 CDD late embryogenesis 0.002695 a OH was indicated by the first calendar week with ovigerous females with prehatch/hatching (stages 3–4) observed each year. Temperature considered was CDDs > 3.4°C over 6-month periods spring/summer (April–September) and fall/winter (October–March) starting from the spring of sampling immediately prior to larvae hatching (summer months excl.) and going back to the fall/winter 3 years prior when the onset of ovarian development began. b Parameter estimates (coefficients) are given for temperature indices only; intercepts are not shown. c k indicates the number of parameters in each model (the number of variables plus intercept). d The best-fit model is indicated by the lowest AICc value (Δ = 0). e AICc weights indicate the relative support received by the different models based on the data. Only the top 5 out of the 32 models compared are shown, yet weights were calculated in relation to all 32 models compared (all combinations of 4 seasons and area terms). Open in new tab Table 3. AIC model selection for trends in OH in relation to temperature during different phases of the reproductive cycle. Modelsa . Parameter estimateb . kc . AICc . Δd . AICc weighte(%) . CDD gametogenesis −0.022914 3 401.43 0.00 49.7 CDD spawning 0.005620 CDD gametogenesis −0.023081 4 403.60 2.16 16.9 CDD spawning 0.005012 CDD late embryogenesis 0.002822 CDD gametogenesis −0.021342 4 403.65 2.21 16.5 CDD spawning 0.005716 CDD early embryogenesis −0.002032 CDD gametogenesis −0.019378 3 405.71 4.27 5.9 CDD late embryogenesis 0.017390 CDD gametogenesis −0.021637 5 405.88 4.45 5.4 CDD spawning 0.005127 CDD early embryogenesis −0.001857 CDD late embryogenesis 0.002695 Modelsa . Parameter estimateb . kc . AICc . Δd . AICc weighte(%) . CDD gametogenesis −0.022914 3 401.43 0.00 49.7 CDD spawning 0.005620 CDD gametogenesis −0.023081 4 403.60 2.16 16.9 CDD spawning 0.005012 CDD late embryogenesis 0.002822 CDD gametogenesis −0.021342 4 403.65 2.21 16.5 CDD spawning 0.005716 CDD early embryogenesis −0.002032 CDD gametogenesis −0.019378 3 405.71 4.27 5.9 CDD late embryogenesis 0.017390 CDD gametogenesis −0.021637 5 405.88 4.45 5.4 CDD spawning 0.005127 CDD early embryogenesis −0.001857 CDD late embryogenesis 0.002695 a OH was indicated by the first calendar week with ovigerous females with prehatch/hatching (stages 3–4) observed each year. Temperature considered was CDDs > 3.4°C over 6-month periods spring/summer (April–September) and fall/winter (October–March) starting from the spring of sampling immediately prior to larvae hatching (summer months excl.) and going back to the fall/winter 3 years prior when the onset of ovarian development began. b Parameter estimates (coefficients) are given for temperature indices only; intercepts are not shown. c k indicates the number of parameters in each model (the number of variables plus intercept). d The best-fit model is indicated by the lowest AICc value (Δ = 0). e AICc weights indicate the relative support received by the different models based on the data. Only the top 5 out of the 32 models compared are shown, yet weights were calculated in relation to all 32 models compared (all combinations of 4 seasons and area terms). Open in new tab Discussion Timing of egg hatching in the sGSL Results of this study provide strong evidence that female American lobsters in the sGSL have been releasing their larvae progressively earlier since 1989. First, the change in ratio of prehatch/hatching (stages 3–4) to developing (stages 1–2) clutches through the spring fishing season, which we refer to as the RCD, occurs on average 40% faster across the study domain now than it did 25 years ago. Second, we showed that the first appearance of ovigerous females with prehatch or hatching clutches, which we refer to as the OH, was observed on average 5 weeks earlier. Both the RCD and OH metrics were subject to limited sampling intensity and the constraint of the relatively short time window of the spring fishing season. This was particularly true for OH. For example, OH was recorded as the first week of sampling in 30–60% of years sampled in different areas. The frequency with which this occurred increased later in the study period [33%, 46%, and 67% of cases (year–area combination) in 1989–1997, 1998–2005, and 2006–2014, respectively], which means that we likely underestimated the true advancement in OH. Also, there were five instances from 1989 to 1991 when no females with prehatch/hatching clutches were reported during the fishing season. This was consistent with later hatching during the earlier part of our survey and further suggests that our data likely underreport the true advancement of hatching. Temporal trends in temperature and their effect on the timing of hatching We found evidence that temperature during the female reproductive cycle influences the timing of hatching of lobster larvae in the sGSL, which is not surprising given that several aspects of lobster biology and reproduction are under thermal regulation (Waddy and Aiken, 1995). The rate of embryonic development increases with temperature (Perkins, 1972), and up to 80% of the embryogenesis can be completed prior to winter (Gendron and Ouellet, 2009). Because CDD in the fall has increased over the past 25 years, early embryonic development following spawning (and prior to winter diapause) is expected to have been accelerated over the this time period, which is supported by our results. Temperature during vitellogenesis also seems to play a role in regulating hatching time. Rising temperature in the fall may affect not only early embryonic development but also ovarian development, as suggested by the relationship between OH and CDD 1.5 years prior to hatching. Primary vitellogenesis occurs over several months in the spring, summer, and fall the year before spawning, resulting in a slow increase in ovarian size before the ovary enters a winter diapause period (Aiken and Waddy, 1980; Comeau and Benhalima, 2018). It has been assumed that secondary vitellogenesis only begins the following spring, prior to summer spawning (Aiken and Waddy, 1980; Waddy and Aiken, 1995), but recent monitoring of ovarian development in the sGSL indicates that secondary vitellogenesis is well underway in the fall prior to spawning (Comeau and Benhalima, 2018). We propose that the mechanism behind the relationship between temperature during the fall prior to spawning and an early OH ∼1.5 years later is an increase in fall CDD allowing the earlier completion of primary vitellogenesis and greater progression of secondary vitellogenesis prior to the winter diapause. Furthermore, warmer water during the transition from primary vitellogenesis to secondary vitellogenesis may lead to an earlier spawning, amplifying the effects of more CDD available for embryonic development in the fall a year later. In contrast with the CDD observed in fall that positively influence the ovarian and embryonic development, higher spring–summer temperature the year of spawning was associated with slower RCD and later OH the following year. It was expected that lower CDD in spring–summers results in delayed secondary vitellogenesis and spawning (Aiken and Waddy, 1980, 1982), and thus delayed hatching as well. The observation that hatching is earlier despite cooler springs–summers may suggest that temperature at this time has limited effect on spawning time, which is consistent with the fact that it was the weakest contributor to model predictive ability. As the onset of secondary vitellogenesis has been observed in fall prior to the winter diapause in the sGSL (Comeau and Benhalima, 2018), our findings suggest that CDD in fall rather than in spring/summer has a greater influence on spawning and hatching. Given the positive relation shown in the lab between temperature and late development of lobster embryos (Perkins, 1972; Gendron and Ouellet, 2009), as well as the ability to predict hatching in nature based on spring temperature and temperature-based embryonic development functions (Miller et al., 2016), the lack of a relationship between interannual variation in spring temperature and our two metrics of hatching time was unexpected. The lack of relationship may be because of an imperfect temporal and/or spatial match between our temperature (daily from April to June over entire area) and biological (ovigerous females sampled in May and June in parts of each area) data and/or errors in the modelled temperature data in shallow coastal areas. Alternatively, it may reflect an adaptation to unpredictable spring temperature. Temperature is considerably more variable in June than in September in the sGSL (Chassé et al., 2014b). Modelled temperature in our study showed interannual variation of 30% around the mean CDD in spring, compared to only 10% in the fall. The ability for embryos to progress to hatching independently of spring temperature may be an adaptive response to unpredictable spring conditions. This interpretation is supported by the observation that American lobster embryos may hatch anytime from 50% development onwards, based on observations of the Perkins Eye Index (Perkins, 1972) of prezoeae (hatchlings not yet moulted to stage I larvae) in relation to the embryonic moult cycle documented by Helluy and Beltz (1991). This suggests that embryos may have the ability to deplete their yolk reserves and proceed to hatching irrespective (to some degree) of the degree-days available for embryogenesis during spring. Given that many aspects of lobster biology are regulated by temperature to some degree, including size-at-maturity and moulting (Waddy et al., 1995), it is not inconceivable that changes to temperature-mediated processes other than vitellogenesis have contributed to the temporal trends in lobster hatch documented in this study. Female size-at-maturity has in fact declined in large parts of eastern Canada and the Gulf of Maine over the past 20–80 years (Haarr et al., 2018; Le Bris et al., 2018). However, such declines have not occurred in the sGSL during the time period of this study (Haarr et al., 2018). There was evidence of a small decrease (≈4 mm in CL) in average size of ovigerous females over our study period (results not shown), but this is unlikely to explain the advancement in hatching time we documented as smaller females consistently release their larvae later (not earlier) than larger females in hatcheries in the sGSL (M. Mallet, Maritime Fishermen Union, Shediac, Canada, pers. comm.). Nor does it seem likely that the temporal trend in hatching time is related to changes to the moulting cycle, as the cold spring temperatures in the sGSL [−1.6°C from December to April (Hanson and Courtenay, 1996)] leave little opportunity for advancement of moulting; soft-shelled lobsters have never been encountered in the past 35 years of the spring fishery survey (ends ≈30 June) upon which this study is based (M. Comeau, Fisheries and Oceans Canada, unpublished data). There are no other empirical data on changes in hatching time of American lobster over a similar time period with which to compare our results. The most comparable data are from a recent study in the Magdalen Islands, in the central Gulf of St Lawrence, in which hatching time of lobster was retro-calculated based on estimated settlement date and water temperature during the larval period. This study suggested that hatching may have moved to later in the season between 1997 and 2013, opposite to what was documented in this study, although the relationship was weak (R2 = 0.18) and not statistically significant (p = 0.09; Gendron et al., 2019). There is also uncertainty associated with this retro-estimation of hatching time related to factors other than temperature that may affect interannual variability in larval development (e.g. differences in larval food supply). The seemingly contradictory results are nevertheless surprising. Fall temperatures have increased around the Magdalen Islands 1994–2013, just as in the sGSL, but spring temperatures have also increased and there has been no trend in summer temperatures (Galbraith et al., 2014), neither which was the case for the sGSL. Consequently, the thermal changes around the Magdalen Islands differ somewhat from those in the sGSL, which may explain this evidence for opposite temporal trends in lobster hatching time in these two regions. Further research is clearly needed to confirm and explain these phenological changes. Effects of an earlier timing of hatching Based on the presence of stage I larvae in the water column, hatching is generally thought to peak between mid-July and mid-August in the sGSL (Chassé and Miller, 2010). There are considerable potential ecological implications if hatching peaks earlier in the season in response to environmental conditions that occur 6–18 months prior to hatching. Survival of larvae is assumed to be very low, generally <2% (Harding et al., 1982; Incze, 2000; Chassé and Miller, 2010), and thus likely important to benthic recruitment. Rising water temperature, within the bounds of physiological limits, is likely positive during the pelagic larval phase as it results in more rapid development and settlement, and hence reduced exposure to pelagic predators and offshore drift (MacKenzie, 1988; Xue et al., 2008; Pershing et al., 2012). However, we documented an earlier larval release that does not appear to be associated with an increase in spring–summer temperature, suggesting that larvae may now be released into colder water (there was a significant negative temporal trend in average temp during the week of OH in two of our four study areas, results not shown), and hence might experience slower development, greater dispersal, and greater mortality than 25 years ago. To the best of our knowledge, these three hypotheses cannot be tested directly, given the sparse data on lobster larvae in the sGSL. The third of these hypotheses is not consistent with the high levels of lobster settlement in certain regions of the sGSL over the past 5–6 years (DFO, 2016b). It must be noted, however, that the linkage between the pelagic and benthic phases of lobsters is complex (Carloni et al., 2018), and the changes in hatch time documented in this study may ultimately have little incidence on the successful settlement and early survival of stage IV postlarvae relative to other processes. An earlier timing of hatching driven by thermal conditions many months prior to hatching may also have ramifications for larval food supply. Mismatches between prey abundance and larval needs can occur if there are asynchronous changes in phenology across different trophic levels (Cushing, 1990; Visser et al., 1998; Edwards and Richardson, 2004; Durant et al., 2007). American lobster larvae are active predators feeding on a variety of zooplankton and phytoplankton (Ennis, 1995). Given lobster larvae appear to be hatching earlier in the summer mostly because of temperature affecting ovarian and early embryonic development, they may face a temporal mismatch with other zooplankton upon which they prey. It seems unlikely that the lobster prey would have a similar early presence in the plankton, given the shorter life cycles of most zooplankton prey species [∼1 month generation time in copepods (Fransz et al., 1991)]. The phenology of plankton most commonly correlates positively with water temperature immediately prior to and during their growing season (Mackas et al., 2012), and as there is less evidence of warming during spring and summer compared to the fall in the sGSL, plankton may not currently be undergoing the same phenological shift as lobster. A loss of synchronicity between the timing of hatching of lobster larvae and their prey is therefore possible, and similar scenarios have been documented and predicted in various zooplankton, crustaceans, fishes, and birds (Gotceitas et al., 1996; Visser et al., 1998; Edwards and Richardson, 2004; Durant et al., 2007; Asch, 2015; Asch et al., 2019). Food limitation is generally not believed to be an important factor in the mortality of lobster larvae (Ennis, 1995). However, if the timing of hatching is altered, resulting in a decoupling between peak prey abundance and lobster larval release, starvation from food limitation could result in high mortality and jeopardize benthic recruitment. Further research into the plankton dynamics of the sGSL is necessary to investigate this possibility. An earlier OH also has the potential to affect larval drift trajectories and connectivity patterns, not only through altering the duration of the pelagic phase, and thus drift time, but also by exposing the larvae to different currents (Xue et al., 2008; Chassé and Miller, 2010; Quinn, 2014). Larval drift modelling in the sGSL predicts significantly lower survival for larvae released in locations where the peak hatching period occurs earlier in summer (Chassé and Miller, 2010), and there is some empirical evidence of lower survival of early hatched larvae (Miller, 1997). Wind and weather patterns also vary seasonally and earlier hatching may expose larvae to different wind-driven surface currents not otherwise experienced during the pelagic phase, which has been shown to have a great effect on spatial and temporal patterns in postlarval supply and settlement (Harding et al., 1982; Wahle and Incze, 1997; Incze, 2000; Pershing et al., 2012; Quinn et al., 2017). Seasonal variation in temperature and currents in the sGSL is predicted to result in variation in drift time and distance up to 1 month and 100 km, respectively, for larvae released at different times in a 5-week window during the summer, and up to >2 months and >300 km over a 10-week window (B. Quinn and M.L. Haarr, unpublished data). Thus, it seems clear that even relatively modest changes in the timing of hatching have the potential to alter connectivity patterns and survival of larvae. This study provides compelling evidence that the timing of hatching for American lobster larvae in the sGSL has advanced over the past ≈25 years (1989–2014). The relatively narrow annual at-sea sampling during the spring fishery (May–June) likely masked the extent of the temporal shift to earlier hatching in the sGSL. The implications of the changes in phenology we document are not clear but could produce adverse effects for the fishery. Hatching earlier in the season most likely results in larvae being exposed to colder water, causing prolonged development and potentially reduced larval survival (MacKenzie, 1988; Quinn et al., 2013). Such an effect could be amplified if larval survival is further reduced by changes in food availability following a possible loss of synchronicity with prey species. Earlier hatching will also result in increased catch rates and handling of females with more-loosely attached embryos, as the clutches of a greater proportion of ovigerous females will reach prehatch/hatching stages before the end of the spring fishing season. Given that eggs are more readily lost from a female’s abdomen in prehatch clutches than from developing ones (Talbot et al., 1984), increased handling of females whilst their clutches are close to hatching may result in increased egg loss and negatively affect larval supply (Tang et al., 2018). Further research into effects of climate change on lobster phenology is clearly warranted, particularly with respect to the potential effects of earlier hatching on larval survival and benthic recruitment. Acknowledgements This research was part of the Canadian Fisheries Research Network's Lobster Node, and it was made possible through the lobster fishery at-sea-sampling programme of Fisheries and Oceans Canada in the southern Gulf of St Lawrence. M.L.H was supported by an NSERC Discovery grant and an NBIF Research Innovation Fund grant to R.R. References Adiyodi R. G. 1985 . Reproduction and its control. In Integument, Pigments, and Hormonal Processes, pp. 147 – 215 . Ed. by D. E. Bliss and L. H. Mantel. Academic Press Inc., Orlando, Florida. Aiken D. E. , Waddy S. L. 1980 . Reproductive biology. In The Biology and Management of Lobsters , pp. 215 – 276 . Ed. by J. S. Cobb and B. F. Phillips. Academic Press Inc., London, UK . Google Scholar Crossref Search ADS Google Scholar Google Preview WorldCat COPAC Aiken D. E. , Waddy S. L. 1982 . Cement gland development, ovary maturation, and reproductive cycles in the American Lobster Homarus Americanus . Journal of Crustacean Biology , 2 : 315 – 327 . Google Scholar Crossref Search ADS WorldCat Asch R. G. 2015 . Climate change and decadal shifts in the phenology of larval fishes in the California Current ecosystem . Proceedings of the National Academy of Sciences of the United States of America , 112 : E4065 – E4074 . Google Scholar Crossref Search ADS PubMed WorldCat Asch R. G. , Stock C. A., Sarmiento J. L. 2019 . Climate change impacts on mismatches between phytoplankton blooms and fish spawning phenology . Global Change Biology , 25 : 2544 – 2559 . Google Scholar Crossref Search ADS PubMed WorldCat Bowlby H. , Hanson J., Hutchings J. 2007 . Resident and dispersal behavior among individuals within a population of American lobster Homarus americanus . Marine Ecology Progress Series , 331 : 207 – 218 . Google Scholar Crossref Search ADS WorldCat Brickman D. , Drozdowski A. 2012 . Development and Validation of a Regional Shelf Model for Maritime Canada Based on the NEMOOPA Circulation Model. Canadian Technical Report of Hydrography and Ocean Sciences, 278. Fisheries and Oceans Canada. Carloni J. T. , Wahle R., Geoghegan P., Bjorkstedt E. 2018 . Bridging the spawner-recruit disconnect: trends in American lobster recruitment linked to the pelagic food web . Bulletin of Marine Science , 94 : 719 – 735 . Google Scholar Crossref Search ADS WorldCat Cha J.-H. , Martin D., Bhaud M. 1997 . Effects of temperature on oocyte growth in the Mediterranean terebellid Eupolymnia nuebulosa (Annelida: Polychaeta) . Marine Biology , 128 : 433 – 439 . Google Scholar Crossref Search ADS WorldCat Chassé J. , Miller R. J. 2010 . Lobster larval transport in the southern Gulf of St. Lawrence: lobster larval transport . Fisheries Oceanography , 19 : 319 – 338 . Google Scholar Crossref Search ADS WorldCat Chassé J. , Lavoie D., Comeau M., Galbraith P. S., Pettipas R. G. 2014a . A 65 Year (1948-2012) Hindcast of Ice-ocean Dynamics in the Gulf of St. Lawrence. 48th CMOS Conference, Rimouski, QC. Chassé J. , Lambert N., Comeau M., Galbraith P. S., Larouche P., Pettipas R. G. 2014b . Environmental Conditions in the southern Gulf of St. Lawrence Relevant to Lobster. Canadian Science Advisory Secretariat Reserach Document, 2014/031. Fisheries and Oceans Canada. Available from: http://waves-vagues.dfo-mpo.gc.ca/Library/360471.pdf. Comeau M. , Savoie F. 2002a . Movement of American lobster (Homarus americanus) in the southwestern Gulf of St . Lawrence. Fishery Bulletin , 1002 : 181 – 192 . OpenURL Placeholder Text WorldCat Comeau M. , Savoie F. 2002b . Maturity and reproductive cycle of the female American lobster, Homarus Americanus, in the southern Gulf of St. Lawrence, Canada . Journal of Crustacean Biology , 22 : 762 – 774 . Google Scholar Crossref Search ADS WorldCat Comeau M. , Hanson J. M., Rondeau A., Mallet M., Chassé J. 2008 . Framework and Assessment for American lobster, Homarus americanus, Fisheries in the Southern Gulf of St. Lawrence: LFA 23, 24, 25, 26A and 26B. Canadian Science Advisory Secretariat Reserach Document, 2008/054. Fisheries and Oceans Canada. Comeau M. , Benhalima K. 2018 . Functional anatomy of the female reproductive system of the American lobster (Homarus americanus) . Journal of Morphology , 279 : 1603 – 1614 . Google Scholar Crossref Search ADS PubMed WorldCat Cowen R. K. , Sponaugle S. 2009 . Larval dispersal and marine population connectivity . Annual Review of Marine Science , 1 : 443 – 466 . Google Scholar Crossref Search ADS PubMed WorldCat Cushing D. H. 1990 . Plankton production and year-class strength in fish populations: an update of the match/mismatch hypothesis. In Advances in Marine Biology , pp. 249 – 293 . Ed. by J. H. S. Blaxter and A. Southward. Academic Press Inc., Suffolk, UK . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC DFO. 2016a . 2015 Lobster Stock Assessment on the North Shore (LFAs 15, 16 and 18) and at Anticosti Island (LFA 17), Quebec Area. Canadian Science Advisory Secretariat Science Advisory Report 2016/044. Available from: https://waves-vagues.dfo-mpo.gc.ca/Library/40595572.pdf. DFO. 2016b . Update of the Stock Status Indicators for the American lobster (Homarus americanus) Stocks in the Southern Gulf of St. Lawrence. Canadian Science Advisory Secretariat Science Response 2016/051. Fisheries and Oceans Canada. Doney S. C. , Ruckelshaus M., Emmett Duffy J., Barry J. P., Chan F., English C. A., Galindo H. M. et al. 2012 . Climate change impacts on marine ecosystems . Annual Review of Marine Science , 4 : 11 – 37 . Google Scholar Crossref Search ADS PubMed WorldCat Durant J. , Hjermann D., Ottersen G., Stenseth N. 2007 . Climate and the match or mismatch between predator requirements and resource availability . Climate Research , 33 : 271 – 283 . Google Scholar Crossref Search ADS WorldCat Edwards M. , Richardson A. J. 2004 . Impact of climate change on marine pelagic phenology and trophic mismatch . Nature , 430 : 881 – 884 . Google Scholar Crossref Search ADS PubMed WorldCat Ennis G. P. 1995 . Larval and postlarval ecology. In Biology of the Lobster , pp. 23 – 46 . Ed. by J. R. Factor. Academic Press Inc., London, UK . Google Scholar Crossref Search ADS Google Scholar Google Preview WorldCat COPAC Fransz H. G. , Colebrook J. M., Gamble J. C., Krause M. 1991 . The zooplankton of the North Sea . Netherlands Journal of Sea Research , 28 : 1 – 52 . Google Scholar Crossref Search ADS WorldCat Galbraith P. S. , Larouche P., Chassé J., Petrie B. 2012 . Sea-surface temperature in relation to air temperature in the Gulf of St. Lawrence: interdecadal variability and long term trends . Deep Sea Research Part II: Topical Studies in Oceanography , 77–80 : 10 – 20 . Google Scholar Crossref Search ADS WorldCat Galbraith P. S. , Chassé J., Gilbert D., Larouche P., Caverhill C., Lefaivre D., Brickman D. et al. 2014 . Physical Oceanographic Conditions in the Gulf of St. Lawrence in 2013. Canadian Science Advisory Secretariat Reserach Document 2014/062. Fisheries and Oceans Canada. Available from: http://www.dfo-mpo.gc.ca/csas-sccs/Publications/ResDocs-DocRech/2014/2014_062-eng.html. Galbraith P. S. , Gilbert D., Pettipas R. G., Chassé J., Lafleur C., Pettigrew B., Larouche P. et al. 2015 . Physical oceanographic conditions in the Gulf of t. Lawrence in 2014. Canadian Science Advisory Secretariat Reserach Document 2015/032. Fisheries and Oceans Canada. Gendron L. , Ouellet P. 2009 . Egg development trajectories of early and late-spawner lobsters (Homarus Americanus) in the Magdalen Islands, Québec . Journal of Crustacean Biology , 29 : 356 – 363 . Google Scholar Crossref Search ADS WorldCat Gendron L. , Lefaivre D., Sainte-Marie B. 2019 . Local egg production and larval losses to advection contribute to interannual and long-term variability of American lobster (Homarus americanus) settlement intensity . Canadian Journal of Fisheries and Aquatic Sciences , 76 : 350 – 363 . Google Scholar Crossref Search ADS WorldCat Gerber L. R. , Mancha-Cisneros M. D. M., O’Connor M. I., Selig E. R. 2014 . Climate change impacts on connectivity in the ocean: implications for conservation . Ecosphere , 5 : art33 . Google Scholar Crossref Search ADS WorldCat Goosse H. , Fichefet T. 1999 . Importance of ice-ocean interactions for the global ocean circulation: a model study . Journal of Geophysical Research: Oceans , 104 : 23337 – 23355 . Google Scholar Crossref Search ADS WorldCat Gotceitas V. , Puvanendran V., Leader L., Brown J. 1996 . An experimental investigation of the ‘match/mismatch’ hypothesis using larval Atlantic cod . Marine Ecology Progress Series , 130 : 29 – 37 . Google Scholar Crossref Search ADS WorldCat Haarr M. L. , Sainte-Marie B., Comeau M., Tremblay M. J., Rochette R. 2018 . Female American lobster (Homarus americanus) size-at-maturity declined in Canada during the 20th and early 21st centuries . Canadian Journal of Fisheries and Aquatic Sciences , 75 : 908 – 924 . Google Scholar Crossref Search ADS WorldCat Hanson J. M. , Courtenay S. C. 1996 . Seasonal use of estuaries by winter flounder in the southern Gulf of St. Lawrence . Transactions of the American Fisheries Society , 125 : 705 – 718 . Google Scholar Crossref Search ADS WorldCat Harding G. C. , Vass W. P., Drinkwter K. F. 1982 . Aspects of larval American lobster (Homarus americanus) ecology in St. Georges Bay, Nova Scotia . Canadian Journal of Fisheries and Aquatic Sciences , 39 : 1117 – 1129 . Google Scholar Crossref Search ADS WorldCat Heilmayer O. , Honnen C., Jacob U., Chiantore M., Cattaneo-Vietti R., Brey T. 2005 . Temperature effects on summer growth rates in the Antarctic scallop, Adamussium colbecki . Polar Biology , 28 : 523 – 527 . Google Scholar Crossref Search ADS WorldCat Helluy S. M. , Beltz B. S. 1991 . Embryonic development of the American Lobster (Homarus americanus): quantitative staging and characterization of an embryonic molt cycle . The Biological Bulletin , 180 : 355 – 371 . Google Scholar Crossref Search ADS PubMed WorldCat Incze L. 2000 . Advection and settlement rates in a benthic invertebrate: recruitment to first benthic stage in Homarus americanus . ICES Journal of Marine Science , 57 : 430 – 437 . Google Scholar Crossref Search ADS WorldCat Jury S. H. , Watson W. H. 2013 . Seasonal and sexual differences in the thermal preferences and movements of American lobsters . Canadian Journal of Fisheries and Aquatic Sciences , 70 : 1650 – 1657 . Google Scholar Crossref Search ADS WorldCat Knudsen M. F. , Seidenkrantz M.-S., Jacobsen B. H., Kuijpers A. 2011 . Tracking the Atlantic multidecadal oscillation through the last 8,000 years . Nature Communications , 2 : 178 . Google Scholar Crossref Search ADS PubMed WorldCat Koopman H. N. , Westgate A. J., Siders Z. A. 2015 . Declining fecundity and factors affecting embryo quality in the American lobster (Homarus americanus) from the Bay of Fundy . Canadian Journal of Fisheries and Aquatic Sciences , 72 : 352 – 363 . Google Scholar Crossref Search ADS WorldCat Le Bris A. , Mills K. E., Wahle R. A., Chen Y., Alexander M. A., Allyn A. J., Schuetz J. G. et al. 2018 . Climate vulnerability and resilience in the most valuable North American fishery . Proceedings of the National Academy of Sciences , 115 : 1831 – 1836 . Google Scholar Crossref Search ADS WorldCat Loder J. W. , Wang Z. 2015 . Trends and variability of sea surface temperature in the northwest Atlantic from three historical gridded datasets . Atmosphere-Ocean , 53 : 510 – 528 . Google Scholar Crossref Search ADS WorldCat Mackas D. L. , Greve W., Edwards M., Chiba S., Tadokoro K., Eloire D., Mazzocchi M. G. et al. 2012 . Changing zooplankton seasonality in a changing ocean: comparing time series of zooplankton phenology . Progress in Oceanography , 97–100 : 31 – 62 . Google Scholar Crossref Search ADS WorldCat MacKenzie B. R. 1988 . Assessment of temperature effects on interrelationships between stage durations, mortality, and growth in laboratory-reared Homarus americanus Milne Edwards larvae . Journal of Experimental Marine Biology and Ecology , 116 : 87 – 98 . Google Scholar Crossref Search ADS WorldCat Madec G. , Delecluse P., Imbard M., Lévy C. 1998 . OPA 8.1 Ocean General Circulation Model Reference Manual. Note du Pôle de mode ´lisation de l’Institut Pierre-Simon Laplace, 11. Institut Pierre Simon Laplacedes Sciences de l’Environnement Global. Madec G. 2016 . NEMO ocean engine. Note du Pôle de mode ´lisation de l’Institut Pierre-Simon Laplace, 27. https://www.nemo-ocean.eu/wp-content/uploads/NEMO_book.pdf (last accessed 5 May 2019). Mallet M. , Comeau B., Gagnon D., Comeau M. 2006 . At-sea Sampling Data Collection and Fishery Regulations for the southern Gulf of Saint Lawrence lobster (Homarus americanus) Fishery—1982-2000. Canadian Manuscript Report of Fisheries and Aquatic Sciences 2769. Fisheries and Oceans Canada. Miller R. J. 1997 . Spatial differences in the productivity of American lobster in Nova Scotia . Canadian Journal of Fisheries and Aquatic Sciences , 54 : 1613 – 1618 . Google Scholar Crossref Search ADS WorldCat Miller E. , Haarr M. L., Rochette R. 2016 . Using temperature-dependent embryonic growth models to predict time of hatch of American lobster (Homarus americanus) in nature . Canadian Journal of Fisheries and Aquatic Sciences , 73 : 1483 – 1492 . Google Scholar Crossref Search ADS WorldCat Parmesan C. , Yohe G. 2003 . A globally coherent fingerprint of climate change impacts across natural systems . Nature , 421 : 37 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat Perkins H. C. 1972 . Developmental rates at various temperature of embryos of the northern lobster (Homarus americanus Milne-Edwards) . Fisheries Bulletin , 70 : 95 – 99 . OpenURL Placeholder Text WorldCat Pershing A. J. , Wahle R. A., Meyers P. C., Lawton P. 2012 . Large-scale coherence in New England lobster (Homarus americanus), settlement and associations with regional atmospheric conditions: lobster settlement and regional weather . Fisheries Oceanography , 21 : 348 – 362 . Google Scholar Crossref Search ADS WorldCat Quinn B. K. , Sainte-Marie B., Rochette R., Ouellet P. 2013 . Effect of temperature on development rate of larvae from cold-water American lobster (Homarus americanus) . Journal of Crustacean Biology , 33 : 527 – 536 . Google Scholar Crossref Search ADS WorldCat Quinn B. K. 2014 . Assessing Potential Influence of Larval Development Time and Drift on Large-Scale Spatial Connectivity of American Lobster (Homarus Americanus) . University of New Brunswick, Saint John, NB, Canada . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Quinn B. K. , Chassé J., Rochette R. 2017 . Potential connectivity among American lobster fisheries as a result of larval drift across the species’ range in eastern North America . Canadian Journal of Fisheries and Aquatic Sciences , 74 : 1549 – 1563 . Google Scholar Crossref Search ADS WorldCat Rhein M. , Rintoul S. R., Aoki S., Campos E., Chambers D., Feely R. A., Gulev S. et al. 2013 . Observations: ocean. In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK and New York, NY, USA. Root T. L. , Price J. T., Hall K. R., Schneider S. H., Rosenzweig C., Pounds J. A. 2003 . Fingerprints of global warming on wild animals and plants . Nature , 421 : 57 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat Schlüter M. H. , Merico A., Reginatto M., Boersma M., Wiltshire K. H., Greve W. 2010 . Phenological shifts of three interacting zooplankton groups in relation to climate change: zooplankton phenology under climate change . Global Change Biology, 16: 3144–3153 . OpenURL Placeholder Text WorldCat Staudinger M. D. , Mills K. E., Stamieszkin K., Record N. R., Hudak C. A., Allyn A., Diamond A. et al. 2019 . It’s about time: a synthesis of changing phenology in the Gulf of Maine ecosystem . Fisheries Oceanography , 28 : 532 – 566 . Google Scholar PubMed OpenURL Placeholder Text WorldCat Sullivan B. K. , Costello J. H., Van Keuren D. 2007 . Seasonality of the copepods Acartia hudsonica and Acartia tonsa in Narragansett Bay, RI, USA during a period of climate change . Estuarine, Coastal and Shelf Science , 73 : 259 – 267 . Google Scholar Crossref Search ADS WorldCat Talbot P. , Thaler C., Wilson P. 1984 . Spawning, egg attachment and egg retention in captive lobsters (Homarus americanus) . Aquaculture , 37 : 239 – 249 . Google Scholar Crossref Search ADS WorldCat Tang F. , Haarr M. L., Sainte-Marie B., Comeau M., Tremblay M. J., Gaudette J., Rochette R. 2018 . Spatio-temporal patterns and reproductive costs of abnormal clutches of female American lobster, Homarus americanus, in eastern Canada . ICES Journal of Marine Science , 75 : 2045 – 2059 . Google Scholar Crossref Search ADS WorldCat Tlusty M. , Metzler A., Malkin E., Goldstein J., Koneval M. 2008 . Microecological impacts of global warming on crustaceans—temperature induced shifts in the release of larvae from American lobster, Homarus americanus, females . Journal of Shellfish Research , 27 : 443 – 448 . Google Scholar Crossref Search ADS WorldCat Vaughn D. , Allen J. D. 2010 . The peril of the plankton . Integrative and Comparative Biology , 50 : 552 – 570 . Google Scholar Crossref Search ADS PubMed WorldCat Visser M. E. , Noordwijk A. J., van, Tinbergen J. M., Lessells C. M. 1998 . Warmer springs lead to mistimed reproduction in great tits (Parus major) . Proceedings of the Royal Society of London. Series B: Biological Sciences , 265 : 1867 – 1870 . Google Scholar Crossref Search ADS WorldCat Waddy S. L. , Aiken D. E. 1986 . Multiple fertilization and consecutive spawning in large American lobsters, Homarus americanus . Canadian Journal of Fisheries and Aquatic Sciences , 43 : 2291 – 2294 . Google Scholar Crossref Search ADS WorldCat Waddy S. L. , Aiken D. E., De Kleijn D. P. V. 1995 . Control of growth and reproduction. In Biology of the Lobster , pp. 217 – 266 . Ed. by J. R. Factor. Academic Press Inc., London, UK . Google Scholar Crossref Search ADS Google Scholar Google Preview WorldCat COPAC Waddy S. L. , Aiken D. E. 1995 . Temperature regulation of reproduction in female American lobsters (Homarus americanus) . ICES Marine Science Symposium , 199 : 54 – 60 . OpenURL Placeholder Text WorldCat Wahle R. A. , Incze L. S. 1997 . Pre- and post-settlement processes in recruitment of the American lobster . Journal of Experimental Marine Biology and Ecology , 217 : 179 – 207 . Google Scholar Crossref Search ADS WorldCat Wahle R. A. , Dellinger L., Olszewski S., Jekielek P. 2015 . American lobster nurseries of southern New England receding in the face of climate change . ICES Journal of Marine Science: Journal du Conseil , 72 : i69 – i78 . Google Scholar Crossref Search ADS WorldCat Xue H. , Incze L., Xu D., Wolff N., Pettigrew N. 2008 . Connectivity of lobster populations in the coastal Gulf of Maine . Ecological Modelling , 210 : 193 – 211 . Google Scholar Crossref Search ADS WorldCat © International Council for the Exploration of the Sea 2020. All rights reserved. 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