High male density favors maintenance over reproduction in a butterfly

High male density favors maintenance over reproduction in a butterfly Abstract Environmental factors exert strong effects on phenotypic expression. A particularly intriguing factor capable of inducing such plastic responses is the social environment experienced by a specific individual. Such social effects may alter the fitness of focal individuals if they affect the expression of reproductive traits and thus life-history strategies. To examine this question, we investigated the effects of individual density on morphology, reproduction, and behavior of male Bicyclus anynana butterflies. Increasing density significantly increased male body mass and the probability to succeed in aggressive interactions and tended to increase abdomen fat content. At the same time, increasing density significantly decreased courtship activity and tended to decrease sperm number. These results suggest that individual density seemed to induce differential strategic investment into survival and somatic maintenance versus reproduction in male butterflies. Males kept at high densities apparently favored high body mass and storage, which may enable longer survival during times of intense intraspecific competition. Moreover, their competitiveness was enhanced as suggested by a higher success in aggressive interactions. Males kept at low density, in contrast, favored reproduction through increased courtship activity and sperm production. Our study illustrates that the effects of density on the expression of morphological and behavioral traits are complex and difficult to predict, owing to resource-allocation trade-offs resulting in prudent strategic investment. INTRODUCTION Along with genetic factors, the expression of phenotypic traits is strongly affected by environmental conditions (Pigliucci 2001). Environmentally induced changes in the phenotype are known as phenotypic plasticity, reflecting the capacity of a single genotype to produce different phenotypes in response to environmental variation (West-Eberhard 1989; Pigliucci 2001). Plasticity can be an adaptive strategy to cope with variable environments, or may comprise nonadaptive biochemical or physiological interactions with the environment (Pigliucci 2001). With regard to the sources inducing phenotypic plasticity, the impact of abiotic environmental factors (e.g. temperature, humidity, salinity, pH, and solar radiation) has been particularly frequently investigated (Via et al. 1995; Miner et al. 2005). Such abiotic factors may substantially alter phenotypes, ranging from morphological and behavioral traits to life history (Pigliucci 2001; Miner et al. 2005). The effects of biotic environmental factors on phenotypic values have also attracted considerable attention (Miner et al. 2005). Biotic factors include interactions with protagonists and antagonists, such as symbionts, mutualists, prey, host pants, parasites, predators, and competitors (West-Eberhard 1989; Pigliucci 2001; Miner et al. 2005). The impact of the latter entails inter and intraspecific competition, exhibiting negative effects on individual fitness (Begon et al. 2014). These effects are often strongly density-dependent, with fitness being more strongly compromised at higher densities due to increasing competition for limiting resources (Agnew et al. 2002; Begon et al. 2014). For instance, high densities may result in reduced body mass and storage reserves, lower growth rates, longer development times, and a higher susceptibility to stress and predation (Agnew et al. 2002; Bauerfeind and Fischer 2005). However, positive density-dependence can also be found, for example, if density enhances antipredatory defenses, foraging efficiency, the probability to find a mate or reproduction (Allee effects; Courchamp et al. 1999; Schippers et al. 2011; Beaulieu et al. 2017; Goodsman et al. 2017). A particularly intriguing type of biotic influence is the social environment experienced by a specific individual. The general interest for the effects of the social environment on phenotypic expression has received increasing interest in recent years (in particular, in the context of mating behavior; Rodríguez et al. 2013; Westermann et al. 2014), which has resulted in the establishment of a new research field coined social plasticity (Rodriguez et al. 2013). Examples include studies on the effects of density and sex ratio on mating success, mate location, and courtship (Cade and Salazar Cade 1992; Janowitz and Fischer 2010, 2012; Holveck et al. 2015). Though effects of male number and density on male reproductive performance have received comparably little attention (Kokko and Rankin 2006; Janowitz and Fischer 2010, 2012; Westerman et al. 2014; Lüpold et al. 2017), this seems surprising because competition among males for mates is often intense, such that density may easily affect male reproductive traits such as mating behavior and sperm numbers (Gage 1991; Gage and Barnard 1996; Wedell and Cook 1999; Kemp and Wiklund 2001; Xue et al. 2016; Lüpold et al. 2017). More specifically, variation in male–male competition may affect sperm-competition risk and, thereby, the reproductive gains of investing into precopulatory traits (e.g. condition, weaponry) that increase mating success on the one hand and postcopulatory traits that increase fertilization success on the other hand (e.g. sperm number; Buzatto et al. 2015; Lüpold et al. 2017). For instance, with increasing population density, mating opportunities may increase, while at the same time encounters with other males become more likely, which may increase sperm-competition risk and reduce the efficiency of male–male contests in controlling access to females (Kokko and Rankin 2006; Lüpold et al. 2017). Against this background, here, we investigate the effects of male density on various traits in the squinting bush brown butterfly Bicyclus anynana. First, we examine density effects on morphology and physiology, focusing on traits reflecting the condition of males, namely body mass, fat and protein content, and phenoloxidase (PO) activity. Body mass is often positively related to male competitiveness, mating success, and stress resistance, but also to sperm production (Kemp 2000; Lewis et al. 2010; Kehl et al. 2015a, 2015b, 2015c). Likewise, fat (and potentially protein) content is considered a good proxy of condition, as fat is the principal energy store in insects (Zwaan et al. 1991; Kemp and Wiklund 2001; Kehl et al. 2015b). PO, finally, is an enzyme involved in immune defense, but more importantly its activity is considered to be positively related to general condition (Karl et al. 2011; González-Santoyo and Córdoba-Aguilar 2012; Franke and Fischer 2013; Kehl et al. 2015b). For instance, male B. anynana butterflies with higher thorax mass, fat content, and PO activity have increased mating success (Kehl et al. 2015b). We predict that, due to intraspecific competition for food and more frequent male–male interactions, increasing male density will result in diminished condition, evidenced by reduced body mass, fat and protein content, and PO activity (hypothesis 1). Second, we investigate male reproductive traits, specifically spermatophore mass and sperm number. High densities typically increase the risk of sperm competition (Wedell and Cook 1999; Kemp and Wiklund 2001), potentially resulting in higher sperm numbers and/or spermatophore mass (Gage 1991; Gage and Barnard 1996; Wedell and Cook 1999). Although higher sperm numbers may be beneficial for fertilization success providing a direct benefit in sperm competition, larger spermatophores delay remating in butterflies (Gage and Barnard 1996; Wedell and Cook 1999). Hence, we predict that spermatophore mass and sperm numbers increase with increasing male density in order to counteract increased sperm-competition risk (hypothesis 2). Third, we analyze behavioral traits, namely courtship, aggressiveness, and success in male–male interactions. Aggressiveness often increases with increasing density (Wedell and Cook 1999; Kemp and Wiklund 2001). We hypothesize that investment into courtship behavior as well as aggressiveness and concomitantly success in male–male interactions increases with increasing male density to ensure mating success under situations of high competition (hypothesis 3). MATERIAL AND METHODS Study organism B. anynana (Nymphalidae) is a tropical, fruit-feeding butterfly inhabiting open forests and savannah grassland in Africa, where it ranges from southern Africa to Ethiopia (Brakefield 1997). The species inhabits seasonal environments entailing a cool dry and a warm wet season. As an adaptation to this seasonality and the associated changes in the ground vegetation used for resting, this species exhibits striking phenotypic plasticity (2 seasonal morphs; Lyytinen et al. 2004). Reproduction is confined to the favorable wet season during which oviposition plants are abundantly available (Brakefield and Reitsma 1991; Brakefield 1997). Males and females are able to mate repeatedly, though females are reluctant to do so and often mate only once (Brakefield et al. 2001; Ferkau and Fischer 2006). For mate location, males employ a “perch-and-chase” strategy and compete for access to females (Brakefield and Reitsma 1991; Janowitz and Fischer 2012). Here, we used a laboratory stock population of B. anynana that was established at Greifswald University, Germany, in 2008, from several hundred eggs derived from a well-established stock population at Leiden University, The Netherlands. The latter population was founded in 1988 from 80 gravid females caught at a single locality in Nkhata Bay, Malawi. Several hundred adults are used per generation to produce the subsequent generation, maintaining high levels of heterozygosity at neutral loci (Van’t Hof et al. 2005). Animal rearing and experimental design All individuals used here were reared in population cages (50 × 50 × 50 cm) and fed with greenhouse-raised young maize plants ad libitum. Plants were replaced as necessary. Resulting pupae were collected daily and transferred to cylindrical hanging cages (30 × 38 cm). Within 6 h after adult eclosion, males and females were separated, ensuring that all individuals remained virgin as B. anynana males do not mate on their eclosion day. Throughout, all individuals were kept in a single climate room set at a photoperiod of 12:12 h light:dark, 27 °C, and 70% humidity, thus mimicking the environmental conditions of the wet season when butterflies reproduce. Butterflies had access to water and a moistened slice of banana for feeding ad libitum. Eclosed females were transferred to new hanging cages (30 × 38 cm) in groups of 10 individuals per cage, while males were randomly distributed among 3 treatment groups: 1) 1 male, 2) 5 males, or 3) 10 males were placed into individual cylindrical plastic pots (1 L) covered with gauze (n = 88, 26, and 21 pots, respectively). By shielding all pots from one another using paper, we ensured that individually kept males could not see any other males. Males were kept at the respective treatment for 3 days. Although B. anynana may show long lifespans during the dry season in which there is no reproduction (Brakefield and Reitsma 1991; Brakefield 1997), reproductively active wet season butterflies can be expected to live only about 1 week based on data from other butterflies (Scott 1973; Molleman et al. 2007). Thus, due to the rather short expected lifespans together with the fact that the first days of adult life seem to be of particular importance for reproduction given that random mortality is common in insects (Scott 1973), we used a rather short treatment period of 3 days only here. Thereafter, males were transferred individually to a female cage until mating occurred. Thus, for mating, we always placed a single male into a cage with 10 females to ensure high male mating rates. Mating couples were removed from the cages and isolated. After mating, both male and female were immediately frozen in liquid nitrogen. Female cages were reused by adding a fresh female once mating had occurred, after which a new male was introduced. For Treatments 2 and 3, 1–4 individuals per pot were set up for mating to ensure sufficiently high sample sizes. This approach resulted in 40 matings in Treatment 1, and 42 matings each in Treatments 2 and 3, using on average 1.6 males per pot in Treatment 2 and 2.0 in Treatment 3. Males and females were used to subsequently score reproductive, morphological, and immunological traits as outlined below. Surplus males not assigned to mating trials were used for analyzing behavioral traits (see below). Reproduction: spermatophore mass and fertile sperm number Females were thawed and afterwards dissected in insect Ringer solution (0.72% NaCl, 0.037% KCl, 0.017% CaCl2, 1% glucose in distilled water). The abdomen was opened and the bursa copulatrix, containing the spermatophore transferred by the male upon mating, was removed. Surplus Ringer solution was removed using filter paper, after which the bursa was weighed (Sartorius LE225D). Thus, the bursa was used as a proxy for spermatophore mass, as the mass of the bursa itself is negligible as compared with that of the spermatophore. After weighing, the bursa was transferred to a cavity slide and placed within a droplet of Ringer solution. The bursa was opened with forceps and then gently stirred to disperse sperm bundles. The number of eupyrene (fertile) sperm bundles was counted under a microscope (×50 magnifications) and then multiplied with 256 to calculate sperm number (as sperm cells undergo a fixed number of 8 divisions in Lepidoptera, resulting in 256 sperm per bundle; Virkki 1969). Morphology: body mass, wing size, and fat content Frozen males were weighed (Sartorius LE225D) before being dissected on dry ice. Head, legs, and wings were removed, and thorax and abdomen were separated. Wings were used for measuring forewing length and wing area (camera Veho UMS-004 Deluxe and program NIS-Elements). Thorax and abdomen were weighed. The thorax was then used to measure immune function (see below), whereas the abdomen was used to measure fat content. Therefore, abdomen were dried for 48 h at 60 °C and then weighed. Then, fat was extracted twice for 48 h using 1 mL acetone for each extraction. Afterwards, abdomen were again dried for 48 h at 60 °C and weighed. Fat content was calculated as the mass difference between the first and the second dry mass and is expressed as the percentage of abdomen dry mass. Immune function: PO activity and protein content To quantify PO activity, we closely followed the protocols of Rolff et al. (2004) and Stocks et al. (2006) as optimized for B. anynana (cf. Karl et al. 2011). In short, thoraces and 200 μL PBS (pH = 7.4) were transferred to 2-mL Eppendorf tubes and homogenized (Tissue Lyser II Qiagen). The cell walls were removed via centrifugation (4 °C, 12000 × g for 10 min), after which 60 μL of the supernatant was added to the wells of a 96-well plate, containing 140 μL L-Dopa (dihydrophenyl-L-alanine). The reaction was allowed to proceed for 45 min at 30 °C. Readings were taken every 30 s at 490 nm, using a temperature-controlled microplate reader (Biotek ELx808, Bad Friedrichshall, Germany). Enzyme activity was measured as the slope during the linear phase of the reaction between 15 and 30 min, during which the enzyme catalyzes the transition from L-DOPA to dopachrome. PO activity was determined twice per individual and the mean of both readings was used in subsequent analyses. As control, we used blanks with PBS, L-DOPA, and distilled water (Bailey et al. 2010). Blank values were subtracted from each individual PO value. Equal numbers per treatment group were always run together on 1 microwell plate. Total protein content was quantified 4 times per individual using the Bio-Rad (Hercules, CA, USA) protein assay based on the Bradford method (Bradford 1976). Therefore, 1 μL of the supernatant was diluted in 160 μL of distilled water, after which 40 μL of dye reagent was added. After 10 min of incubation at 30 °C, the absorbance was read at 595 nm on a microplate reader (BioTekELx 808). A standard curve was constructed with Albumine Bovine Serum in PBS buffer using a concentration series (0 to 2 mg/mL) to obtain a standard equation to calculate protein content. The mean value of the 4 measurements per individual was used for further analyses. Behavioral traits For scoring behavioral traits, 1 virgin male per treatment group (i.e. 3 in total) and a randomly selected virgin female were introduced into a cylindrical plastic container (1 L; 17 replicate trials). To distinguish different treatment groups, males were color-marked with color codes being randomly assigned to treatments within each trial. The containers were placed into a climate cabinet set at 12:12 h light:dark, 27 °C, and 70% humidity (Sanyo MIR 553, Osaka, Japan), and butterfly behavior was video-taped for 1 h with digital cameras (Samsung SEB-1005R and SDE-5001N, South Korea; cf. Beaulieu et al. 2015a). Based on the resulting videos, we scored per male 1) whether or not it was involved in aggressive male–male interactions (binary data: yes, no), 2) how often it initiated aggressive interactions, 3) how often it “won” aggressive interactions (winner: stayed; loser: retreated), 4) whether or not it initiated courtship behavior (binary data: yes, no), and 5) how often it initiated courtship behavior. Statistical analyses For analyzing variation in reproductive, morphological, and immunological traits, general linear models with treatment group as a fixed factor were used. Body mass was used as covariate when analyzing variation in spermatophore mass and sperm number. For locating significant differences among groups, the Tukey HSD post hoc test was used. Pearson correlations were used to calculate correlations between continuous traits. Variation in behavioral traits was analyzed using generalized linear models with a binomial error distribution and logit-link function (for binary data) or with a Poisson error distribution and log-link function (for frequency data). For locating significant differences among groups, the Bonferroni post hoc test was used. Throughout the text, all means are given ±1 SE. All statistical analyses were performed using Statistica (Stat Soft Inc. Version 8.0) or SPSS (IBM SPSS Statistics Version 21). RESULTS Body, thorax, and abdomen mass differed significantly among treatment groups, whereas all other traits did not (Table 1). Total body and abdomen mass were highest in the group with 5 males and lowest in the group with single males, whereas thorax mass was highest in the group with 10 males (Table 2; Figure 1). Additionally, sperm numbers tended to decrease whereas fat content tended to increase with increasing group size. The covariate body mass had a significant impact on spermatophore mass, indicating a positive relationship (r = 0.298, P = 0.001, n = 119). Table 1 Results of general linear models for the effects of treatment group (1, 5, or 10 males) on reproductive, morphological, and immunological traits in Bicyclus anynana Trait / factor DF MS F P Spermatophore mass Treatment group 2 0.14 0.64 0.530 Body mass 1 0.23 11.39 0.001 Error 117 0.02 Sperm number Treatment group 2 33542945 2.69 0.072 Body mass 1 60153 0.01 0.945 Error 117 12564670 Body mass Treatment group 2 136.2 4.43 0.014 Error 118 30.8 Abdomen mass Treatment group 2 56.6 4.29 0.016 Error 117 13.2 Thorax mass Treatment group 2 13.7 3.23 0.043 Error 118 4.2 Abdomen fat content Treatment group 2 208.2 2.61 0.078 Error 117 79.7 Wing area Treatment group 2 168.2 0.95 0.390 Error 112 177.1 Forewing length Treatment group 2 0.75 1.26 0.287 Error 115 0.59 Phenoloxidase activity Treatment group 2 80.8 1.87 0.161 Error 78 43.2 Protein content Treatment group 2 0.13 0.31 0.731 Error 93 0.42 Trait / factor DF MS F P Spermatophore mass Treatment group 2 0.14 0.64 0.530 Body mass 1 0.23 11.39 0.001 Error 117 0.02 Sperm number Treatment group 2 33542945 2.69 0.072 Body mass 1 60153 0.01 0.945 Error 117 12564670 Body mass Treatment group 2 136.2 4.43 0.014 Error 118 30.8 Abdomen mass Treatment group 2 56.6 4.29 0.016 Error 117 13.2 Thorax mass Treatment group 2 13.7 3.23 0.043 Error 118 4.2 Abdomen fat content Treatment group 2 208.2 2.61 0.078 Error 117 79.7 Wing area Treatment group 2 168.2 0.95 0.390 Error 112 177.1 Forewing length Treatment group 2 0.75 1.26 0.287 Error 115 0.59 Phenoloxidase activity Treatment group 2 80.8 1.87 0.161 Error 78 43.2 Protein content Treatment group 2 0.13 0.31 0.731 Error 93 0.42 Significant P values are given in bold. View Large Table 1 Results of general linear models for the effects of treatment group (1, 5, or 10 males) on reproductive, morphological, and immunological traits in Bicyclus anynana Trait / factor DF MS F P Spermatophore mass Treatment group 2 0.14 0.64 0.530 Body mass 1 0.23 11.39 0.001 Error 117 0.02 Sperm number Treatment group 2 33542945 2.69 0.072 Body mass 1 60153 0.01 0.945 Error 117 12564670 Body mass Treatment group 2 136.2 4.43 0.014 Error 118 30.8 Abdomen mass Treatment group 2 56.6 4.29 0.016 Error 117 13.2 Thorax mass Treatment group 2 13.7 3.23 0.043 Error 118 4.2 Abdomen fat content Treatment group 2 208.2 2.61 0.078 Error 117 79.7 Wing area Treatment group 2 168.2 0.95 0.390 Error 112 177.1 Forewing length Treatment group 2 0.75 1.26 0.287 Error 115 0.59 Phenoloxidase activity Treatment group 2 80.8 1.87 0.161 Error 78 43.2 Protein content Treatment group 2 0.13 0.31 0.731 Error 93 0.42 Trait / factor DF MS F P Spermatophore mass Treatment group 2 0.14 0.64 0.530 Body mass 1 0.23 11.39 0.001 Error 117 0.02 Sperm number Treatment group 2 33542945 2.69 0.072 Body mass 1 60153 0.01 0.945 Error 117 12564670 Body mass Treatment group 2 136.2 4.43 0.014 Error 118 30.8 Abdomen mass Treatment group 2 56.6 4.29 0.016 Error 117 13.2 Thorax mass Treatment group 2 13.7 3.23 0.043 Error 118 4.2 Abdomen fat content Treatment group 2 208.2 2.61 0.078 Error 117 79.7 Wing area Treatment group 2 168.2 0.95 0.390 Error 112 177.1 Forewing length Treatment group 2 0.75 1.26 0.287 Error 115 0.59 Phenoloxidase activity Treatment group 2 80.8 1.87 0.161 Error 78 43.2 Protein content Treatment group 2 0.13 0.31 0.731 Error 93 0.42 Significant P values are given in bold. View Large Table 2 Mean values (±SE) for reproductive, morphological, and immunological traits in relation to treatment group (1, 5, or 10 males) in Bicyclus anynana Trait 1 male 5 males 10 males Spermatophore mass (mg) 0.62 ± 0.02 a 0.63 ± 0.02 a 0.66 ± 0.02 a Sperm number 5811 ± 647 a 5285 ± 549 a 4017 ± 448 a Body mass (mg) 35.90 ± 0.95 a 39.37 ± 0.85 b 38.68 ± 0.82 ab Abdomen mass (mg) 13.79 ± 0.62 a 16.14 ± 0.63 b 14.74 ± 0.44 ab Thorax mass (mg) 14.01 ± 0.30 a 14.73 ± 0.29 ab 15.18 ± 0.37 b Abdomen fat content (%) 26.44 ± 1.69 a 28.64 ± 1.41 a 31.06 ± 1.06 a Wing area (mm2) 156.86 ± 1.92 a 158.25 ± 2.15 a 161.06 ± 2.36 a Forewing length (mm) 18.29 ± 0.11 a 18.41 ± 0.13 a 18.58 ± 0.13 a Phenoloxidase activity (mOD) 5.23 ± 1.33 a 6.93 ± 1.38 a 3.49 ± 0.96 a Protein content (mg/mL) 1.31 ± 0.11 a 1.20 ± 0.12 a 1.31 ± 0.11 a Trait 1 male 5 males 10 males Spermatophore mass (mg) 0.62 ± 0.02 a 0.63 ± 0.02 a 0.66 ± 0.02 a Sperm number 5811 ± 647 a 5285 ± 549 a 4017 ± 448 a Body mass (mg) 35.90 ± 0.95 a 39.37 ± 0.85 b 38.68 ± 0.82 ab Abdomen mass (mg) 13.79 ± 0.62 a 16.14 ± 0.63 b 14.74 ± 0.44 ab Thorax mass (mg) 14.01 ± 0.30 a 14.73 ± 0.29 ab 15.18 ± 0.37 b Abdomen fat content (%) 26.44 ± 1.69 a 28.64 ± 1.41 a 31.06 ± 1.06 a Wing area (mm2) 156.86 ± 1.92 a 158.25 ± 2.15 a 161.06 ± 2.36 a Forewing length (mm) 18.29 ± 0.11 a 18.41 ± 0.13 a 18.58 ± 0.13 a Phenoloxidase activity (mOD) 5.23 ± 1.33 a 6.93 ± 1.38 a 3.49 ± 0.96 a Protein content (mg/mL) 1.31 ± 0.11 a 1.20 ± 0.12 a 1.31 ± 0.11 a Different upper-case letters indicate significant differences among treatment groups (Tukey HSD). View Large Table 2 Mean values (±SE) for reproductive, morphological, and immunological traits in relation to treatment group (1, 5, or 10 males) in Bicyclus anynana Trait 1 male 5 males 10 males Spermatophore mass (mg) 0.62 ± 0.02 a 0.63 ± 0.02 a 0.66 ± 0.02 a Sperm number 5811 ± 647 a 5285 ± 549 a 4017 ± 448 a Body mass (mg) 35.90 ± 0.95 a 39.37 ± 0.85 b 38.68 ± 0.82 ab Abdomen mass (mg) 13.79 ± 0.62 a 16.14 ± 0.63 b 14.74 ± 0.44 ab Thorax mass (mg) 14.01 ± 0.30 a 14.73 ± 0.29 ab 15.18 ± 0.37 b Abdomen fat content (%) 26.44 ± 1.69 a 28.64 ± 1.41 a 31.06 ± 1.06 a Wing area (mm2) 156.86 ± 1.92 a 158.25 ± 2.15 a 161.06 ± 2.36 a Forewing length (mm) 18.29 ± 0.11 a 18.41 ± 0.13 a 18.58 ± 0.13 a Phenoloxidase activity (mOD) 5.23 ± 1.33 a 6.93 ± 1.38 a 3.49 ± 0.96 a Protein content (mg/mL) 1.31 ± 0.11 a 1.20 ± 0.12 a 1.31 ± 0.11 a Trait 1 male 5 males 10 males Spermatophore mass (mg) 0.62 ± 0.02 a 0.63 ± 0.02 a 0.66 ± 0.02 a Sperm number 5811 ± 647 a 5285 ± 549 a 4017 ± 448 a Body mass (mg) 35.90 ± 0.95 a 39.37 ± 0.85 b 38.68 ± 0.82 ab Abdomen mass (mg) 13.79 ± 0.62 a 16.14 ± 0.63 b 14.74 ± 0.44 ab Thorax mass (mg) 14.01 ± 0.30 a 14.73 ± 0.29 ab 15.18 ± 0.37 b Abdomen fat content (%) 26.44 ± 1.69 a 28.64 ± 1.41 a 31.06 ± 1.06 a Wing area (mm2) 156.86 ± 1.92 a 158.25 ± 2.15 a 161.06 ± 2.36 a Forewing length (mm) 18.29 ± 0.11 a 18.41 ± 0.13 a 18.58 ± 0.13 a Phenoloxidase activity (mOD) 5.23 ± 1.33 a 6.93 ± 1.38 a 3.49 ± 0.96 a Protein content (mg/mL) 1.31 ± 0.11 a 1.20 ± 0.12 a 1.31 ± 0.11 a Different upper-case letters indicate significant differences among treatment groups (Tukey HSD). View Large Figure 1 View largeDownload slide Sperm number (a), total body mass (b), abdomen mass (c), thorax mass (d), abdomen fat content (e), frequency of winning an aggressive interaction (f), and frequency of courtship behavior (g) in relation to treatment group (1, 5, or 10 males) in Bicyclus anynana. Given are means ± 1 SE. Different letters within or above bars indicate significant differences among groups. Figure 1 View largeDownload slide Sperm number (a), total body mass (b), abdomen mass (c), thorax mass (d), abdomen fat content (e), frequency of winning an aggressive interaction (f), and frequency of courtship behavior (g) in relation to treatment group (1, 5, or 10 males) in Bicyclus anynana. Given are means ± 1 SE. Different letters within or above bars indicate significant differences among groups. Regarding behavioral traits, treatment groups did not differ significantly in the occurrence and frequency of initiating aggressive behavior (Table 3). Nevertheless, the chances to win an aggressive interaction increased significantly with group size (Figure 1). Courtship behavior occurred significantly more frequently in the groups consisting of 1 (82% of trials) or 5 (88%) than in those consisting of 10 males (41%; 1 = 5 > 10, Bonferroni post hoc test). Similarly, the number of courtship attempts per male decreased significantly with increasing group size (Figure 1). Courtship frequency was not significantly related to the frequency of initiating aggressive behavior (r2 = 0.044, P = 0.137) or winning aggressive interactions (r2 = 0.015, P = 0.399). Table 3 Results of generalized linear models for the effects of treatment group (1, 5, or 10 males) on behavioral traits in Bicyclus anynana Variable DF Wald χ2 P Involvement in aggressive interactions (yes/no) 2 0.25 0.884 Frequency of initiating aggressive behavior 2 3.75 0.153 Frequency winning aggressive interactions 2 33.93 < 0.001 Occurrence of courtship behavior (yes/no) 2 9.40 0.009 Frequency of courtship behavior 2 8.20 0.017 Variable DF Wald χ2 P Involvement in aggressive interactions (yes/no) 2 0.25 0.884 Frequency of initiating aggressive behavior 2 3.75 0.153 Frequency winning aggressive interactions 2 33.93 < 0.001 Occurrence of courtship behavior (yes/no) 2 9.40 0.009 Frequency of courtship behavior 2 8.20 0.017 Significant P values are given in bold. View Large Table 3 Results of generalized linear models for the effects of treatment group (1, 5, or 10 males) on behavioral traits in Bicyclus anynana Variable DF Wald χ2 P Involvement in aggressive interactions (yes/no) 2 0.25 0.884 Frequency of initiating aggressive behavior 2 3.75 0.153 Frequency winning aggressive interactions 2 33.93 < 0.001 Occurrence of courtship behavior (yes/no) 2 9.40 0.009 Frequency of courtship behavior 2 8.20 0.017 Variable DF Wald χ2 P Involvement in aggressive interactions (yes/no) 2 0.25 0.884 Frequency of initiating aggressive behavior 2 3.75 0.153 Frequency winning aggressive interactions 2 33.93 < 0.001 Occurrence of courtship behavior (yes/no) 2 9.40 0.009 Frequency of courtship behavior 2 8.20 0.017 Significant P values are given in bold. View Large DISCUSSION Morphological, immunological, and reproductive traits In contrast to our a priori prediction (hypothesis 1), our results on parameters potentially underlying individual condition did not show evidence for a diminished male condition at higher densities. Only body mass was significantly affected by male density, showing higher rather than lower values with increasing male density, with fat content showing the same (nonsignificant) tendency. This is certainly an interesting finding, given that the densities used were extremely high with up to 10 males in a 1-L plastic cup. We conclude that the experimental conditions used were not too stressful for the butterflies and further speculate that the lower mass of individually kept males may result from difficulties in finding the food source and/or from the absence of stimulation of seeing other males feeding (Trowbridge 1991). The latter seems more likely, as B. anynana is well able to locate food based on odor (Dierks and Fischer 2008; Kehl and Fischer 2012), which should have guided the butterflies readily to the banana provided within the small enclosures used here. Taken together, these findings indicate that, if anything, the condition was better rather than poorer when males were kept in groups. Naturally, this conclusion is valid only under the conditions used here, with food being provided ad libitum. Restricted feeding may lead to different results. The fact that males from 10-male groups did not differ significantly from single males, whereas males from 5-male groups were significantly heavier than single males suggests that the effects of competition may have started to counterbalance the positive effects of the presence of other males under such high densities. We also did not find support for our second hypothesis, namely that spermatophore mass and fertile sperm number should increase with increasing density in order to ensure fertilization success under high risk of sperm competition (cf. Gage 1991; Gage and Barnard 1996). Potentially, sex ratio rather than male density is a more important social factor affecting reproduction in male B. anynana (Janowitz and Fischer 2012). However, sperm number tended to decrease with increasing density, whereas spermatophore mass remained unaffected. Whether the former tendency reflects detrimental effects of high density, challenging the above results, or differential strategic investment into reproduction versus survival (Stearns 1992; Ferkau and Fischer 2006) is unclear. However, the latter, indicating that males invest more in their own maintenance than in reproduction at high densities, would be consistent with our findings of increased body mass but reduced sperm numbers and is also supported by some other studies (Martin and Hosken 2004; Paukku and Kotiaho 2005). These results are also consistent with previous findings in B. anynana butterflies, showing that these butterflies favor self-maintenance at the expense of reproduction under stressful conditions (Beaulieu et al. 2015b). Yet, another explanation for decreased sperm numbers at high densities would be that males decrease their investment per ejaculate in order to produce a higher number of ejaculates due to the higher risk of sperm competition (Wedell et al. 2002). In contrast to our study, other recent studies did find increased investment into sperm production at the expense of maintenance at higher population densities, for example, in frogs (Buzatto et al. 2015; Lüpold et al. 2017). Such variation may arise from differences in mating systems, because the returns of expenditure into sperm quantity depend on various factors including the number of competing males, the level of sperm competition, and the benefits of investing into traits securing mating rather than fertilization success (Kokko and Rankin 2006; Buzatto et al. 2015). Note that frogs, in contrast to butterflies, have external fertilization such that inferior males may sneak fertilizations by releasing sperm close to mating pairs or by means of multi-male amplexus, thus increasing sperm competition and the benefits of increased sperm production (Buzatto et al. 2015; Lüpold et al. 2017). In contrast, in male butterflies, aggressiveness and persistence in male–male interactions and courtship, and thereby access to mating partners, may be much more important especially because females often mate only once (Brakefield et al. 2001; Ferkau and Fischer 2006; Kehl et al. 2015a, 2015b, 2015c), such that maintenance rather than sperm production may be favored. Behavioral traits Treatment groups did not seem to differ in their levels of aggressiveness, and courtship activity decreased rather than increased with increasing density, thereby challenging our third hypothesis. Interestingly though, the probability of winning an aggressive interaction increased strongly with male density. The decreased courtship activity in males originating from high densities may once again indicate a premium on survival and somatic maintenance at the expense of reproduction, thus trying to save as much energy as possible, whereas males that have been kept individually show a high investment into reproduction. However, if involved in aggressive interactions, males from high densities proved to be highly competitive, which may be related to their high body mass and levels of storage reserves. Alternatively, they may have been primed behaviorally to persist in disputes due to the high levels of competition experienced previously and may thus have a higher enforcement capacity (Christenson and Goist 1979; Wedell et al. 2002; Janowitz and Fischer 2012; Westerman et al. 2014). CONCLUSIONS In summary, our results revealed interesting albeit partly unexpected effects of increasing density and thus competition on morphological and behavioral traits. Increasing male density was or tended to be associated with increased body mass, abdomen fat content, and success in aggressive interactions, but decreased sperm number and courtship activity. Taken together, these findings indicate that 1) the high densities used here did not impose severe stress on the butterflies, but 2) induced differential strategic investment into somatic maintenance versus reproduction. Thus, males kept at high densities favored gaining and preserving high body mass and storage reserves, which may enable longer survival during times of intense intraspecific competition and also increase success in aggressive interactions (and thus precopulatory investment). Males kept individually, in contrast, favored reproduction over maintenance, perhaps because receptive females comprise a more valuable resource if densities are low. To what extent our findings can be extrapolated to more natural conditions, though, is currently not clear. This is a common limitation of laboratory studies being conducted under rather artificial settings as is the case here. In order to manipulate densities, we confined 1, 5, or 10 males to small plastic cups (1 L). This results in very high densities rarely encountered in nature. An undeniable advantage associated with the use of small enclosures is that they permit high levels of control and replication, which enabled us to reliably investigate whether density on principle affects male traits. Even though the patterns found make sense and may, therefore, suggest biological relevance, the results obtained should be interpreted with caution in terms of transferability to natural conditions due to the high densities used. Note though that, in butterfly species such as B. anynana using a perching strategy for mate location, multiple males may frequently directly interact (Fischer et al. 1999; Fischer and Fiedler 2001). This typically happens when 2 (or more) males engage in aerial contests, thereby incidentally touching other males’ territories. This may easily result in >10 interacting males (Fischer K, personal observation based on Copper butterflies). Note that, in general, butterflies often depend on scattered and only patchily available resources, which may also result in dense aggregations of many individuals (e.g. at food sources, mud-puddles, roosts; Beck et al. 1999; Fischer et al. 1999). Overall, our findings indicate that the effects of density on morphology and behavior are complex to investigate and difficult to predict, owing to resource-allocation trade-offs resulting in prudent strategic investment, which may easily override expected (detrimental) effects of high density. Data accessibility Analyses reported in this article can be reproduced using the data provided by Geiger et al. (2018). 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Published by Oxford University Press on behalf of the International Society for Behavioral Ecology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com 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) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Behavioral Ecology Oxford University Press

High male density favors maintenance over reproduction in a butterfly

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Abstract

Abstract Environmental factors exert strong effects on phenotypic expression. A particularly intriguing factor capable of inducing such plastic responses is the social environment experienced by a specific individual. Such social effects may alter the fitness of focal individuals if they affect the expression of reproductive traits and thus life-history strategies. To examine this question, we investigated the effects of individual density on morphology, reproduction, and behavior of male Bicyclus anynana butterflies. Increasing density significantly increased male body mass and the probability to succeed in aggressive interactions and tended to increase abdomen fat content. At the same time, increasing density significantly decreased courtship activity and tended to decrease sperm number. These results suggest that individual density seemed to induce differential strategic investment into survival and somatic maintenance versus reproduction in male butterflies. Males kept at high densities apparently favored high body mass and storage, which may enable longer survival during times of intense intraspecific competition. Moreover, their competitiveness was enhanced as suggested by a higher success in aggressive interactions. Males kept at low density, in contrast, favored reproduction through increased courtship activity and sperm production. Our study illustrates that the effects of density on the expression of morphological and behavioral traits are complex and difficult to predict, owing to resource-allocation trade-offs resulting in prudent strategic investment. INTRODUCTION Along with genetic factors, the expression of phenotypic traits is strongly affected by environmental conditions (Pigliucci 2001). Environmentally induced changes in the phenotype are known as phenotypic plasticity, reflecting the capacity of a single genotype to produce different phenotypes in response to environmental variation (West-Eberhard 1989; Pigliucci 2001). Plasticity can be an adaptive strategy to cope with variable environments, or may comprise nonadaptive biochemical or physiological interactions with the environment (Pigliucci 2001). With regard to the sources inducing phenotypic plasticity, the impact of abiotic environmental factors (e.g. temperature, humidity, salinity, pH, and solar radiation) has been particularly frequently investigated (Via et al. 1995; Miner et al. 2005). Such abiotic factors may substantially alter phenotypes, ranging from morphological and behavioral traits to life history (Pigliucci 2001; Miner et al. 2005). The effects of biotic environmental factors on phenotypic values have also attracted considerable attention (Miner et al. 2005). Biotic factors include interactions with protagonists and antagonists, such as symbionts, mutualists, prey, host pants, parasites, predators, and competitors (West-Eberhard 1989; Pigliucci 2001; Miner et al. 2005). The impact of the latter entails inter and intraspecific competition, exhibiting negative effects on individual fitness (Begon et al. 2014). These effects are often strongly density-dependent, with fitness being more strongly compromised at higher densities due to increasing competition for limiting resources (Agnew et al. 2002; Begon et al. 2014). For instance, high densities may result in reduced body mass and storage reserves, lower growth rates, longer development times, and a higher susceptibility to stress and predation (Agnew et al. 2002; Bauerfeind and Fischer 2005). However, positive density-dependence can also be found, for example, if density enhances antipredatory defenses, foraging efficiency, the probability to find a mate or reproduction (Allee effects; Courchamp et al. 1999; Schippers et al. 2011; Beaulieu et al. 2017; Goodsman et al. 2017). A particularly intriguing type of biotic influence is the social environment experienced by a specific individual. The general interest for the effects of the social environment on phenotypic expression has received increasing interest in recent years (in particular, in the context of mating behavior; Rodríguez et al. 2013; Westermann et al. 2014), which has resulted in the establishment of a new research field coined social plasticity (Rodriguez et al. 2013). Examples include studies on the effects of density and sex ratio on mating success, mate location, and courtship (Cade and Salazar Cade 1992; Janowitz and Fischer 2010, 2012; Holveck et al. 2015). Though effects of male number and density on male reproductive performance have received comparably little attention (Kokko and Rankin 2006; Janowitz and Fischer 2010, 2012; Westerman et al. 2014; Lüpold et al. 2017), this seems surprising because competition among males for mates is often intense, such that density may easily affect male reproductive traits such as mating behavior and sperm numbers (Gage 1991; Gage and Barnard 1996; Wedell and Cook 1999; Kemp and Wiklund 2001; Xue et al. 2016; Lüpold et al. 2017). More specifically, variation in male–male competition may affect sperm-competition risk and, thereby, the reproductive gains of investing into precopulatory traits (e.g. condition, weaponry) that increase mating success on the one hand and postcopulatory traits that increase fertilization success on the other hand (e.g. sperm number; Buzatto et al. 2015; Lüpold et al. 2017). For instance, with increasing population density, mating opportunities may increase, while at the same time encounters with other males become more likely, which may increase sperm-competition risk and reduce the efficiency of male–male contests in controlling access to females (Kokko and Rankin 2006; Lüpold et al. 2017). Against this background, here, we investigate the effects of male density on various traits in the squinting bush brown butterfly Bicyclus anynana. First, we examine density effects on morphology and physiology, focusing on traits reflecting the condition of males, namely body mass, fat and protein content, and phenoloxidase (PO) activity. Body mass is often positively related to male competitiveness, mating success, and stress resistance, but also to sperm production (Kemp 2000; Lewis et al. 2010; Kehl et al. 2015a, 2015b, 2015c). Likewise, fat (and potentially protein) content is considered a good proxy of condition, as fat is the principal energy store in insects (Zwaan et al. 1991; Kemp and Wiklund 2001; Kehl et al. 2015b). PO, finally, is an enzyme involved in immune defense, but more importantly its activity is considered to be positively related to general condition (Karl et al. 2011; González-Santoyo and Córdoba-Aguilar 2012; Franke and Fischer 2013; Kehl et al. 2015b). For instance, male B. anynana butterflies with higher thorax mass, fat content, and PO activity have increased mating success (Kehl et al. 2015b). We predict that, due to intraspecific competition for food and more frequent male–male interactions, increasing male density will result in diminished condition, evidenced by reduced body mass, fat and protein content, and PO activity (hypothesis 1). Second, we investigate male reproductive traits, specifically spermatophore mass and sperm number. High densities typically increase the risk of sperm competition (Wedell and Cook 1999; Kemp and Wiklund 2001), potentially resulting in higher sperm numbers and/or spermatophore mass (Gage 1991; Gage and Barnard 1996; Wedell and Cook 1999). Although higher sperm numbers may be beneficial for fertilization success providing a direct benefit in sperm competition, larger spermatophores delay remating in butterflies (Gage and Barnard 1996; Wedell and Cook 1999). Hence, we predict that spermatophore mass and sperm numbers increase with increasing male density in order to counteract increased sperm-competition risk (hypothesis 2). Third, we analyze behavioral traits, namely courtship, aggressiveness, and success in male–male interactions. Aggressiveness often increases with increasing density (Wedell and Cook 1999; Kemp and Wiklund 2001). We hypothesize that investment into courtship behavior as well as aggressiveness and concomitantly success in male–male interactions increases with increasing male density to ensure mating success under situations of high competition (hypothesis 3). MATERIAL AND METHODS Study organism B. anynana (Nymphalidae) is a tropical, fruit-feeding butterfly inhabiting open forests and savannah grassland in Africa, where it ranges from southern Africa to Ethiopia (Brakefield 1997). The species inhabits seasonal environments entailing a cool dry and a warm wet season. As an adaptation to this seasonality and the associated changes in the ground vegetation used for resting, this species exhibits striking phenotypic plasticity (2 seasonal morphs; Lyytinen et al. 2004). Reproduction is confined to the favorable wet season during which oviposition plants are abundantly available (Brakefield and Reitsma 1991; Brakefield 1997). Males and females are able to mate repeatedly, though females are reluctant to do so and often mate only once (Brakefield et al. 2001; Ferkau and Fischer 2006). For mate location, males employ a “perch-and-chase” strategy and compete for access to females (Brakefield and Reitsma 1991; Janowitz and Fischer 2012). Here, we used a laboratory stock population of B. anynana that was established at Greifswald University, Germany, in 2008, from several hundred eggs derived from a well-established stock population at Leiden University, The Netherlands. The latter population was founded in 1988 from 80 gravid females caught at a single locality in Nkhata Bay, Malawi. Several hundred adults are used per generation to produce the subsequent generation, maintaining high levels of heterozygosity at neutral loci (Van’t Hof et al. 2005). Animal rearing and experimental design All individuals used here were reared in population cages (50 × 50 × 50 cm) and fed with greenhouse-raised young maize plants ad libitum. Plants were replaced as necessary. Resulting pupae were collected daily and transferred to cylindrical hanging cages (30 × 38 cm). Within 6 h after adult eclosion, males and females were separated, ensuring that all individuals remained virgin as B. anynana males do not mate on their eclosion day. Throughout, all individuals were kept in a single climate room set at a photoperiod of 12:12 h light:dark, 27 °C, and 70% humidity, thus mimicking the environmental conditions of the wet season when butterflies reproduce. Butterflies had access to water and a moistened slice of banana for feeding ad libitum. Eclosed females were transferred to new hanging cages (30 × 38 cm) in groups of 10 individuals per cage, while males were randomly distributed among 3 treatment groups: 1) 1 male, 2) 5 males, or 3) 10 males were placed into individual cylindrical plastic pots (1 L) covered with gauze (n = 88, 26, and 21 pots, respectively). By shielding all pots from one another using paper, we ensured that individually kept males could not see any other males. Males were kept at the respective treatment for 3 days. Although B. anynana may show long lifespans during the dry season in which there is no reproduction (Brakefield and Reitsma 1991; Brakefield 1997), reproductively active wet season butterflies can be expected to live only about 1 week based on data from other butterflies (Scott 1973; Molleman et al. 2007). Thus, due to the rather short expected lifespans together with the fact that the first days of adult life seem to be of particular importance for reproduction given that random mortality is common in insects (Scott 1973), we used a rather short treatment period of 3 days only here. Thereafter, males were transferred individually to a female cage until mating occurred. Thus, for mating, we always placed a single male into a cage with 10 females to ensure high male mating rates. Mating couples were removed from the cages and isolated. After mating, both male and female were immediately frozen in liquid nitrogen. Female cages were reused by adding a fresh female once mating had occurred, after which a new male was introduced. For Treatments 2 and 3, 1–4 individuals per pot were set up for mating to ensure sufficiently high sample sizes. This approach resulted in 40 matings in Treatment 1, and 42 matings each in Treatments 2 and 3, using on average 1.6 males per pot in Treatment 2 and 2.0 in Treatment 3. Males and females were used to subsequently score reproductive, morphological, and immunological traits as outlined below. Surplus males not assigned to mating trials were used for analyzing behavioral traits (see below). Reproduction: spermatophore mass and fertile sperm number Females were thawed and afterwards dissected in insect Ringer solution (0.72% NaCl, 0.037% KCl, 0.017% CaCl2, 1% glucose in distilled water). The abdomen was opened and the bursa copulatrix, containing the spermatophore transferred by the male upon mating, was removed. Surplus Ringer solution was removed using filter paper, after which the bursa was weighed (Sartorius LE225D). Thus, the bursa was used as a proxy for spermatophore mass, as the mass of the bursa itself is negligible as compared with that of the spermatophore. After weighing, the bursa was transferred to a cavity slide and placed within a droplet of Ringer solution. The bursa was opened with forceps and then gently stirred to disperse sperm bundles. The number of eupyrene (fertile) sperm bundles was counted under a microscope (×50 magnifications) and then multiplied with 256 to calculate sperm number (as sperm cells undergo a fixed number of 8 divisions in Lepidoptera, resulting in 256 sperm per bundle; Virkki 1969). Morphology: body mass, wing size, and fat content Frozen males were weighed (Sartorius LE225D) before being dissected on dry ice. Head, legs, and wings were removed, and thorax and abdomen were separated. Wings were used for measuring forewing length and wing area (camera Veho UMS-004 Deluxe and program NIS-Elements). Thorax and abdomen were weighed. The thorax was then used to measure immune function (see below), whereas the abdomen was used to measure fat content. Therefore, abdomen were dried for 48 h at 60 °C and then weighed. Then, fat was extracted twice for 48 h using 1 mL acetone for each extraction. Afterwards, abdomen were again dried for 48 h at 60 °C and weighed. Fat content was calculated as the mass difference between the first and the second dry mass and is expressed as the percentage of abdomen dry mass. Immune function: PO activity and protein content To quantify PO activity, we closely followed the protocols of Rolff et al. (2004) and Stocks et al. (2006) as optimized for B. anynana (cf. Karl et al. 2011). In short, thoraces and 200 μL PBS (pH = 7.4) were transferred to 2-mL Eppendorf tubes and homogenized (Tissue Lyser II Qiagen). The cell walls were removed via centrifugation (4 °C, 12000 × g for 10 min), after which 60 μL of the supernatant was added to the wells of a 96-well plate, containing 140 μL L-Dopa (dihydrophenyl-L-alanine). The reaction was allowed to proceed for 45 min at 30 °C. Readings were taken every 30 s at 490 nm, using a temperature-controlled microplate reader (Biotek ELx808, Bad Friedrichshall, Germany). Enzyme activity was measured as the slope during the linear phase of the reaction between 15 and 30 min, during which the enzyme catalyzes the transition from L-DOPA to dopachrome. PO activity was determined twice per individual and the mean of both readings was used in subsequent analyses. As control, we used blanks with PBS, L-DOPA, and distilled water (Bailey et al. 2010). Blank values were subtracted from each individual PO value. Equal numbers per treatment group were always run together on 1 microwell plate. Total protein content was quantified 4 times per individual using the Bio-Rad (Hercules, CA, USA) protein assay based on the Bradford method (Bradford 1976). Therefore, 1 μL of the supernatant was diluted in 160 μL of distilled water, after which 40 μL of dye reagent was added. After 10 min of incubation at 30 °C, the absorbance was read at 595 nm on a microplate reader (BioTekELx 808). A standard curve was constructed with Albumine Bovine Serum in PBS buffer using a concentration series (0 to 2 mg/mL) to obtain a standard equation to calculate protein content. The mean value of the 4 measurements per individual was used for further analyses. Behavioral traits For scoring behavioral traits, 1 virgin male per treatment group (i.e. 3 in total) and a randomly selected virgin female were introduced into a cylindrical plastic container (1 L; 17 replicate trials). To distinguish different treatment groups, males were color-marked with color codes being randomly assigned to treatments within each trial. The containers were placed into a climate cabinet set at 12:12 h light:dark, 27 °C, and 70% humidity (Sanyo MIR 553, Osaka, Japan), and butterfly behavior was video-taped for 1 h with digital cameras (Samsung SEB-1005R and SDE-5001N, South Korea; cf. Beaulieu et al. 2015a). Based on the resulting videos, we scored per male 1) whether or not it was involved in aggressive male–male interactions (binary data: yes, no), 2) how often it initiated aggressive interactions, 3) how often it “won” aggressive interactions (winner: stayed; loser: retreated), 4) whether or not it initiated courtship behavior (binary data: yes, no), and 5) how often it initiated courtship behavior. Statistical analyses For analyzing variation in reproductive, morphological, and immunological traits, general linear models with treatment group as a fixed factor were used. Body mass was used as covariate when analyzing variation in spermatophore mass and sperm number. For locating significant differences among groups, the Tukey HSD post hoc test was used. Pearson correlations were used to calculate correlations between continuous traits. Variation in behavioral traits was analyzed using generalized linear models with a binomial error distribution and logit-link function (for binary data) or with a Poisson error distribution and log-link function (for frequency data). For locating significant differences among groups, the Bonferroni post hoc test was used. Throughout the text, all means are given ±1 SE. All statistical analyses were performed using Statistica (Stat Soft Inc. Version 8.0) or SPSS (IBM SPSS Statistics Version 21). RESULTS Body, thorax, and abdomen mass differed significantly among treatment groups, whereas all other traits did not (Table 1). Total body and abdomen mass were highest in the group with 5 males and lowest in the group with single males, whereas thorax mass was highest in the group with 10 males (Table 2; Figure 1). Additionally, sperm numbers tended to decrease whereas fat content tended to increase with increasing group size. The covariate body mass had a significant impact on spermatophore mass, indicating a positive relationship (r = 0.298, P = 0.001, n = 119). Table 1 Results of general linear models for the effects of treatment group (1, 5, or 10 males) on reproductive, morphological, and immunological traits in Bicyclus anynana Trait / factor DF MS F P Spermatophore mass Treatment group 2 0.14 0.64 0.530 Body mass 1 0.23 11.39 0.001 Error 117 0.02 Sperm number Treatment group 2 33542945 2.69 0.072 Body mass 1 60153 0.01 0.945 Error 117 12564670 Body mass Treatment group 2 136.2 4.43 0.014 Error 118 30.8 Abdomen mass Treatment group 2 56.6 4.29 0.016 Error 117 13.2 Thorax mass Treatment group 2 13.7 3.23 0.043 Error 118 4.2 Abdomen fat content Treatment group 2 208.2 2.61 0.078 Error 117 79.7 Wing area Treatment group 2 168.2 0.95 0.390 Error 112 177.1 Forewing length Treatment group 2 0.75 1.26 0.287 Error 115 0.59 Phenoloxidase activity Treatment group 2 80.8 1.87 0.161 Error 78 43.2 Protein content Treatment group 2 0.13 0.31 0.731 Error 93 0.42 Trait / factor DF MS F P Spermatophore mass Treatment group 2 0.14 0.64 0.530 Body mass 1 0.23 11.39 0.001 Error 117 0.02 Sperm number Treatment group 2 33542945 2.69 0.072 Body mass 1 60153 0.01 0.945 Error 117 12564670 Body mass Treatment group 2 136.2 4.43 0.014 Error 118 30.8 Abdomen mass Treatment group 2 56.6 4.29 0.016 Error 117 13.2 Thorax mass Treatment group 2 13.7 3.23 0.043 Error 118 4.2 Abdomen fat content Treatment group 2 208.2 2.61 0.078 Error 117 79.7 Wing area Treatment group 2 168.2 0.95 0.390 Error 112 177.1 Forewing length Treatment group 2 0.75 1.26 0.287 Error 115 0.59 Phenoloxidase activity Treatment group 2 80.8 1.87 0.161 Error 78 43.2 Protein content Treatment group 2 0.13 0.31 0.731 Error 93 0.42 Significant P values are given in bold. View Large Table 1 Results of general linear models for the effects of treatment group (1, 5, or 10 males) on reproductive, morphological, and immunological traits in Bicyclus anynana Trait / factor DF MS F P Spermatophore mass Treatment group 2 0.14 0.64 0.530 Body mass 1 0.23 11.39 0.001 Error 117 0.02 Sperm number Treatment group 2 33542945 2.69 0.072 Body mass 1 60153 0.01 0.945 Error 117 12564670 Body mass Treatment group 2 136.2 4.43 0.014 Error 118 30.8 Abdomen mass Treatment group 2 56.6 4.29 0.016 Error 117 13.2 Thorax mass Treatment group 2 13.7 3.23 0.043 Error 118 4.2 Abdomen fat content Treatment group 2 208.2 2.61 0.078 Error 117 79.7 Wing area Treatment group 2 168.2 0.95 0.390 Error 112 177.1 Forewing length Treatment group 2 0.75 1.26 0.287 Error 115 0.59 Phenoloxidase activity Treatment group 2 80.8 1.87 0.161 Error 78 43.2 Protein content Treatment group 2 0.13 0.31 0.731 Error 93 0.42 Trait / factor DF MS F P Spermatophore mass Treatment group 2 0.14 0.64 0.530 Body mass 1 0.23 11.39 0.001 Error 117 0.02 Sperm number Treatment group 2 33542945 2.69 0.072 Body mass 1 60153 0.01 0.945 Error 117 12564670 Body mass Treatment group 2 136.2 4.43 0.014 Error 118 30.8 Abdomen mass Treatment group 2 56.6 4.29 0.016 Error 117 13.2 Thorax mass Treatment group 2 13.7 3.23 0.043 Error 118 4.2 Abdomen fat content Treatment group 2 208.2 2.61 0.078 Error 117 79.7 Wing area Treatment group 2 168.2 0.95 0.390 Error 112 177.1 Forewing length Treatment group 2 0.75 1.26 0.287 Error 115 0.59 Phenoloxidase activity Treatment group 2 80.8 1.87 0.161 Error 78 43.2 Protein content Treatment group 2 0.13 0.31 0.731 Error 93 0.42 Significant P values are given in bold. View Large Table 2 Mean values (±SE) for reproductive, morphological, and immunological traits in relation to treatment group (1, 5, or 10 males) in Bicyclus anynana Trait 1 male 5 males 10 males Spermatophore mass (mg) 0.62 ± 0.02 a 0.63 ± 0.02 a 0.66 ± 0.02 a Sperm number 5811 ± 647 a 5285 ± 549 a 4017 ± 448 a Body mass (mg) 35.90 ± 0.95 a 39.37 ± 0.85 b 38.68 ± 0.82 ab Abdomen mass (mg) 13.79 ± 0.62 a 16.14 ± 0.63 b 14.74 ± 0.44 ab Thorax mass (mg) 14.01 ± 0.30 a 14.73 ± 0.29 ab 15.18 ± 0.37 b Abdomen fat content (%) 26.44 ± 1.69 a 28.64 ± 1.41 a 31.06 ± 1.06 a Wing area (mm2) 156.86 ± 1.92 a 158.25 ± 2.15 a 161.06 ± 2.36 a Forewing length (mm) 18.29 ± 0.11 a 18.41 ± 0.13 a 18.58 ± 0.13 a Phenoloxidase activity (mOD) 5.23 ± 1.33 a 6.93 ± 1.38 a 3.49 ± 0.96 a Protein content (mg/mL) 1.31 ± 0.11 a 1.20 ± 0.12 a 1.31 ± 0.11 a Trait 1 male 5 males 10 males Spermatophore mass (mg) 0.62 ± 0.02 a 0.63 ± 0.02 a 0.66 ± 0.02 a Sperm number 5811 ± 647 a 5285 ± 549 a 4017 ± 448 a Body mass (mg) 35.90 ± 0.95 a 39.37 ± 0.85 b 38.68 ± 0.82 ab Abdomen mass (mg) 13.79 ± 0.62 a 16.14 ± 0.63 b 14.74 ± 0.44 ab Thorax mass (mg) 14.01 ± 0.30 a 14.73 ± 0.29 ab 15.18 ± 0.37 b Abdomen fat content (%) 26.44 ± 1.69 a 28.64 ± 1.41 a 31.06 ± 1.06 a Wing area (mm2) 156.86 ± 1.92 a 158.25 ± 2.15 a 161.06 ± 2.36 a Forewing length (mm) 18.29 ± 0.11 a 18.41 ± 0.13 a 18.58 ± 0.13 a Phenoloxidase activity (mOD) 5.23 ± 1.33 a 6.93 ± 1.38 a 3.49 ± 0.96 a Protein content (mg/mL) 1.31 ± 0.11 a 1.20 ± 0.12 a 1.31 ± 0.11 a Different upper-case letters indicate significant differences among treatment groups (Tukey HSD). View Large Table 2 Mean values (±SE) for reproductive, morphological, and immunological traits in relation to treatment group (1, 5, or 10 males) in Bicyclus anynana Trait 1 male 5 males 10 males Spermatophore mass (mg) 0.62 ± 0.02 a 0.63 ± 0.02 a 0.66 ± 0.02 a Sperm number 5811 ± 647 a 5285 ± 549 a 4017 ± 448 a Body mass (mg) 35.90 ± 0.95 a 39.37 ± 0.85 b 38.68 ± 0.82 ab Abdomen mass (mg) 13.79 ± 0.62 a 16.14 ± 0.63 b 14.74 ± 0.44 ab Thorax mass (mg) 14.01 ± 0.30 a 14.73 ± 0.29 ab 15.18 ± 0.37 b Abdomen fat content (%) 26.44 ± 1.69 a 28.64 ± 1.41 a 31.06 ± 1.06 a Wing area (mm2) 156.86 ± 1.92 a 158.25 ± 2.15 a 161.06 ± 2.36 a Forewing length (mm) 18.29 ± 0.11 a 18.41 ± 0.13 a 18.58 ± 0.13 a Phenoloxidase activity (mOD) 5.23 ± 1.33 a 6.93 ± 1.38 a 3.49 ± 0.96 a Protein content (mg/mL) 1.31 ± 0.11 a 1.20 ± 0.12 a 1.31 ± 0.11 a Trait 1 male 5 males 10 males Spermatophore mass (mg) 0.62 ± 0.02 a 0.63 ± 0.02 a 0.66 ± 0.02 a Sperm number 5811 ± 647 a 5285 ± 549 a 4017 ± 448 a Body mass (mg) 35.90 ± 0.95 a 39.37 ± 0.85 b 38.68 ± 0.82 ab Abdomen mass (mg) 13.79 ± 0.62 a 16.14 ± 0.63 b 14.74 ± 0.44 ab Thorax mass (mg) 14.01 ± 0.30 a 14.73 ± 0.29 ab 15.18 ± 0.37 b Abdomen fat content (%) 26.44 ± 1.69 a 28.64 ± 1.41 a 31.06 ± 1.06 a Wing area (mm2) 156.86 ± 1.92 a 158.25 ± 2.15 a 161.06 ± 2.36 a Forewing length (mm) 18.29 ± 0.11 a 18.41 ± 0.13 a 18.58 ± 0.13 a Phenoloxidase activity (mOD) 5.23 ± 1.33 a 6.93 ± 1.38 a 3.49 ± 0.96 a Protein content (mg/mL) 1.31 ± 0.11 a 1.20 ± 0.12 a 1.31 ± 0.11 a Different upper-case letters indicate significant differences among treatment groups (Tukey HSD). View Large Figure 1 View largeDownload slide Sperm number (a), total body mass (b), abdomen mass (c), thorax mass (d), abdomen fat content (e), frequency of winning an aggressive interaction (f), and frequency of courtship behavior (g) in relation to treatment group (1, 5, or 10 males) in Bicyclus anynana. Given are means ± 1 SE. Different letters within or above bars indicate significant differences among groups. Figure 1 View largeDownload slide Sperm number (a), total body mass (b), abdomen mass (c), thorax mass (d), abdomen fat content (e), frequency of winning an aggressive interaction (f), and frequency of courtship behavior (g) in relation to treatment group (1, 5, or 10 males) in Bicyclus anynana. Given are means ± 1 SE. Different letters within or above bars indicate significant differences among groups. Regarding behavioral traits, treatment groups did not differ significantly in the occurrence and frequency of initiating aggressive behavior (Table 3). Nevertheless, the chances to win an aggressive interaction increased significantly with group size (Figure 1). Courtship behavior occurred significantly more frequently in the groups consisting of 1 (82% of trials) or 5 (88%) than in those consisting of 10 males (41%; 1 = 5 > 10, Bonferroni post hoc test). Similarly, the number of courtship attempts per male decreased significantly with increasing group size (Figure 1). Courtship frequency was not significantly related to the frequency of initiating aggressive behavior (r2 = 0.044, P = 0.137) or winning aggressive interactions (r2 = 0.015, P = 0.399). Table 3 Results of generalized linear models for the effects of treatment group (1, 5, or 10 males) on behavioral traits in Bicyclus anynana Variable DF Wald χ2 P Involvement in aggressive interactions (yes/no) 2 0.25 0.884 Frequency of initiating aggressive behavior 2 3.75 0.153 Frequency winning aggressive interactions 2 33.93 < 0.001 Occurrence of courtship behavior (yes/no) 2 9.40 0.009 Frequency of courtship behavior 2 8.20 0.017 Variable DF Wald χ2 P Involvement in aggressive interactions (yes/no) 2 0.25 0.884 Frequency of initiating aggressive behavior 2 3.75 0.153 Frequency winning aggressive interactions 2 33.93 < 0.001 Occurrence of courtship behavior (yes/no) 2 9.40 0.009 Frequency of courtship behavior 2 8.20 0.017 Significant P values are given in bold. View Large Table 3 Results of generalized linear models for the effects of treatment group (1, 5, or 10 males) on behavioral traits in Bicyclus anynana Variable DF Wald χ2 P Involvement in aggressive interactions (yes/no) 2 0.25 0.884 Frequency of initiating aggressive behavior 2 3.75 0.153 Frequency winning aggressive interactions 2 33.93 < 0.001 Occurrence of courtship behavior (yes/no) 2 9.40 0.009 Frequency of courtship behavior 2 8.20 0.017 Variable DF Wald χ2 P Involvement in aggressive interactions (yes/no) 2 0.25 0.884 Frequency of initiating aggressive behavior 2 3.75 0.153 Frequency winning aggressive interactions 2 33.93 < 0.001 Occurrence of courtship behavior (yes/no) 2 9.40 0.009 Frequency of courtship behavior 2 8.20 0.017 Significant P values are given in bold. View Large DISCUSSION Morphological, immunological, and reproductive traits In contrast to our a priori prediction (hypothesis 1), our results on parameters potentially underlying individual condition did not show evidence for a diminished male condition at higher densities. Only body mass was significantly affected by male density, showing higher rather than lower values with increasing male density, with fat content showing the same (nonsignificant) tendency. This is certainly an interesting finding, given that the densities used were extremely high with up to 10 males in a 1-L plastic cup. We conclude that the experimental conditions used were not too stressful for the butterflies and further speculate that the lower mass of individually kept males may result from difficulties in finding the food source and/or from the absence of stimulation of seeing other males feeding (Trowbridge 1991). The latter seems more likely, as B. anynana is well able to locate food based on odor (Dierks and Fischer 2008; Kehl and Fischer 2012), which should have guided the butterflies readily to the banana provided within the small enclosures used here. Taken together, these findings indicate that, if anything, the condition was better rather than poorer when males were kept in groups. Naturally, this conclusion is valid only under the conditions used here, with food being provided ad libitum. Restricted feeding may lead to different results. The fact that males from 10-male groups did not differ significantly from single males, whereas males from 5-male groups were significantly heavier than single males suggests that the effects of competition may have started to counterbalance the positive effects of the presence of other males under such high densities. We also did not find support for our second hypothesis, namely that spermatophore mass and fertile sperm number should increase with increasing density in order to ensure fertilization success under high risk of sperm competition (cf. Gage 1991; Gage and Barnard 1996). Potentially, sex ratio rather than male density is a more important social factor affecting reproduction in male B. anynana (Janowitz and Fischer 2012). However, sperm number tended to decrease with increasing density, whereas spermatophore mass remained unaffected. Whether the former tendency reflects detrimental effects of high density, challenging the above results, or differential strategic investment into reproduction versus survival (Stearns 1992; Ferkau and Fischer 2006) is unclear. However, the latter, indicating that males invest more in their own maintenance than in reproduction at high densities, would be consistent with our findings of increased body mass but reduced sperm numbers and is also supported by some other studies (Martin and Hosken 2004; Paukku and Kotiaho 2005). These results are also consistent with previous findings in B. anynana butterflies, showing that these butterflies favor self-maintenance at the expense of reproduction under stressful conditions (Beaulieu et al. 2015b). Yet, another explanation for decreased sperm numbers at high densities would be that males decrease their investment per ejaculate in order to produce a higher number of ejaculates due to the higher risk of sperm competition (Wedell et al. 2002). In contrast to our study, other recent studies did find increased investment into sperm production at the expense of maintenance at higher population densities, for example, in frogs (Buzatto et al. 2015; Lüpold et al. 2017). Such variation may arise from differences in mating systems, because the returns of expenditure into sperm quantity depend on various factors including the number of competing males, the level of sperm competition, and the benefits of investing into traits securing mating rather than fertilization success (Kokko and Rankin 2006; Buzatto et al. 2015). Note that frogs, in contrast to butterflies, have external fertilization such that inferior males may sneak fertilizations by releasing sperm close to mating pairs or by means of multi-male amplexus, thus increasing sperm competition and the benefits of increased sperm production (Buzatto et al. 2015; Lüpold et al. 2017). In contrast, in male butterflies, aggressiveness and persistence in male–male interactions and courtship, and thereby access to mating partners, may be much more important especially because females often mate only once (Brakefield et al. 2001; Ferkau and Fischer 2006; Kehl et al. 2015a, 2015b, 2015c), such that maintenance rather than sperm production may be favored. Behavioral traits Treatment groups did not seem to differ in their levels of aggressiveness, and courtship activity decreased rather than increased with increasing density, thereby challenging our third hypothesis. Interestingly though, the probability of winning an aggressive interaction increased strongly with male density. The decreased courtship activity in males originating from high densities may once again indicate a premium on survival and somatic maintenance at the expense of reproduction, thus trying to save as much energy as possible, whereas males that have been kept individually show a high investment into reproduction. However, if involved in aggressive interactions, males from high densities proved to be highly competitive, which may be related to their high body mass and levels of storage reserves. Alternatively, they may have been primed behaviorally to persist in disputes due to the high levels of competition experienced previously and may thus have a higher enforcement capacity (Christenson and Goist 1979; Wedell et al. 2002; Janowitz and Fischer 2012; Westerman et al. 2014). CONCLUSIONS In summary, our results revealed interesting albeit partly unexpected effects of increasing density and thus competition on morphological and behavioral traits. Increasing male density was or tended to be associated with increased body mass, abdomen fat content, and success in aggressive interactions, but decreased sperm number and courtship activity. Taken together, these findings indicate that 1) the high densities used here did not impose severe stress on the butterflies, but 2) induced differential strategic investment into somatic maintenance versus reproduction. Thus, males kept at high densities favored gaining and preserving high body mass and storage reserves, which may enable longer survival during times of intense intraspecific competition and also increase success in aggressive interactions (and thus precopulatory investment). Males kept individually, in contrast, favored reproduction over maintenance, perhaps because receptive females comprise a more valuable resource if densities are low. To what extent our findings can be extrapolated to more natural conditions, though, is currently not clear. This is a common limitation of laboratory studies being conducted under rather artificial settings as is the case here. In order to manipulate densities, we confined 1, 5, or 10 males to small plastic cups (1 L). This results in very high densities rarely encountered in nature. An undeniable advantage associated with the use of small enclosures is that they permit high levels of control and replication, which enabled us to reliably investigate whether density on principle affects male traits. Even though the patterns found make sense and may, therefore, suggest biological relevance, the results obtained should be interpreted with caution in terms of transferability to natural conditions due to the high densities used. Note though that, in butterfly species such as B. anynana using a perching strategy for mate location, multiple males may frequently directly interact (Fischer et al. 1999; Fischer and Fiedler 2001). This typically happens when 2 (or more) males engage in aerial contests, thereby incidentally touching other males’ territories. This may easily result in >10 interacting males (Fischer K, personal observation based on Copper butterflies). Note that, in general, butterflies often depend on scattered and only patchily available resources, which may also result in dense aggregations of many individuals (e.g. at food sources, mud-puddles, roosts; Beck et al. 1999; Fischer et al. 1999). Overall, our findings indicate that the effects of density on morphology and behavior are complex to investigate and difficult to predict, owing to resource-allocation trade-offs resulting in prudent strategic investment, which may easily override expected (detrimental) effects of high density. Data accessibility Analyses reported in this article can be reproduced using the data provided by Geiger et al. (2018). 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Published by Oxford University Press on behalf of the International Society for Behavioral Ecology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com 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)

Journal

Behavioral EcologyOxford University Press

Published: Sep 10, 2018

References

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