Many organisms have evolved adaptive coloration that reduces their risk of predation. Cryptic colo- ration reduces the likelihood of detection/recognition by potential predators, while warning or apo- sematic coloration advertises unproﬁtability and thereby reduces the likelihood of attack. Although some studies show that aposematic coloration functions better at decreasing attack rate than cryp- sis, recent work has suggested and demonstrated that crypsis and aposematism are both success- ful strategies for avoiding predation. Furthermore, the visual environment (e.g., ambient lighting, background) affects the ability for predators to detect prey. We investigated these 2 related hypoth- eses using 2 well-known visually aposematic species of Heliconius butterﬂies, which occupy differ- ent habitats (open-canopy vs. closed-canopy), and one palatable, cryptic, generalist species Junonia coenia. We tested if the differently colored butterﬂies differ in attack rates by placing plasti- cine models of each of the 3 species in 2 different tropical habitats where the butterﬂies naturally occur: disturbed, open-canopy habitat and forested, closed-canopy habitat. The cryptic model had fewer attacks than one of the aposematic models. Predation rates differed between the 2 habitats, with the open habitat having much higher predation. However, we did not ﬁnd an interaction between species and habitat type, which is perplexing due to the different aposematic phenotypes naturally occurring in different habitats. Our ﬁndings suggest that during the Panamanian dry sea- son avian predation on perched butterﬂies is not a leading cause in habitat segregation between the 2 aposematic species and demonstrate that cryptically colored animals at rest may be better than aposematic prey at avoiding avian attacks in certain environments. Key words: avian attacks, camouﬂage, Heliconius, Junonia, light environment, plasticine models, predation, warning coloration. Many animals face high rates of predation in the wild and have (e.g., stings, toxins, armor, etc.) are coupled with conspicuous sig- evolved a diverse array of defenses to increase survival (Poulton nals to facilitate predator recognition of unprofitable prey (Wallace 1890; Cott 1940; Ruxton et al. 2004; Stevens and Merilaita 2009). 1867; Poulton 1890; Ruxton et al. 2004). The functional benefits of One adaptation to avoid predation is camouflage, in which a prey’s both crypsis and aposematism are well documented (Endler 1981; color pattern blends with that of the visual background (i.e., cryp- Heiling et al. 2005; Mappes et al. 2005; Speed et al. 2010; Summers sis), rendering that individual difficult for potential predators to et al. 2015); however, comparisons between the 2 visual strategies detect (Edmunds 1974; Endler 1984; Cuthill et al. 2005; Stevens are lacking (but see Carroll and Sherratt 2013). and Merilaita 2011; Seymoure and Aiello 2015). Another common Little is known about the differential fitness benefits between defensive adaptation is aposematism, in which the characteristics of these 2 types of defensive coloration, crypsis and aposematism. Does potential prey animals that are potentially damaging to predators aposematic coloration reduce predation better than crypsis due to V C The Author (2017). Published by Oxford University Press. 663 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact email@example.com Downloaded from https://academic.oup.com/cz/article-abstract/64/5/663/4575132 by Ed 'DeepDyve' Gillespie user on 18 October 2018 664 Current Zoology, 2018, Vol. 64, No. 5 mutual benefits to both the prey (i.e., survival) and predator (i.e., (Papageorgis 1975; Devries 1987; Mallet and Gilbert 1995; avoiding noxious characteristics; Papageorgis 1975; Guilford 1990; Thurman and Seymoure 2016). In the lowland rainforest of Guilford and Dawkins 1993; Mappes et al. 2005; Saporito et al. Panama, 2 aposematic coloration patterns are segregated by habitat, 2007)? Until recently there was no direct comparison of attack rates the Postman (yellow, red, and black; comprised of Heliconius mel- on cryptic and aposematic prey by wild predators in the field. pomene and Heliconius erato) occurs in open-canopy, disturbed Carroll and Sherratt (2013) used pastry baits with paper model habitats and the Blue–white (blue, white, and black; comprised of wings and found that aposematic prey and cryptic prey had the Heliconius cydno and Heliconius sapho) occurs in closed-canopy, same overall attack rates, but that aposematic prey were less fully undisturbed forest (Estrada and Jiggins 2002). Therefore, these 2 consumed than cryptic prey. In other words, although the attack different aposematic groups live in areas with different ambient illu- rate on aposematic prey and cryptic prey is similar, cryptic prey are mination (brighter and broad spectrum in open-canopy, while more likely to be fully consumed, rather than bitten and released. darker and rich in green light in closed-canopy), as well as with dif- Hence, there appear to be opportunities for aposematic, but not ferent avian predators (Endler 1993). Due to the habitat segregation cryptic, prey to be taste-rejected by predators, leading to higher sur- of these aposematic patterns, tests of environmental effects on the vival of aposematic prey (Wiklund and Ja ¨ rvi 1982; Pinheiro 1996; effectiveness of aposematic coloration are possible (Endler 1992). Nokelainen et al. 2014). Here, we utilized plasticine models of a cryptic species J. coenia, The intensity of selection from visually hunting predators will and the 2 species with aposematic color patterns (H. melpomene for not only be a function of unpalatability and predator cognition, but the Postman mimicry ring and H. cydno for the Blue–white mimicry also how coloration and backgrounds are perceived by the visually ring) to test 3 sets of hypotheses and predictions where both butter- hunting predators. Perception of prey depends upon several factors flies and educated predators naturally occur: 1) cryptic and apose- including the reflectance of the prey’s surface, the behavior of both matic individuals have evolved coloration to reduce predation and prey and predator, the ambient lighting, transmission properties of therefore will have similar attack rates; 2) the cryptic species has the environment, and predator visual sensitivity (Endler 1990, 1993; evolved to be undetected at rest and therefore the cryptic species will Stevens 2013; Hutton et al. 2015). These various determinants of have similar attack rates across both habitats; and 3) the aposematic trait perception have led to the hypothesis that the nature of selec- species’ warning signals are most effective in their respective habi- tion on cryptic and warning coloration will be different in disparate tats and therefore we predict that the Postman will be attacked less environments (Endler 1990, 1992; Stevens and Merilaita 2011). in open-canopy while Blue–white will be attacked less in closed- Camouflage depends on the ambient illumination and visual back- canopy habitats. ground; therefore, 1 phenotype may be cryptic in 1 set of conditions and very conspicuous in another (Endler and Greenwood 1988; Rojas 2014). Also, Douglas (2013) demonstrated that aposematic Materials and Methods butterflies differ in coloration depending on the habitat in which Model construction they are found, with tropical understory butterflies exhibiting high We collected 3 males each of H. melpomene (Postman pattern), achromatic contrast (i.e., black and white), while butterflies that H. cydno (Blue–white pattern), and J. coenia in lowland rainforest occupy open habitats exhibited highly chromatic contrasts (e.g., yel- habitats of central Panama in July 2012 using aerial nets. We then low and red). However, no study to date has tested attack rates of used these males to develop artificial models following the methods naturally cryptic individuals and of aposematic species in different of Finkbeiner et al. (2012) and Seymoure and Aiello (2015). The habitats. Different habitats should affect predation rates due to visi- models were constructed using scanned images (Brother MFC- bility of prey (e.g., dense forest vs. open fields), local abundance of J4510DW Scanner, Brother Industries, Nagoya, Japan) of ventral predators, environmental effects on conspicuousness (i.e., lighting wing surfaces of each species because individuals of Heliconius and and visual background), as well as differences in prey abundance Junonia perch with their wings closed unless they are thermoregulat- and predator experience with specific warning color patterns. ing or involved in courtship (Brown 1981; Devries 1987). High reso- Therefore, the environmental context must be considered when lution models were printed onto Whatman filter paper (GE assessing the survival advantages of particular “conspicuous” apose- Healthcare Life Sciences, Pittsburgh, PA, USA) with a Brother MFC- matic and “inconspicuous” cryptic phenotypes. J4510DW printer (Brother Industries) and then cut and inserted into Lepidoptera offer excellent opportunities to comparatively test the “body,” a 2.5-cm long piece of black, non-toxic plastalina mod- the environmental factors that affect the adaptive value of crypsis eling plasticine (Craftsmart, Irving, TX, USA), which remains malle- and aposematism (Endler 1984; Nokelainen et al. 2014). Many able in the field and thereby shows beak marks when attacked by Lepidoptera, such as the common buckeye butterfly Junonia coenia, the bill of avian predators (Finkbeiner et al. 2012; Merrill et al. are profitable prey with inconspicuous coloration when perched 2012; Seymoure and Aiello 2015). (Silberglied et al. 1979; Devries 1987; Pinheiro 1996; Camara 1997), whereas other species such as Heliconius butterflies sequester Model color measurements host plant toxins and display a conspicuous warning coloration To confirm that each model type was visually indistinguishable (Chai 1986; Devries 1987). Both J. coenia and Heliconius butterflies from the natural butterfly wings, we quantified full-spectrum reflec- occur in Panama (Brown 1981; Kozak et al. 2015). Unlike the palat- tance and incorporated the data into avian visual threshold models able J. coenia, Heliconius butterflies contain cyanogenic glycoside (Vorobyev and Osorio 1998; Maia et al. 2013). We measured the toxins (Cardoso and Gilbert 2013), which combined with their con- ventral reflectance of the main color patches for each species using 3 spicuous color patterns leads avian predators to avoid consuming male individuals and then measured the same color patches of 3 of them (Chai 1986; Finkbeiner et al. 2014; Langham 2005). Furthermore, Heliconius butterflies exhibit immense color diversity each printed model type using a USB2000 Spectroradiometer both within and between species and may have up to 5 different (Ocean Optics, Dunedin, FL, USA) and Xenon standardized light aposematic color patterns that are segregated by habitat in 1 forest source (Ocean Optics). Wing color reflectance was measured as the Downloaded from https://academic.oup.com/cz/article-abstract/64/5/663/4575132 by Ed 'DeepDyve' Gillespie user on 18 October 2018 Seymoure et al. Attacks on cryptic and aposematic butterflies 665 proportion of a white reference standard (WS-1-SL, Ocean Optics) open-canopy and closed-canopy, which were categorized by canopy using a coaxial fiber cable (QR400-7, Ocean Optics). We used avian cover (open canopy was defined as having <70% canopy cover, visual thresholds using the PAVO program within R (Maia et al. whereas closed-canopy had >90% canopy cover; author, unpub- 2013; R Core Team 2014) to determine if the artificial wing models lished data). Each specific block site was only used once and there accurately represented the coloration of natural wings, as seen were fewer locations in the closed-canopy habitats to place models, through the eyes of birds with both ultraviolet-sensitive (UVS) and so the overall sample size for open-canopy was 99 blocks while violet-sensitive (VS) visual systems (Vorobyev and Osorio 1998; closed-canopy was 50 blocks, for a total placement of 447 models. Osorio and Vorobyev 2005). Although the main predators of We conducted 8 different 3-day trials from February to April during Heliconius are jacamars and tyrant flycatchers (Pinheiro 2011), the dry season in 2013. These experiments took place during the dry which have the VS visual system, the predators of J. coenia may season for 2 reasons: because predation rates on insects are higher in include predators with either the VS or UVS visual system (Devries the dry than in the wet season and to avoid the potential for rain 1987). We applied von Kries transformation to account for receptor damage to the models (Kricher 2011). Each model was checked adaptation and used the default parameters for Weber’s fraction daily (11 AM–4 PM) for 3 days for beak, teeth, and mandible marks (0.05), illumination (D65 irradiance spectrum for standard day- (see Finkbeiner et al. 2012; Seymoure and Aiello 2015). Attacked light), background, and cone ratios of N1 ¼ 1, N2 ¼ 2, N3 ¼ 2, models were removed from the experiment and not replaced, to N4 ¼ 4 (Hart 2001: Maia et al. 2013). We calculated both achro- avoid inflating mortality rates among treatments (Cuthill et al. matic and chromatic just noticeable differences (JNDs) for each 2005; Finkbeiner et al. 2012; Merrill et al. 2012). We counted main color patch of each model compared with its respective natural only beak marks (i.e., triangular indentations, see Figure 1)as butterfly: Postman red, Postman yellow, Postman black, Blue–white predatory attacks. Models that disappeared were censored (i.e., white, Blue–white black, Blue–white red, Junonia brown, and included in the attack analyses until removed from the study Junonia orange, see Supplementary Figure S1. We did not run JND for non-relevant reasons) in the statistical analysis, because it is tests for the blue of the Blue–white mimicry ring because the blue is impossible to know if the models were removed by an avian iridescent and in most cases will be seen as black. It is only at certain predator or a non-relevant force (e.g., curious people, rodents, angles that a blue hue is reflected from the wing. As we were not wind) (Hurlbert 1984). Models that showed evidence of non-avian able to replicate the iridescence in these paper models, we focused attacks (i.e., teeth marks and gashes of mammals; small holes of on replicating the black, as this is most likely what predators will see insects) were also censored in the statistical analysis since these when butterflies are roosting. JNDs represent the ability of a visual attacks were unlikely to have been visually guided and are therefore system to perceive 2 colors differently, with a JND value of <1 being not a good indicator of color-based predation (Finkbeiner et al. indistinguishable in ideal conditions (Siddiqi et al. 2004). All com- 2012). parisons had JNDs of <1 for achromatic and chromatic compari- sons for both the V/Vis and UV/Vis visual systems, see Statistical analysis Supplementary Figures S2 and S3. Therefore, we inferred that in the Differences in attack rates after 72 h were analyzed using Cox eyes of birds the difference in coloration between the models and proportional-hazards regression (“survival” package) in R (RCore real butterflies would be minimal if not imperceptible. Furthermore, Team 2014). Missing models and non-avian attacks were censored spectral reflectance curves for each model fit within the natural in the Cox proportional-hazards regression. Model type (i.e., color variation of each species, see Supplementary Figure S1. Postman, Blue–white, and cryptic), habitat (i.e., open and closed), date of trial, and block were included in the Cox analysis. Both Attack rate experiments date of trial and block were analyzed as random factors. We also We tested the attack rates of our model types in 2 different habitats calculated the effect sizes with odds ratios (OR), where a value of in Soberania National Park in Central Panama (9.1 N, 79.7 W). 1.00 indicates that 2 models have identical probabilities of being Models were set out in blocks of 3 that included one of each color attacked. We must note that the OR test assumes that all model pattern (i.e., Postman, Blue-white, and Junonia). Within each block, types have an equal chance of being attacked and because we models were arranged randomly 1–3 m apart at heights ranging removed models once they were attacked, we violated a key test from 0.2 m to 2 m. We tied each model with black string to leaves assumption. However, we analyzed both the OR test and the Cox and branches of rainforest plants. Although we did not specifically proportional hazards 2 ways: 1) with all attacks included in the control for background, there is no evidence that Heliconius individ- uals or J. coenia choose a particular type of vegetation or back- ground for resting (Devries 1987; Mallet and Gilbert 1995). Furthermore, due to the heterogeneity of the vegetation at each site, it is unlikely that a predator would see all 3 models instantaneously. Each block was placed 100 m from the nearest block to reduce the risk of the same bird attacking models as most avian predators of butterflies have home ranges of <1ha(Buskirk et al. 1972; Karr 1977). Furthermore, it is unlikely that predators learned that the plasticine body was unprofitable due to the few exposures of the plasticine bodies. Learning experiments indicate that birds need Figure 1. Examples of artiﬁcial models placed in the ﬁelds with marks inter- more than 3 experiences to learn unpalatability and thus develop preted as beak marks from attacks by avian predators on plasticine-paper avoidance (Skelhorn et al. 2016). As we were testing the efficacy of models. Arrows point to beak marks. Left, a beak mark on the plasticine abdo- the coloration of the 3 species of butterflies, we did not manipulate men of a Postman model; central, a beak mark on the plasticine abdomen of secondary defenses to control for any chemical cue that predators a Blue–white model; right, the wing pulled from the body of the J. coenia may rely upon. Blocks of models were placed in each habitat type, model. Downloaded from https://academic.oup.com/cz/article-abstract/64/5/663/4575132 by Ed 'DeepDyve' Gillespie user on 18 October 2018 666 Current Zoology, 2018, Vol. 64, No. 5 Table 1. Number of models that displayed evidence of avian and non-avian attacks, or went missing during the trials for each species and habitat Species Open Closed N Avian attack Non-avian attack Missing N Avian attack Non-avian attack Missing H. melpomene 99 20 3 10 50 3 3 1 H. cydno 99 15 0 8 50 5 1 1 J. coenia 99 9 2 14 50 2 1 0 The number of models placed is represented by N. analysis regardless of whether the model was attacked first in the block or after an initial attack on another model in the same block; and 2) with only the models in a block that were attacked first and other sequential attacks were censored. Both statistical approaches resulted in the same test statistics and thus we conclude that although the methods may have violated a statistical assumption of the OR test, our findings are rigorous. Results Over the 8 different trials, all of which lasted 3 days, 12.1% (54/ 447) of the models showed evidence of attack by birds. Avian attack rates in the open habitat were 14.8% (44/297) and in the closed habitat were 6.7% (10/150). Attacks by non-avian predators (e.g., rodents and insects) contributed another 2.2% (10/447), while 7.6% (34/447) of the models were missing (Table 1). Lastly, the open habitat had 10.8% (32/297) of the models missing while the closed only had 1.3% (2/150). The high rates of missing models in the open habitat are due to areas of forest being clear cut and remov- ing 15 models, 5 of each model type. We included these missing models into our analysis because the clear cutting occurred after day 1, thus allowing for the use of attack data from these models for at least 1 day. Model survivorship curves differed significantly by model type (Cox regression, F ¼ 2.049, P ¼ 0.040; Figure 2A) and habitat (Cox regression, F ¼ 2.536, P ¼ 0.011; Figure 2B), but not with placement Figure 2. Survival curves for the 3 different models. Red represents postman H. melpomene, blue represents Blue–white H. cydno, and brown represents date (Cox regression, F ¼ 1.784, P ¼ 0.074), nor the random factor the cryptic model J. coenia.(A) Combined habitat survival curves for each of block (Cox regression, v ¼ 0.07, P ¼ 0.53). Also, the model sta- morph. (B) Individual survival curves for each morph in each habitat. Long tistic was the same regardless if only the first model attacked was dashes represent survival in the open habitat while dots represent survival in included in the model when compared with having all attacks in the closed habitat. each block included. Furthermore, there was not an interaction between model type and habitat (Cox regression, F ¼ 0.533, Discussion P ¼ 0.594). Pairwise comparisons revealed that independent of habi- Previous research has shown that both cryptic individuals and apo- tat, aposematically colored H. melpomene models were attacked sematic individuals have similar attack rates in artificial prey more often than cryptically colored J. coenia models (Wald ¼ 10.18, (Carroll and Sherratt 2013). Here, we demonstrate that attack rates df ¼ 2, P ¼ 0.006, OR ¼ 2.290), but aposematically colored H. mel- on 2 different aposematic species (Heliconius) and cryptic (Junonia) pomene had similar attack rates to aposematically colored H. cydno individuals depend on coloration as well as the environment. We models (Wald ¼ 5.26, df ¼ 2, P ¼ 0.061, OR ¼ 1.177). Heliconius found that the aposematic Postman models were attacked more than cydno and J. coenia models also had similar attack rates the cryptic model, yet the 2 aposematic color patterns had similar (Wald ¼ 4.73, df ¼ 2, P ¼ 0.094, OR ¼ 1.945). Also, the number of attack rates. Furthermore, the attack rates differed among habitats attacks on H. melpomene differed between habitat types with much with more attacks occurring in the open habitat than in closed habi- higher predation in the respective, open habitat of H. melpomene tat. Our results, along with Carroll and Sherratt’s (2013) results, (Wald ¼ 4.48, df ¼ 1, P ¼ 0.034, OR ¼ 3.966; Supplementary Figure indicate that aposematic theory needs to include factors other than S4), while the number of attacks on the other 2 species did not differ just conspicuousness and unpalatability. between habitats (H. cydno: Wald ¼ 0.840, df ¼ 1, P ¼0.358, Heliconius butterflies are aposematic and several studies have OR ¼ 1.607; J. coenia: Wald ¼ 1.38, df ¼ 1, P ¼ 0.240, OR ¼ 2.4; demonstrated that avian predators recognize the visual warning sig- Supplementary Figure S4). nals of Heliconius to avoid attacking individuals (Chai 1986, 1996; Downloaded from https://academic.oup.com/cz/article-abstract/64/5/663/4575132 by Ed 'DeepDyve' Gillespie user on 18 October 2018 Seymoure et al. Attacks on cryptic and aposematic butterflies 667 Chai and Srygley 1990; Langham 2004, 2005). Previous research on fledglings begin foraging during the dry season and may have not the avian community in central Panama has revealed that the closed learned to avoid aposematic species (Skutch 1968; Hoyo et al. 2004). habitat has different insectivorous bird species compared with open There were more overall attacks for each species in the open hab- and edge habitats (Karr 1977; Samuel et al. 1985; Poulin and itat, although there was only a significant difference for H. melpo- Lefebvre 1996; Robinson et al. 2000). However, at the family level, mene. This finding is most likely due to visibility and predator the composition is similar with the main Lepidoptera predators composition. The closed, forested site where models were placed being non-migratory flycatchers, jacamars, and warblers (see Poulin was thick with vegetation and therefore it may have been harder for and Lefebvre 1996; Robinson et al. 2000). The likely avian preda- birds to detect even the conspicuous models. Also, predator compo- tors of Heliconius and other tropical butterflies are flycatchers and sition varies between the 2 habitats and the forest edge habitat has jacamars (Pinheiro 1996), which often aerially attack prey at the high abundance of insectivorous birds such as tyrant flycatchers (del thorax and then either consume palatable prey or taste reject chemi- Hoyo et al. 2004). cally defended prey (Pinheiro 2011). Thus, our study is complicated The Postman coloration was attacked more in its respective habi- at 2 levels: 1) our models were sedentary and may not be the best tat than in the habitat where it does not reside. This is contrary to surrogate for naturally occurring attack rates and 2) our models did our predictions as we predicted that predation on aposematic mod- not differ in palatability and we could not assay taste rejection by els would be lower where the aposematic model is common due to avian predators. Taste rejection is likely an adaptation to find palat- experienced predators as has been supported by previous research able mimics of aposematic prey and the act of taste rejection has (Mallet and Barton 1989; Merrill et al. 2012). As stated previously, been shown to leave butterflies intact and capable of flight (Wiklund this suggests that avian predators are likely attacking aposematic and Ja ¨ rvi 1982; Sillen-Tullberg 1985; Pinheiro 1996, 2011). individuals and then deciding whether to consume or reject the prey Therefore, although we found that the cryptic species had fewer dependent upon chemical defenses (Wiklund and Ja ¨ rvi 1982; Sillen- attacks than the aposematic Postman species, we were not able to Tullberg 1985; Pinheiro 1996; Pinheiro 2011; Carroll and Sherratt determine whether the aposematic species would have been taste 2013). Heliconius species have many palatable mimics that may be rejected since the bodies were plasticine. It is likely that the survival rewarding avian predators that test the palatability of prey items rates of all 3 species are similar in wild butterflies due to taste rejec- (Pinheiro 1996, 2007, 2011). And if the palatable mimics are segre- tion by birds. In fact, Carroll and Sherratt (2013) demonstrated that gated by habitat like their aposematic model (i.e., Postman butter- artificial models made to be unpalatable with quinine pastry baits, flies), then predators may be searching for individuals with the were attacked at the same rate as palatable, cryptic pastry bait mod- Postman coloration. Furthermore, the Postman has high chromatic els, but that the unpalatable pastry baits were taste rejected more contrast (red, yellow, and black color pattern) and thus is highly often. Future studies to test taste rejection in these species of butter- noticeable in well-lit environments like edge habitats and may be flies in the wild are needed to better understand the role of predator easier to detect by avian predators in the edge habitat (Douglas behavior in selecting for aposematic and cryptic phenotypes. 2013). Further research into the rates of taste rejection in apose- Our study replicated components of the study by Merrill et al. matic species is needed to understand the evolutionary processes (2012) in that we used plasticine models of Postman and Blue–white behind warning coloration and mimicry. butterflies in Panama to determine if predation rates differed Plasticine models have been used to test many hypotheses between aposematic morphs in different habitats. Although we explaining differences in morphology, as well as hypotheses relative found similar results as Merrill et al. (2012) for the overall study in to the ecology and evolution of predator–prey interactions that butterflies were not less likely to be attacked in their respective (Papageorgis 1975; Cuthill et al. 2005; Finkbeiner et al. 2012; environment, we found that overall attack rate did differ between Seymoure and Aiello 2015). However, in several such studies, the forest edge and forest habitats, whereas Merrill et al. (2012) did not plasticine model manipulations done to address the questions they find differences in attack rates dependent upon habitat. Our findings proposed are artificial and do not resemble any natural prey item may differ from Merrill et al. (2012) because we tested predation (see Cuthill et al. 2005; Carroll and Sherratt 2013) or are drastically during the dry season instead of the wet season. Avian predation has different from the natural coloration (see Finkbeiner et al. 2014; been reported to increase during the dry season due to lower avail- Seymoure and Aiello 2015). It is conceivable that this may lead to ability of prey, which may mean that aposematic prey are attacked attack rates that are higher than would occur with natural colora- more during the dry season than in the wet season (Kricher 2011). tion. Hence, the comparatively low predator attack rates that we In fact, we observed an attack rate that was 3 times that recorded by observed might be due to the relatively natural appearance of the Merrill et al. (2012; 12% compared with 4%), even though the plasticine models that we used. overall methods were very similar. Seasonal differences in attack Our findings here suggest that both aposematism and cryptic col- rates have also been reported by Mappes et al. (2014), who found oration have low attack rates in the wild. However, the plasticine that the attack rates of cryptic and aposematic larvae in Finland var- models are a surrogate for wild butterflies and may not be equally ied with season. Specifically, Mappes et al. (2014) attributed the sea- representative of the attack rates for living cryptic and aposematic sonal attack differences between cryptic and aposematic larvae to individuals. Most prey items move, especially butterflies, and the seasonal differences in the prior experiences of avian predators. models used in this study were static, so perhaps predation rates Naı ¨ve fledglings attacked more aposematic prey than cryptic prey, between cryptic and aposematic animals differ when movement is but later in the year when all birds were experienced, the cryptic included. In fact, cryptic organisms are hypothesized to move less prey were attacked more than aposematic prey. In our study, it is than conspicuous organisms because predators can use movement to possible that differences in predation rates between aposematic and detect prey (Stevens and Merilaita 2011). cryptic morphologies were due to bird age and experience. Both In conclusion, our study suggests that both aposematic colora- tyrant flycatchers and jacamars have breeding seasons that begin at tion and cryptic coloration can be adaptive strategies for avoiding the transition from wet season to dry season and thus naı ¨ve predation at rest as all models had low attack rates. The findings Downloaded from https://academic.oup.com/cz/article-abstract/64/5/663/4575132 by Ed 'DeepDyve' Gillespie user on 18 October 2018 668 Current Zoology, 2018, Vol. 64, No. 5 Devries PJ, 1987. The Butterﬂies of Costa Rica and Their Natural History. suggest that the form of aposematic coloration and the habitat (i.e., Vol. I: Papilionidae, Pieridae, Nymphalidae. Princeton: Princeton University open-canopy vs. closed-canopy) in which an organism resides affects Press. the predation rate. All 3 color forms were attacked more in the open Douglas JM, 2013. Ambient Light Environment and the Evolution of habitat, which is most likely due to visibility and perhaps greater Brigthness, Chroma, and Perceived Chromaticity in the Warning Signals of abundance of predators. Furthermore, the more chromatic apose- Butterﬂies. Tempe: Arizona State University. matic species was attacked more than the cryptic species. Lastly, this Edmunds M, 1974. Defence in Animals. Englewood Cliffs (NJ): Prentice Hall study highlights the need for further research into the tradeoffs of Press. crypsis and aposematism including using avian visual models to Endler JA, 1981. An overview of the relationships between mimicry and cryp- determine how different habitats (open vs. closed) affect the conspic- sis. Biol J Linn Soc 16:25–31. uousness of color patterns. 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Published: Oct 1, 2018
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