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. 2016 Mar 16;62(3):227–235. doi: 10.1093/cz/zow014

Lack of functional link in the tadpole morphology induced by predators

María Gabriela Perotti a,*, Mariana Pueta a,b, Fabián Gastón Jara a, Carmen Adria Úbeda c, Debora Lina Moreno Azocar a
PMCID: PMC5804239  PMID: 29491910

Abstract

Most studies of predator-induced plasticity have focused on documenting how prey species respond to predators by modifying phenotypic traits and how traits correlate with fitness. We have previously shown that Pleurodema thaul tadpoles exposed to the dragonfly Rhionaeschna variegata responded strongly by showing morphological changes, less activity, and better survival than non-exposed tadpoles. Here, we tested whether there is a functional link between morphological plasticity and increased survival in the presence of predators. Tadpoles that experienced predation risk were smaller, less developed, and much less active than tadpoles without this experience. Burst speed did not correlate significantly with morphological changes and predator-induced deeper tails did not act as a lure to divert predator strikes away from the head. Although we have previously found that tadpoles with predator-induced morphology survive better under a direct predator threat, our results on the functional link between morphology and fitness are not conclusive. Our results suggest that in P. thaul tadpoles (1) burst speed is not important to evade predators, (2) those exposed to predators reduce their activity, and (3) morphological changes do not divert predator attacks away from areas that compromise tadpole survivalEE. Our results show that morphological changes in P. thaul tadpoles do not explain burst speed or lure attraction, although there was a clear reduction of activity, which itself reduces predation. We propose that changes in tadpole activity could be further analyzed from another perspective, with morphological change as an indirect product of behavior mediated by physiological mechanisms.

Keywords: induced morphology, lure effect, predator exposure, swimming performance, tadpoles


Inducible morphological defenses have served as model systems to test the evolution and maintenance of phenotypic plasticity as an important source of natural variation (Agrawal 2001). Most studies of predator-induced plasticity have focused on documenting how prey species respond to predators by modifying several traits and how traits correlate with fitness. Many studies have focused on Arnold's (1983) paradigm, “Morphology, performance and fitness,” by analyzing the effect of trait variation on performance and fitness (Kingsolver and Schemske 1991; Scheiner et al. 2000; Johnson et al. 2008; Calsbeek and Kuchta 2011). When exposed to predators, larval amphibians develop inducible defenses as changes in morphology (e.g., deeper or colored tails) and/or changes in behavior (e.g., decreased activity or increased refuge use) (Morin 1986; Skelly and Werner 1990; Skelly 1996; Van Buskirk et al. 1997; Van Buskirk and McCollum 1999; Relyea 2001; Kishida and Nishimura 2004; Laurila et al. 2004). These induced defenses (Tollrain and Harvell 1999) can be effective but are sometimes associated with costs, and tadpoles exposed to predators are usually smaller and/or less developed than non-exposed tadpoles (Werner 1992; Storfer et al. 1999; LaFiandra and Babbitt 2004; Steiner 2007; Steiner and Van Buskirk 2008; Touchon and Warkentin 2008). Some studies have correlated swimming responses (in acceleration or speed) in tadpoles with induced morphological characters, such as wider, longer, and deeper tails (Dayton et al. 2005; Teplisky et al. 2005). Additionally, changes in morphology may also act as predator distracters, as proposed in the “lure effect” hypothesis, which proposes that larger tails may distract the predator from attacking vulnerable regions of the body (Van Buskirk et al. 2003; Johnson et al. 2008). Recent studies have shown that survival of tadpoles is enhanced through changes in body and tail shape that either affect swimming performance or serve as a “lure” to attract predators (Johnson et al. 2008; Calsbeek and Kutcha 2011). We know from previous studies that tadpoles of Pleurodema thaul (Schneider 1799) (Anura: Leptodactylidae) exposed to non-lethal risk of predation by the dragonfly Rhionaeschna variegata (Fabricius 1775) reduce their activity and change their morphology (deep tails and small sizes) (Jara 2010; Jara and Perotti 2010).

Based on this information, we performed a series of experiments to test whether the morphological changes induced in P.thaul tadpoles pre-exposed to predators correlate with functional response components (burst speed and lure effect), which ultimately enhance tadpole fitness (survival). We have previously determined that tadpoles with previous exposure to predators have better survival than tadpoles without this experience (Jara 2010). We predicted that the morphological changes induced by predators result in better burst swimming performance to evade predation and/or that the distractive effect (lure effect) should direct predator strikes more often on tails rather than on vital body parts. Thus, we expected (1) that morphological changes correlate with swimming performance in tadpoles pre-exposed to predators, implying an adaptive response, and/or (2) that tadpoles developing morphological changes attract predator attacks to body parts that result in enhanced survival (i.e., inducing non-lethal attacks).

Materials and Methods

Study system

We studied a common predator–prey system that occurs in temporary and semipermanent wetlands in Northwestern Patagonia (Argentina) composed of tadpoles of P.thaul (prey) and larvae of R.variegata (Anysoptera: Aeshnidae) (predator) (Jara and Perotti 2010). Both tadpoles and larvae were collected from the same site (Fantasma lagoon, 41°05′S, 71°27′W, 794 m.a.s.l.; Río Negro province, Argentina) in October 2011 and October 2012. Specimens collected in 2011 were used to study the morphological responses of tadpoles exposed to R. variegata larvae and the relationship between morphology and burst speed, whereas specimens collected in 2012 were used to test whether morphological changes apply to the hypothesis of “lure effect.” All procedures were authorized by the corresponding authorities of Nahuel Huapi National Park and Subsecretaria de Medio Ambiente of San Carlos de Bariloche, Río Negro, Argentina.

Effect of predator exposure on morphology and burst swimming performance

The 8 clutches of P. thaul (Gosner stages 11–13; Gosner 1960) collected in October 2011 were reared outdoors in eight 500-L containers under natural photoperiod and temperature conditions. After hatching, tadpoles of all 8 clutches were mixed and reared to reach developmental stages 25–26 (total length average: 13.7 ± 0.11 mm; free swimming tadpoles, 2 weeks old; Gosner 1960) to avoid confounding genetic effects when setting the experiment.

Next, we conducted a completely randomized experimental design, in which tadpoles were reared under 2 predation conditions (treatments): presence and absence of caged predator larvae of R. variegata. Treatments were replicated in 60 plastic containers (15 L) filled with tap water (30 replicates for each treatment). The bottom of each container was covered with 500 g of fine sediment and each tank was inoculated with 500 mL of an algal culture mixture (Chlamydomonas sp. + Scenedesmus sp.) as food. Each replicate consisted of a plastic cage (5 cm × 10 cm) with six tadpoles selected at random from the rearing containers. The 30 replicates of the predator treatment contained 1 caged larva of R. variegata (average size 28.99 mm ± 1.94 mm) whereas the other 30 replicates of the non-predator treatment consisted of empty cages. The water volume in the containers was kept constant, checked and cleaned daily, and re-filled when necessary. The larvae of Rhionaeschna in the predator treatment were fed every other day with one P. thaul tadpole. Therefore, tadpoles in the predator treatment were provided with a combination of chemical cues from the predator (kairomones) and chemical cues derived from the damage (alarm cues) and digestion of conspecifics (Schoeppner and Relyea 2009). Cages with predators were checked daily and those with dead larvae or predators that had stopped feeding were replaced by a new larva of similar size.

The experiment finished 50 days later, before forelimbs emerged (around stage 39, Gosner 1960). At this stage, tadpoles from all treatments were photographed for later measurement of morphological features. Each tadpole was photographed in its lateral view with a digital camera (Canon PowerShot IF S5). Photographs were taken from the same distance and under the same light conditions (Figure 1), and then analyzed using the ImageJ software (version 1.47). The following morphological measurements were obtained from the digital images: tail length (TL), body length (BL), body depth (BD), tail muscle depth (MD), tail fin depth (TD), and total tadpole length (TTL) (Figure 1). These measurements were considered as important for swimming trials (Smith and Van Buskirk 1995; Relyea 2001). Tadpole measurements from each replicate were averaged to analyze morphological features in each treatment. In addition, size and developmental stage of each tadpole were measured 30 days after the beginning of the experiment in the 2 treatments and the average of each replicate was used for the analysis (exposure and non-exposure to predator risk).

Figure 1.

Figure 1.

Digital photograph showing tadpole morphological measurements and sections considered for predator attacks (white dotted lines). Total tadpole length (TTL); Tail length (TL); Body length (BL); Body depth (BD); Tail muscle depth (MD); and Tail fin depth (TD).

We used a racetrack (1 m long × 0.08 m wide × 0.12 m high) with 7 LED sensors and beams (spaced every 0.10 m) connected to an electronic circuit and hooked up to a computer to measure burst speed (maximum speed in m/s) of tadpoles from the 2 treatments; the maximum velocity measured was considered analogous to burst speed. Measurements were performed on a same day for all tadpoles. The racetrack was placed in an indoor experimental room provided by 2 fluorescent lamps (Philips daylight, TLT 40 W/54RS) and filled with tap water at 15°C until 0.10 m depth. Sixty tadpoles (30 per treatment) at stages 40–41 were used to measure burst swimming performance. These 60 tadpoles were obtained by randomly selecting 1 tadpole from each replicate (total length of tadpoles in the predator treatment was 21.52 ± 0.62 whereas that in the non-predator treatment was 24.42 ± 0.54). Tadpoles were allowed to habituate for a couple of minutes and a predator attack was simulated by touching the tail with a stick. Each tadpole performed 3 races, with 1-min rest between races. Water was changed between trials. Only the best of the 3 runs was considered at the “burst speed” run for each specimen. Usually, the first run after simulating the attack was the one computed as the best run.

Effect of predator exposure on morphology and lure effect

To study predator strikes, we conducted a second experiment with the clutches collected in October 2012. To induce morphological changes by the presence of the predator, we followed the same protocol as in 2011 but varying the number of replicates (12 replicates for the predator treatment and 11 replicates for the non-predator treatment), and recorded the same morphological measurements (TL, BL, BD, MD, TD, and TTL).

To record the predator attacks, we took into account the different vulnerability of 2 sections of a tadpole body (as described by Van Buskirk et al. 2003, Figure 2): (1) head/body plus one-third of the tail section (from now on “head”) and (2) the last two-thirds of the tail section (from now on “tail”) (Figure 1). Each replicate consisted of groups of 5 tadpoles from the same rearing container exposed to 1 free Rhionaeschna larva in 1-L plastic containers. Before the experiment, tadpoles were allowed to acclimate for 3 min and after acclimation a larva was placed on a perch. We recorded predator attacks in 17 experimental units (6 experimental units were discarded because they did not complete the minimal of 5 tadpoles per replicate): nine with tadpoles from the predator treatment and eight from the non-predator treatment. Predators were starved for 48 hours prior to the start of the experiment to increase hunger level and standardize motivation. We used a digital video camera (Sony HDR-XR200V; 30 frames s-1) placed 0.70 m above the container to record both the predator and prey for 30 min. Between each test, the containers were cleaned and the water replaced. Testing all the individuals took 2 days.

Figure 2.

Figure 2.

Body and tail changes of P. thaul after experimental switch of predator setting in 2 different years.

Video recordings were evaluated using VLC media player 2.0.1, which allows the observer to reduce the playback speed to 0.02 x and thus accurately determine strike location (head or tail of tadpoles). A larval labium contacting a tadpole was considered a strike. We analyzed only the first strike in each container and did not record subsequent attacks because we considered that predator strikes on scared tadpoles were not comparable to those on unaware tadpoles. Additionally, we quantified the proportion of active tadpoles (the number of tadpoles moving in each cage). Activity was recorded for each replicate and expressed as the proportion of active tadpoles over total observations (30) per container (Jara and Perotti 2010). A tadpole was considered active if it was either swimming or moving the tail. All tadpoles were weighed at the end of the evaluation. Weight was calculated as the mean value per replicate.

Statistical analysis

For analyses of tadpole morphology, we performed a univariate GLM for each ln-transformed trait with predator treatment as a factor. To evaluate the effect of the predator on morphological traits, we performed ANCOVAs. We controlled for differences in size by including size (centered TTL measure) as a covariate in the model (Berner 2011; El Balaa and Blouin-Demers 2013; Touchon and Wojdak 2014). In general, we ran reduced models (without interaction), because interactions between TTL and treatment were not significant; the only exception was BL in 2011 for which we ran the full model. TTL and developmental stage were compared between predator treatments by a t-test in both experiments (2011 and 2012).

To explore the effect of morphology on performance gradients (effects of size and morphological traits on swimming speed), we ran generalized least squares (GLS) models considering every treatment separately. GLS models were performed considering all possible models with morphological predictor variables (BL, TL, BD, MD, TD, and TTL), and burst speed as dependent variable. All the analyses were performed using the ‘dredge’ function of the ‘MuMIn’ package (Multi-Model Inference. R package version 1.12.1; Barton 2014), which performs automated model selection. To ensure that the regression model provided the best fit among the candidate models (Angilletta 2006), we used the Akaike information criterion (AIC). Because of the limited number of samples, we used the AIC for small sample sizes and Akaike weights (Wi), which indicates the probability that a given model is the best among a series of candidate models (Burnham and Anderson 2004). Model averaging (typified by AIC) was calculated to estimate the effect size of every predictor variable on the response variable (burst swimming), considering the subset of models where the target variable appeared (Burnham et al. 2011).

We analyzed predator strikes, activity and body mass of tadpoles as a function of predator treatments. Scores of predator strikes were analyzed by Chi-square test. Tadpole activity and tadpole size were analyzed by parametric t-tests for independent samples. To explore the relationship between tadpole activity and tadpole size, we performed Pearson correlation between the total proportion of active tadpoles and the mean body weight of the tadpoles in each container.

Results

Morphology in P.thaul tadpoles covaried with tadpole size and some specific traits were affected by the predator treatment (Table 1). Body length and tail fin depth were affected by the predator treatment in the two seasons evaluated; during 2012, tail fin length was also affected. Tadpoles exposed to caged predators showed shorter body length, greater tail fin depth, and longer tail fin length than non-exposed tadpoles (Figure 2). The analysis of body length in 2011 showed an interaction between the predator treatment and tadpole size, indicating that body length increased with tadpole total length. No differences were observed in body depth or tail muscle depth between treatments in either experiment (2011–2012) (Figure 2).

Table 1.

Univariate GLMs with TTL as covariate testing for mean differences in morphological traits between predator treatments in 2011 and 2012

Source Season-2011
Season-2012
F P-value F P-value
Body length
 Predator 4.499 0.038 7.789 0.011
 TTL 106.511 0.000 73.304 0.000
 *Predator x TTL 4.586 0.036 ‐ ‐
Body depth
 Predator 1.295 0.259 1.339 0.261
 TTL 66.542 0.000 80.036 0.000
Tail muscle depth
 Predator 2.269 0.137 0.088 0.769
 TTL 23.352 0.000 107.688 0.000
Tail fin depth
 Predator 5.321 0.025 68.209 0.000
 TTL 47.718 0.000 230.234 0.000
Tail fin length
 Predator 2.139 0.149 17.198 0.000
 TTL 133.431 0.000 514.989 0.000

Significance is highlighted in boldface. *Only significant interaction.

Tadpole size (total length) and developmental stage were affected by the presence of the predator in the same way. After 30 days, tadpoles exposed to caged predators were smaller and less developed than non-exposed tadpoles (2011 t-test; size t = 2.0, df = 58, P < 0.001, developmental stage, t = 2.2, df = 58, P < 0.05; 2012 t-test; size t = 2.07, df = 15, P < 0.001, developmental stage, t = 7.74, df = 15, P < 0.001; Figure 3).

Figure 3.

Figure 3.

Average changes in tadpole size (mm) and developmental stage (Gosner 1960) after 30 days of exposure and non-exposure of predator risk (black circles = experiment 2011, white circles = experiment 2012). Total tadpole length (TTL).

Swimming speed did not differ significantly between treatments (predator treatment: 0.150 m/s ± 0.004; non-predator treatment: 0.165 m/s ± 0.009; t-test, t = 1.67, df = 58, P = 0.49). However, since we observed morphological changes, we used GLS models to test the effect of morphological traits (after predator treatment) on swimming. In the predator treatment, the swimming of tadpoles showed that the model including tail fin depth presented the lowest AICc value, although the regression coefficient value was low (see Appendix; VELOC∼TD, R2 = 0.029, AICc = −72.454, Wi = 0.082). In the non-predator treatment, the lowest AICc was observed in the model including body depth (BD) (Appendix; VELOC∼BL, R2 = 0.023, AICc = −50.969, Wi = 0.082). Parameter estimates after model averaging in the predator treatment showed that no variable contributed significantly to the models evaluated and that body length was the only variable with positive effect on tadpole swimming. In contrast, in the non-predator treatment, tail fin depth and tail length showed a negative effect on tadpole swimming while all the other traits showed a positive effect (Table 2). The analysis of strikes on the head and tail of tadpoles was not significant (χ2 = 0.055, P > 0.8).

Table 2.

Model averaged parameter estimates from the model selection explaining the effect of predator-induced morphological variables on burst swimming

Estimate SE z value Pr( > |z|)
Predator
Intercept 0.201 0.260 0.748 0.454
TD −0.077 0.101 0.731 0.465
TL −0.138 0.211 0.632 0.527
TTL −0.003 0.011 0.271 0.786
BD −0.032 0.116 0.269 0.788
BL 0.162 0.196 0.800 0.424
MD −0.007 0.083 0.078 0.938
No Predator
Intercept 0.333 0.805 0.404 0.686
BD 0.109 0.209 0.496 0.620
BL 0.150 0.305 0.471 0.638
TTL 0.013 0.022 0.558 0.577
MD 0.077 0.262 0.284 0.776
TD −0.042 0.278 0.144 0.886
TL −0.335 0.391 0.829 0.407

Predictor variables correspond to: Total tadpole length (TTL), Tail length (TL), Body length (BL), Body depth (BD), Tail muscle depth (MD), and Tail fin depth (TD). Shown are: Averaged coefficient (estimate), unconditional standard error, z-test statistic, and associated P-value.

We also found significant differences in the activity of tadpoles (t = −2.18; df = 15, P < 0.05): tadpoles exposed to the predator were less active than non-exposed tadpoles (predator treatment: 0.18 ± 0.02, n = 9; non-predator treatment: 0.23 ± 0.01, n = 8). Tadpole weight was also significantly affected by the predator treatment (t = −4.39; df = 15, P < 0.00005), with larger tadpoles in the non-predator treatment (predator treatment: 0.30 ± 0.02, n = 9; non-predator treatment: 0.44 ± 0.03, n = 8). However, activity was not correlated with tadpole weight (Pearson r = 0.37, P = 0.15, n = 17).

Discussion

In the present study, we found no direct evidence that morphology per se represents a trait that directly correlates with enhanced performance or acts as a predator distracter. However, the activity of tadpoles revealed significant differences between treatments, and body mass and developmental stage were also significantly affected by the presence of the predator, with tadpoles exposed to predators being less active and smaller than non-exposed tadpoles. However, in previous studies we observed that P.thaul tadpoles exposed to a scent signal indicating non-lethal risk of predation (caged predator) by the dragonfly R.variegata responded strongly by showing changes in their morphology such as deeper tails and bodies and enhanced survival, thus supporting the hypothesis of a fitness benefit (Jara 2010).

Predator-induced morphological changes that improve the swimming performance of tadpoles are not quite evident (Dayton et al. 2005; Teplitsky et al. 2005; Arendt 2009). We expected that tadpoles that increased their tail fin depth showed faster swimming performance (Van Buskirk and McCollum 2000). However, we found no significant relationship between morphology and performance. GLS models also confirmed these findings; although morphological traits influenced swimming performance differently in each treatment, the models showed no significant effect.

Previous studies showing no significant relationship between morphology and swimming in tadpoles later tested the tail lure tactic as a way to distract predators as an alternative hypothesis to understand this relationship. Some of these studies found that distractive tactics are a good intermediate predictor of enhanced survival (Van Buskirk et al. 2003; Johnson et al. 2008). However, in the present study, when we tested the lure effect based on different body vulnerability (see section “Methods”), we found no differences on strikes on the head or tail between tadpoles exposed and not exposed to the predator. Additionally, P.thaul tadpoles did not develop conspicuous tail coloration in the presence of the predator, as previously observed in other anuran species (Caldwell 1982; McCollum and Van Buskirk 1996; Skelly 1997). Instead, changes in morphology in P. thaul could be the result of the allometric growth that goes along with the abovementioned changes affecting life history features as observed in other vertebrates (Pettersson and Brönmark 1997, 1999; Andersson et al. 2006; Frommen et al. 2011).

Morphological changes could primarily be the result of physical constraints or biological interactions imposed on the developing organisms, ultimately affecting the expression of morphology (Abdala and Ponssa 2012). As suggested by Bourdeau and Johansson (2012), many examples of predator-induced morphological defenses in animals may actually be indirect effects (by-products) of alterations in prey behavior, rather than direct adaptive morphological responses to predation cues. They proposed that activity, growth rate, and morphology are often highly integrated traits. Then, as shown in previous studies (Jara and Perotti 2010), activity in P.thaul tadpoles seems to be the functional link that explains the increased survival of tadpoles in the presence of predation risk. Moreover, the reduction in activity can be interpreted as a change in the behavior of tadpoles, potentially resulting in morphological changes.

We know that P.thaul tadpoles pre-exposed to predators show enhanced survival (Jara 2010) and that they innately respond to conspecific alarm cues (Pueta et al. 2016) and to caged odonate larvae fed with mosquito larvae (Jara and Perotti 2010). Then, being less active can make these tadpoles less conspicuous when they are at risk of predation, and pre-exposure to caged predators and damaged conspecifics can give tadpoles an advantage when they face a free predator (Alvarez and Nicieza 2006; Mirza et al. 2006; Polo-Cavia and Gómez-Mestre 2014). However, more evidence is needed to find out whether the behavioral plasticity (low activity) of tadpoles exposed to predator risk affects traits (as the morphological changes observed) that are not necessarily related to a functional correlation (tadpole swimming).

We conclude that the morphological changes observed may be related to other unmeasured traits rather than serving as a functional link to swimming performance or lure distraction (Arendt 2003, 2010; Calsbeek and Kuchta 2011). Pleurodema thaul tadpoles occur in environments that vary in predator density and composition, and experimental studies have shown that they survive more if they have prior experience to predators (Jara 2010). Although our results do not elucidate the functional correlation of the traits, they provide evidence that tadpoles respond when they have previous predator risk experience.

Acknowledgments

We acknowledge the critical reading of early versions of this manuscript by A. Herrell and anonymous reviewers that helped to considerably improve of the manuscript. Thanks to D. Basanta for help with the fieldwork. We thank C. Chehébar and L. Buria (APN, National Parks of Argentina), and Subsecretaria de Medio Ambiente of San Carlos de Bariloche (SMA) authorities for providing collection permits. This investigation was performed under the institutional animal care guidelines established by APN and SMA. This work was partially supported by Universidad Nacional del Comahue (B166-UNCOMA to MP, FGJ, and MGP), Agencia Nacional de Promoción Científica y Tecnológica (PICT 2013‐2384-BID, to MP) and Consejo Nacional de Investigaciones Científicas y Técnicas (PIP-11220110100782, to MGP).

Appendix

Appendix 1.

Generalized Least Square Models evaluating morphological traits (body length = BL, tail length = TL, body depth = BD, tail muscle depth = MD, tail fin depth = TD, and total tadpole length = TTL) on swimming performance of tadpoles from 2 predator treatments (SP = swimming from tadpoles exposed to predator, SNP = swimming from tadpoles non-exposed to predators)

Treatment Model Intercept BD BL MD TD TL TTL R2 LL AICc Δi Wi
SP VEL ∼ TD 0.202 −0.033 0.029 39.688 −72.454 0.000 0.082
SP VEL ∼ TL 0.273 −0.044 0.025 39.623 −72.322 0.132 0.077
SP VEL ∼ TTL 0.147 −0.003 0.019 39.526 −72.128 0.326 0.070
SP VEL ∼ BD 0.207 −0.039 0.012 39.421 −71.920 0.534 0.063
SP VEL ∼ BL + TL 0.452 0.259 −0.302 0.093 40.707 −71.814 0.640 0.060
SP VEL ∼ BL 0.196 −0.022 0.007 39.343 −71.763 0.691 0.058
SP VEL ∼ MD 0.152 −0.003 0.000 39.245 −71.566 0.888 0.053
SP VEL ∼ BL+ TD 0.063 0.131 −0.120 0.066 40.270 −70.940 1.514 0.038
SP VEL ∼ TD + MD 0.229 −0.022 −0.042 0.039 39.835 −70.070 2.384 0.025
SP VEL ∼ BD +TD 0.236 −0.027 −0.030 0.035 39.773 −69.946 2.508 0.023
SP VEL ∼ TTL + BL + TD −0.193 0.284 −0.167 −0.008 0.120 41.162 −69.825 2.629 0.022
SP VEL ∼ TTL + TD 0.192 −0.027 −0.001 0.030 39.706 −69.812 2.642 0.022
SP VEL ∼ TD + TL 0.187 −0.039 0.009 0.029 39.690 −69.780 2.674 0.022
SP VEL ∼ BD + TL 0.290 −0.023 −0.038 0.029 39.681 −69.762 2.692 0.021
SP VEL ∼ MD + TL 0.293 −0.012 −0.048 0.028 39.673 −69.747 2.707 0.021
SP VEL ∼ TTL + TL 0.257 −0.039 0.000 0.025 39.626 −69.651 2.802 0.020
SP VEL ∼ BD + MD 0.246 −0.079 0.031 0.022 39.574 −69.548 2.906 0.019
SP VEL ∼ TTL + BL 0.100 0.021 −0.004 0.021 39.560 −69.520 2.934 0.019
SP VEL ∼ TTL + MD 0.142 0.007 −0.003 0.020 39.541 −69.482 2.972 0.019
SP VEL ∼ TTL + BD 0.155 −0.006 −0.002 0.019 39.527 −69.455 2.999 0.018
SP VEL ∼ BD + BL 0.227 −0.033 −0.014 0.014 39.457 −69.314 3.140 0.017
SP VEL ∼ BL + TD + TL 0.332 0.270 −0.058 −0.235 0.103 40.866 −69.233 3.221 0.016
SP VEL ∼ BD + BL+ TL 0.481 −0.032 0.266 −0.301 0.100 40.826 −69.152 3.302 0.016
SP VEL ∼ BD +TD + MD 0.065 0.181 −0.045 −0.171 0.099 40.813 −69.125 3.328 0.016
SP VEL ∼ BL+ MD 0.206 −0.025 −0.008 0.008 39.363 −69.125 3.329 0.016
SP VEL ∼ TTL + BL + TL 0.398 0.266 −0.289 −0.002 0.096 40.751 −69.002 3.452 0.015
SP VEL ∼ BL + MD + TL 0.467 0.257 −0.010 −0.304 0.095 40.744 −68.988 3.466 0.015
SP VEL ∼ BD + BL+ TD 0.098 −0.059 0.169 −0.138 0.089 40.635 −68.770 3.684 0.013
SP VEL ∼ TTL + BL + MD −0.435 0.236 0.112 −0.020 0.060 40.168 −67.835 4.618 0.008
SP VEL ∼ TTL + TD + MD 0.342 −0.065 −0.094 0.005 0.050 40.004 −67.508 4.946 0.007
SP VEL ∼ TTL + MD + TL 0.852 −0.091 −0.226 0.013 0.044 39.914 −67.329 5.125 0.006
SP VEL ∼ TD + MD + TL 0.129 −0.031 −0.086 0.062 0.043 39.901 −67.302 5.152 0.006
SP VEL ∼ BD +TD + MD 0.194 0.063 −0.060 −0.065 0.042 39.884 −67.267 5.186 0.006
SP VEL ∼ TTL + BD + TD 0.288 −0.051 −0.040 0.002 0.037 39.804 −67.109 5.345 0.006
SP VEL ∼ BD + TD + TL 0.180 −0.033 −0.053 0.036 0.036 39.797 −67.095 5.359 0.006
SP VEL ∼ TTL + BD + TL 0.524 −0.080 −0.090 0.006 0.036 39.785 −67.070 5.384 0.006
SP VEL ∼ TTL + TD + TL 0.019 −0.070 0.085 −0.003 0.034 39.764 −67.028 5.426 0.005
SP VEL ∼ TTL + BD + BL + TD −0.388 0.066 0.335 −0.176 −0.013 0.128 41.298 −66.944 5.510 0.005
SP VEL ∼ TTL + BL + TD + MD −0.389 0.347 0.048 −0.150 −0.015 0.126 41.264 −66.875 5.579 0.005
SP VEL ∼ BD + MD + TL 0.291 −0.020 −0.002 −0.040 0.029 39.681 −66.862 5.592 0.005
SP VEL ∼ TTL + BL + TD + TL −0.022 0.313 −0.130 −0.103 −0.007 0.125 41.241 −66.829 5.625 0.005
SP VEL ∼ BD + BL+ MD 0.237 −0.119 0.026 0.053 0.025 39.619 −66.738 5.716 0.005
SP VEL ∼ TTL + BD + MD 0.210 −0.053 0.024 −0.001 0.023 39.595 −66.689 5.765 0.005
SP VEL ∼ TTL + BD + BL 0.043 0.021 0.033 −0.005 0.022 39.573 −66.646 5.808 0.004
SP VEL ∼ BL + TD + MD + TL 0.271 0.275 −0.033 −0.110 −0.181 0.119 41.136 −66.620 5.834 0.004
SP VEL ∼ BD + BL + TD + TL 0.330 −0.047 0.286 −0.079 −0.210 0.117 41.104 −66.555 5.899 0.004
SP VEL ∼ BD + BL + MD + TL 0.482 −0.093 0.287 0.037 −0.294 0.105 40.913 −66.173 6.281 0.004
SP VEL ∼ BD + BL + TD + MD 0.027 0.069 0.182 −0.086 −0.196 0.103 40.875 −66.097 6.356 0.003
SP VEL ∼ TTL + BD + BL + TL 0.611 −0.065 0.260 −0.325 0.003 0.102 40.862 −66.072 6.382 0.003
SP VEL ∼ TTL + BL + MD + TL 0.355 0.272 0.007 −0.280 −0.003 0.096 40.752 −65.852 6.601 0.003
SP VEL ∼ TTL + BD + BL + MD −0.386 −0.105 0.272 0.162 −0.019 0.073 40.379 −65.106 7.348 0.002
SP VEL ∼ TTL + BD + TD + MD 0.308 0.072 −0.109 −0.122 0.006 0.053 40.067 −64.481 7.973 0.002
SP VEL ∼ TTL + TD + MD + TL 0.613 −0.090 −0.068 −0.104 0.010 0.052 40.048 −64.443 8.010 0.001
SP VEL ∼ BD + TD + MD + TL 0.034 0.097 −0.091 −0.139 0.089 0.050 40.004 −64.355 8.098 0.001
SP VEL ∼ TTL + BD + MD + TL 0.879 −0.037 −0.076 −0.219 0.014 0.046 39.942 −64.232 8.222 0.001
SP VEL ∼ TTL + BD + TD + TL 0.317 −0.054 −0.036 −0.011 0.002 0.037 39.805 −63.957 8.496 0.001
SP VEL ∼ TTL + BD + BL + TD + MD −0.408 0.054 0.344 0.014 −0.170 −0.014 0.128 41.302 −63.512 8.941 0.001
SP VEL ∼ TTL + BD + BL + TD + TL −0.384 0.066 0.335 −0.176 −0.002 −0.013 0.128 41.298 −63.505 8.948 0.001
SP VEL ∼ TTL + BL + TD + MD + TL −0.260 0.344 0.035 −0.137 −0.047 −0.012 0.127 41.273 −63.456 8.998 0.001
SP VEL ∼ BD + BL +TD + MD + TL 0.266 0.005 0.274 −0.036 −0.112 −0.179 0.119 41.136 −63.182 9.272 0.001
SP VEL ∼ TTL + BD + BL + MD + TL 0.366 −0.093 0.302 0.055 −0.269 −0.003 0.106 40.922 −62.752 9.701 0.001
SP VEL ∼ TTL + BD + TD + MD + TL 0.452 0.055 −0.111 −0.102 −0.052 0.008 0.054 40.075 −61.058 11.396 0.000
SP VEL ∼ TTL + BD + BL +TD + MD + TL −0.418 0.055 0.344 0.014 −0.171 0.004 −0.014 0.128 41.302 −59.746 12.708 0.000
SNP VEL ∼ BD 0.105 0.023 28.946 −50.969 0.000 0.082
SNP VEL ∼ BL −0.076 0.105 0.020 28.901 −50.878 0.091 0.078
SNP VEL ∼ TTL 0.161 0.003 0.009 28.743 −50.563 0.406 0.067
SNP VEL ∼ MD 0.142 0.037 0.006 28.700 −50.477 0.492 0.064
SNP VEL ∼ TD 0.126 0.025 0.001 28.624 −50.325 0.644 0.059
SNP VEL ∼ TTL + TL 1.718 −0.551 0.027 0.086 29.950 −50.299 0.670 0.059
SNP VEL ∼ TL 0.178 −0.005 0.000 28.604 −50.286 0.684 0.058
SNP VEL ∼ MD + TL 1.194 0.297 −0.419 0.055 29.455 −49.310 1.660 0.036
SNP VEL ∼ BL + TL 0.115 0.267 −0.195 0.052 29.400 −49.199 1.770 0.034
SNP VEL ∼ BD + TL 0.214 0.169 −0.105 0.037 29.173 −48.746 2.224 0.027
SNP VEL ∼ BL+ TD −0.147 0.235 −0.143 0.036 29.152 −48.703 2.266 0.026
SNP VEL ∼ BD +TD 0.048 0.168 −0.086 0.031 29.080 −48.561 2.409 0.025
SNP VEL ∼ TTL + BL −0.317 0.213 −0.005 0.024 28.974 −48.348 2.621 0.022
SNP VEL ∼ BL+ MD −0.224 0.185 −0.058 0.024 28.973 −48.346 2.623 0.022
SNP VEL ∼ BD + MD −0.014 0.127 −0.021 0.024 28.963 −48.325 2.644 0.022
SNP VEL ∼ TTL + BD −0.013 0.119 −0.001 0.023 28.951 −48.303 2.667 0.022
SNP VEL ∼ BD + BL −0.018 0.086 0.023 0.023 28.949 −48.298 2.671 0.022
SNP VEL ∼ TTL + TD 0.394 −0.152 0.010 0.020 28.912 −48.224 2.745 0.021
SNP VEL ∼ TD + MD 0.295 0.116 −0.126 0.013 28.801 −48.003 2.966 0.019
SNP VEL ∼ TTL + MD 0.203 −0.082 0.009 0.011 28.777 −47.954 3.015 0.018
SNP VEL ∼ TD + TL 0.382 0.175 −0.171 0.011 28.774 −47.948 3.021 0.018
SNP VEL ∼ TTL + TD + TL 1.754 0.074 −0.603 0.026 0.088 29.981 −47.462 3.507 0.014
SNP VEL ∼ TTL + MD + TL 1.746 0.064 −0.573 0.024 0.087 29.970 −47.440 3.529 0.014
SNP VEL ∼ TTL + BD + TL 1.616 0.031 −0.531 0.025 0.087 29.964 −47.427 3.542 0.014
SNP VEL ∼ TTL + BL + TL 1.832 −0.030 −0.568 0.029 0.086 29.953 −47.406 3.563 0.014
SNP VEL ∼ BL + MD + TL 0.829 0.169 0.202 −0.406 0.070 29.695 −46.889 4.080 0.011
SNP VEL ∼ BD + MD + TL 1.002 0.096 0.235 −0.389 0.065 29.609 −46.717 4.252 0.010
SNP VEL ∼ TD + MD + TL 1.207 0.284 0.047 −0.446 0.056 29.466 −46.433 4.536 0.008
SNP VEL ∼ BL + TD + TL 0.157 0.258 0.034 −0.221 0.052 29.405 −46.311 4.658 0.008
SNP VEL ∼ BD + BL+ TL 0.118 0.008 0.259 −0.193 0.052 29.400 −46.300 4.669 0.008
SNP VEL ∼ TTL + BD + TD 0.238 0.139 −0.183 0.006 0.039 29.195 −45.889 5.080 0.006
SNP VEL ∼ BD + BL+ TD −0.097 0.071 0.164 −0.138 0.038 29.184 −45.868 5.101 0.006
SNP VEL ∼ BD + TD + TL 0.261 0.159 0.042 −0.139 0.038 29.181 −45.862 5.108 0.006
SNP VEL ∼ BD +TD + MD −0.075 0.217 0.035 −0.175 0.037 29.165 −45.830 5.139 0.006
SNP VEL ∼ BD +TD + MD 0.173 0.153 0.081 −0.181 0.037 29.165 −45.830 5.139 0.006
SNP VEL ∼ TTL + BL + TD −0.087 0.217 −0.156 0.001 0.036 29.155 −45.810 5.159 0.006
SNP VEL ∼ BD + BL+ MD −0.158 0.066 0.111 −0.050 0.026 29.000 −45.500 5.469 0.005
SNP VEL ∼ TTL + BD + BL −0.234 0.053 0.142 −0.004 0.025 28.989 −45.479 5.490 0.005
SNP VEL ∼ TTL + BD + MD 0.027 0.117 −0.074 0.004 0.025 28.979 −45.458 5.511 0.005
SNP VEL ∼ TTL + BL + MD −0.285 0.205 −0.030 −0.003 0.025 28.978 −45.457 5.513 0.005
SNP VEL ∼ TTL + TD + MD 0.394 −0.015 −0.147 0.010 0.020 28.913 −45.326 5.643 0.005
SNP VEL ∼ TTL + BD + BL + TL 2.070 0.107 −0.182 −0.586 0.032 0.090 30.020 −44.387 6.582 0.003
SNP VEL ∼ TTL + BL + TD + TL 2.039 −0.072 0.096 −0.660 0.030 0.089 29.999 −44.347 6.623 0.003
SNP VEL ∼ TTL + TD + MD + TL 1.768 0.046 0.062 −0.610 0.024 0.088 29.991 −44.329 6.640 0.003
SNP VEL ∼ TTL + BD + TD + TL 1.700 0.015 0.064 −0.587 0.025 0.088 29.984 −44.315 6.654 0.003
SNP VEL ∼ TTL + BD + MD + TL 1.650 0.029 0.061 −0.553 0.022 0.088 29.982 −44.312 6.657 0.003
SNP VEL ∼ TTL + BL + MD + TL 1.825 −0.021 0.062 −0.583 0.025 0.087 29.972 −44.291 6.678 0.003
SNP VEL ∼ BL + TD + MD + TL 0.822 0.171 0.203 −0.009 −0.401 0.070 29.695 −43.738 7.232 0.002
SNP VEL ∼ BD + BL + MD + TL 0.830 0.004 0.165 0.201 −0.406 0.070 29.695 −43.737 7.232 0.002
SNP VEL ∼ BD + TD + MD + TL 0.993 0.099 0.236 −0.014 −0.380 0.065 29.610 −43.567 7.402 0.002
SNP VEL ∼ BD + BL + TD + TL 0.157 0.000 0.258 0.034 −0.221 0.052 29.405 −43.159 7.810 0.002
SNP VEL ∼ BD + BL + TD + MD 0.019 0.086 0.122 0.051 −0.184 0.040 29.211 −42.769 8.200 0.001
SNP VEL ∼ TTL + BD + BL + TD 0.098 0.100 0.083 −0.176 0.004 0.039 29.208 −42.763 8.206 0.001
SNP VEL ∼ TTL + BD + TD + MD 0.237 0.140 0.013 −0.188 0.006 0.039 29.195 −42.739 8.230 0.001
SNP VEL ∼ TTL + BL + TD + MD −0.121 0.232 0.056 −0.174 −0.002 0.037 29.168 −42.684 8.286 0.001
SNP VEL ∼ TTL + BD + BL + MD −0.162 0.065 0.113 −0.049 0.000 0.026 29.000 −42.348 8.621 0.001
SNP VEL ∼ TTL + BD + BL + TD + TL 2.204 0.093 −0.196 0.077 −0.657 0.033 0.092 30.048 −−41.005 9.964 0.001
SNP VEL ∼ TTL + BD + BL + MD + TL 2.048 0.099 −0.166 0.034 −0.594 0.030 0.090 30.025 −40.960 10.010 0.001
SNP VEL ∼ TTL + BL + TD + MD + TL 2.012 −0.062 0.031 0.085 −0.657 0.028 0.089 30.004 −40.916 10.053 0.001
SNP VEL ∼ TTL + BD + TD + MD + TL 1.709 0.017 0.047 0.051 −0.593 0.023 0.089 29.994 −40.897 10.072 0.001
SNP VEL ∼ BD + BL +TD + MD + TL 0.823 0.006 0.165 0.203 −0.011 −0.399 0.070 29.695 −40.299 10.670 0.000
SNP VEL ∼ TTL + BD + BL + TD + MD 0.066 0.094 0.101 0.035 −0.186 0.002 0.040 29.212 −39.334 11.635 0.000
SNP VEL ∼ TTL + BD + BL +TD + MD + TL 2.192 0.092 −0.191 0.010 0.073 −0.657 0.032 0.092 30.049 −37.240 13.729 0.000

References

  1. Abdala V, Ponsa ML, 2012. Life in the slow lane: the effect of reduced mobility on tadpole limb development. Anat Rec 295: 5.–. [DOI] [PubMed] [Google Scholar]
  2. Agrawal AA, 2001. Phenotypic plasticity in the interactions and evolution of the species. Science 294: 321.–. [DOI] [PubMed] [Google Scholar]
  3. Alvarez D, Nicieza AG, 2006. Factors determining tadpole vulnerability to predators: can prior experience compensate for a suboptimal shape? Evol Ecol 20: 523.–. [Google Scholar]
  4. Andersson J, Johansson F, Söderlund T, 2006. Interactions between predator- and diet- induced phenotypic changes in body shape of crucian carp. Proc R Soc Lond B Biol Sci 273: 431.–. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Angilleta MJ, 2006. Estimating and comparing thermal performance curves. J Thermal Biol 31: 541.–. [Google Scholar]
  6. Arendt JD, 2003. Reduced burst speed is a cost of rapid growth in anuran tadpoles: problems of autocorrelation and inferences about growth rates. Funct Ecol 17: 328.–. [Google Scholar]
  7. Arendt JD, 2009. Influence of sprint speed and body size on predator avoidance in new mexican spadefoot toads Spea multiplicata. Oecologia 159: 455.–. [DOI] [PubMed] [Google Scholar]
  8. Arendt JD, 2010. Morphological correlates of sprint swimming speed in five species of spadefoot toad tadpoles: comparison of morphometric methods. J Morphol 271: 1044.–. [DOI] [PubMed] [Google Scholar]
  9. Arnold JS, 1983. Morphology, performance and fitness. Am Zool 23: 347.–. [Google Scholar]
  10. Barton K, 2014. MuMIn: multi-Model Inference. R package version 1.12.1. Available from: http://CRAN.R-project.org/package=MuMIn.
  11. Berner D, 2011. Size correction in biology: how reliable are approaches based on (common) principal component analysis. Oecologia 166: 961.–. [DOI] [PubMed] [Google Scholar]
  12. Billerbeck JM, Lankford TE Jr, Conover DO, 2001. Evolution of intrinsic growth and energy acquisition rates. I. Trade-offs with swimming performance in Menidia menidia. Evolution 55: 1863.–. [DOI] [PubMed] [Google Scholar]
  13. Bookstein FL, 1982. Foundations of morphometrics. Annu Rev Ecol Syst 13: 451.–. [Google Scholar]
  14. Bourdeau PE, Johansson F, 2012. Predator-induced morphological defences as by-products of prey behaviour: a review and prospectus. Oikos 121: 1175.–. [Google Scholar]
  15. Burnham KP, Anderson DR, 2004. Multimodel inference: understanding AIC and BIC in model selection. Sociol Methods Res 33: 261.–. [Google Scholar]
  16. Burnham KP, Anderson DR, Huyvaert KP, 2011. AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons. Behav Ecol Sociobiol 65: 23.–. [Google Scholar]
  17. Caldwell JP, 1982. Disruptive selection: a tail color polymorphism in Acris tadpoles in response to differential predation. Can J Zool 60: 2818.–. [Google Scholar]
  18. Calsbeek R, Kuchta S, 2011. Predator mediated selection and the impact of developmental stage on viability in wood frog tadpoles Rana sylvatica. BMC Evol Biol 353: 1.–. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Dayton GH, Saenz D, Baum KA, Langerhans RB, DeWitt TJ, 2005. Body shape, burst speed and escape behavior of larval anurans. Oikos 111: 582.–. [Google Scholar]
  20. El Balaa R, Blouin-Demers G, 2013. Does exposure to cues of fish predators fed different diets affect morphology and performance of Northern Leopard frog Lithobates pipiens larvae? Can J Zool 91: 203.–. [Google Scholar]
  21. Ferrari MCO, Wisenden BD, Chivers DP, 2010. Chemical ecology of predator-prey interactions in aquatic ecosystems: a review and prospectus. Can J Zool 88: 698.–. [Google Scholar]
  22. Frommen JG, Herder F, Engqvist L, Mehlis M, Bakker TCM et al. , 2011. Costly plastic morphological responses to predator specific odour cues in three-spined sticklebacks Gasterosteus aculeatus. Evol Ecol 25: 641.–. [Google Scholar]
  23. Gosner KL, 1960. A simplified table for staging anuran embryos and larvae with notes on identification. Herpetologica 16: 183.–. [Google Scholar]
  24. Jara FG, 2010. Plasticidad fenotípica en anuros patagónicos de los géneros Pleurodema y Rhinella: Respuestas al hidroperíodo y a los depredadores [Dissertation]: Universidad Nacional del Comahue. [Google Scholar]
  25. Jara FG, Perotti MG, 2010. Risk of predation and behavioural response in three anuran species: influence of tadpole size and predator type. Hydrobiologia 644: 313.–. [Google Scholar]
  26. Johnson JB, Burt BD, DeWitt TJ, 2008. Form, function, and fitness: pathways to survival. Evolution 62: 1243.–. [DOI] [PubMed] [Google Scholar]
  27. Kingsolver JG, Schemske DW, 1991. Path analysis of selection. TREE 6: 276.–. [DOI] [PubMed] [Google Scholar]
  28. Kishida O, Nishimura K, 2004. Bulgy tadpoles: inducible defense morph. Oecologia 140: 414.–. [DOI] [PubMed] [Google Scholar]
  29. LaFiandra EM, Babbitt KJ, 2004. Predator induced phenotypic plasticity in the pinewoods tree frog Hyla femoralis: necessary cues and the cost of development. Oecologia 138: 350.–. [DOI] [PubMed] [Google Scholar]
  30. Laurila A, Jarvi-Laturi M, Pakkasmaa S, Merilä J, 2004. Temporal variation in predation risk: stage-dependency, graded responses and fitness costs in tadpole antipredator defences. Oikos 107: 90.–. [Google Scholar]
  31. McCollum SA, Van Buskirk J, 1996. Costs and benefits of a predator-induced polyphenism in the gray treefrog Hyla chrysoscelis. Evolution 50: 583.–. [DOI] [PubMed] [Google Scholar]
  32. Mirza RS, Ferrari MCO, Kiesecker JM, Chivers DP, 2006. Responses of American toad tadpoles to predation cues: Behavioural response thresholds, threat-sensitivity and acquired predation recognition. Behaviour 143: 887.–. [Google Scholar]
  33. Morin PJ, 1986. Interactions between intraspecific competition and predation in an amphibian predator-prey system. Ecology 67: 713.–. [Google Scholar]
  34. Pettersson LB, Brönmark C, 1997. Density-dependent costs of an inducible morphological defense in crucian carp. Ecology 78: 1805.–. [Google Scholar]
  35. Pettersson LB, Brönmark C, 1999. Energetic consequences of an inducible morphological defense in crucian carp. Oecologia 121: 12.–. [DOI] [PubMed] [Google Scholar]
  36. Polo-Cavia N, Gómez-Mestre I, 2014. Learned recognition of introduced predators determines survival of tadpole prey. Funct Ecol 28: 432.–. [Google Scholar]
  37. Pueta M, Cruz FB, Perotti MG, 2016. Feeding regime and food availability determine behavioural decisions under predation risk in Pleurodema thaul (Anura: Leptodactylidae) tadpoles. Herpetol J 26: 61.–. [Google Scholar]
  38. Relyea RA, 2001. Morphological and behavioral plasticity of larval anurans in response to different predators. Ecology 82: 523.–. [Google Scholar]
  39. Scheiner SM, Mitchell RJ, Callahan HS. 2000. Using path analysis to measure natural selection. J Evol Biol 13: 423.–. [Google Scholar]
  40. Schoeppner NM, Relyea RA, 2009. Interpreting the smells of predation: how alarm cues and kairomones induce different prey defences. Funct Ecol 23: 1114.–. [Google Scholar]
  41. Skelly DK, 1996. Pond drying, predators, and the distributions of Pseudacris tadpoles. Copeia 1996: 599.–. [Google Scholar]
  42. Skelly DK, 1997. Tadpole communities. Am Sci 85: 36.–. [Google Scholar]
  43. Skelly DK, Werner EE, 1990. Behavioral and life-historical responses of larval american toads to an odonate predator. Ecology 71: 2313.–. [Google Scholar]
  44. Smith DC, Van Buskirk J, 1995. Phenotypic design, plasticity and ecological performance in two tadpole species. Am Nat 145: 211.–. [Google Scholar]
  45. Steiner UK, 2007. Investment in defense and cost of predator induced defense along a resource gradient. Oecologia 152: 201.–. [DOI] [PubMed] [Google Scholar]
  46. Steiner UK, Van Buskirk J, 2008. Environmental stress and the costs of whole-organism phenotypic plasticity in tadpoles. J Evol Biol 21: 97.–. [DOI] [PubMed] [Google Scholar]
  47. Storfer A, Cross J, Rush V, Caruso J, 1999. Adaptive coloration and gene flow as a constraint to local adaptation in the streamside salamander Ambystoma barbouri. Evolution 53: 889.–. [DOI] [PubMed] [Google Scholar]
  48. Teplitsky C, Plenet S, Lena JP, Mermet N, Malet E et al. , 2005. Escape behaviour and ultimate causes of specific induced defenses in ananuran tadpole. J Evol Biol 18: 180.–. [DOI] [PubMed] [Google Scholar]
  49. Tollrain R, Harvell C, 1999. The Ecology and Evolution of Inducible Defenses. Princeton: Princeton University Press. [Google Scholar]
  50. Touchon JC, Warkentin KM, 2008. Fish and dragonfly nymph predators induce opposite shifts in color and morphology of tadpoles. Oikos 117: 634.–. [Google Scholar]
  51. Touchon JC, Wojdak JM, 2014. Plastic hatching timing by red-eyed treefrog embryos interacts with larval predator identity and sublethal predation to affect prey morphology but not performance. PLoS ONE 9: e100623. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Van Buskirk J, McCollum SA, Werner EE, 1997. Natural selection for environmentally-induced phenotypes in tadpoles. Evolution 51: 1983.–. [DOI] [PubMed] [Google Scholar]
  53. Van Buskirk J, McCollum SA, 1999. Plasticity and selection explain variation in tadpole phenotype between ponds with different predator composition. Oikos 85: 31.–. [Google Scholar]
  54. Van Buskirk J, McCollum SA, 2000. Functional mechanisms of an inducible defence in tadpoles: morphology and behaviour infuence mortality risk from predation. J Evol Biol 13: 336.–. [Google Scholar]
  55. Van Buskirk J, Anderwald P, Lupold S, Reinhardt L, Schuler H, 2003. The lure effect, tadpole tail shape, and the target of dragonfly strikes. J Herpetol 37: 420.–. [Google Scholar]
  56. Werner EE, 1992. Individual behavior and higher-order species interactions. Am Nat 140: S5.–. [Google Scholar]

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