ORIGINAL ARTICLE

doi:10.1111/evo.12294

NONCONSUMPTIVE PREDATOR-DRIVEN MORTALITY CAUSES NATURAL SELECTION ON PREY

Adam M. Siepielski,1,2 Jason Wang,1 and Garrett Prince1 1Department of Biology, University of San Diego, 5998 Alcala Park, San Diego, California 92110 2E-mail: [email protected]

Received July 23, 2013 Accepted October 10, 2013

Predators frequently exert natural selection through differential consumption of their prey. However, predators may also cause prey mortality through nonconsumptive effects, which could cause selection if different prey phenotypes are differentially susceptible to this nonconsumptive mortality. Here we present an experimental test of this hypothesis, which reveals that nonconsumptive mortality imposed by predatory dragonflies causes selection on their damselfly prey favoring increased activity levels. These results are consistent with other studies of predator-driven selection, however, they reveal that consumption alone is not the only mechanism by which predators can exert selection on prey. Uncovering this mechanism also suggests that prey defensive traits may represent adaptations to not only avoid being consumed, but also for dealing with other sources of mortality caused by predators. Demonstrating selection through both consumptive and nonconsumptive predator mortality provides us with insight into the diverse effects of predators as an evolutionary force.

KEY WORDS: Adaptation, consumptive mortality, natural selection, nonconsumptive mortality, predation, prey defenses.

Predators often exert intense natural selection on prey phenotypes physiological stress responses (Preisser 2009; Sheriff et al. 2009) ranging from morphological (Endler 1986; Benkman et al. 2001; among others (see Preisser et al. 2005; Orrock et al. 2008; Losos et al. 2004) to physiological (McPeek 1997) and behavioral McCauley et al. 2011). The microevolutionary consequences of traits (McPeek 1997; Reale and Festa-Bianchet 2003; Strobbe these effects remain largely unexplored despite the fact that they et al. 2009, 2010) among others (Vermeij 1987; Lima and Dill may have important fitness consequences, which may be directly 1990; Ruxton et al. 2004). Such selection has driven the evolution linked to phenotypic variation. Indeed, elevated stress responses of of an array of defensive adaptations (e.g., Vermeij 1987; Ruxton prey to the nonconsumptive effects of predators, or through other et al. 2004) and in some cases has contributed to population as of yet unquantified pathways, frequently cause mortality (Stoks divergence and ecological speciation (Vamosi 2005; Langerhans 2001; McCauley et al. 2011). That is, the mere presence of preda- et al. 2007; Nosil 2012). It is, however, unclear if such selection tors can cause or contribute to prey mortality. If such mortality is and subsequent adaptive evolution is necessarily because of the linked to variation in individual prey phenotypes, this may result effects of differential consumption of prey by predators. in natural selection imposed through nonconsumptive mortality. This uncertainty arises because the effects of predators on Here, we report an experimental study designed to test the prey frequently extend beyond direct consumption. Predators hypothesis that nonconsumptive mortality by predators causes can impact prey populations through consumptive and noncon- phenotypic selection on prey. We use a well-characterized prey sumptive effects (Preisser et al. 2005; Peckarsky et al. 2008). For () and predator (dragonfly) system (McPeek 1997) to instance, predators can depress growth and development rates impose the potential for nonconsumptive mortality and natural (Benard 2004; McCauley et al. 2011), reduce fecundity (Preisser selection by exposing prey to predators in situations where the et al. 2005; Creel et al. 2009; Zanette et al. 2011) and elevate predators cannot consume the prey, but the prey still perceive

C 2013 The Author(s). Evolution C 2013 The Society for the Study of Evolution. 696 Evolution 68-3: 696–704 NONCONSUMPTIVE PREDATOR-DRIVEN SELECTION

the presence of the predator. We also quantified possible selec- surviving from each bucket were housed in a room tion imposed by direct consumption by predators to allow us to at 20◦C individually in 50 mL cups filled with filtered pond and understand if consumptive and nonconsumptive mortality from dechlorinated tap water. Individual assays began 24 h after re- predators differs in the patterns of selection they generate. moval from the experiment and were completed one at a time by two observers and lasted 15 min in duration each. Assays be- gan when an individual damselfly was gently placed into a 250 Materials and Methods mL glass dish with a small piece of fiberglass screen covering the bottom of the dish to give damselflies footing. No dragonfly Experimental setup for quantifying mortality predators were present during these assays. After a 1-min acclima- rates and phenotypic selection tion period, approximately 50–70 Artemia were added as a food Experimental setup source. The following behavioral traits were recorded: number of The experiment was conducted in a walk-in environmental cham- walks, number of body moves/bends, number of prey attacks, and ber. We used 18.92 L (5 gallon) buckets filled with filtered pond swimming propensity (see McPeek 2004; Strobbe et al. 2009 for and dechlorinated tap water, a small amount of gravel, a bubbler details). Swimming propensity is quantified as individuals either to provide constant aeration, and rehydrated dried moss—which swimming away or not swimming away when gently prodded served the purposes of an aquatic macrophyte because damselflies with a metal probe. After each assay was completed, damselflies are sit-and-wait predators that are typically found on macrophytes. were immediately stored in 70% ethanol before photographing Each bucket was stocked with 35 cervula damselfly lar- for morphometric analysis. vae. Damselfly larvae were collected March 21, 2012 from a small pond near the intersection of CA79 and I8 in San Diego County, Morphometric analysis California (32◦4951N, 116◦3721W). In this pond, Anax drag- We took photographs of surviving damselfly larvae using a digital onflies are likely the primary predator of damselflies because fish camera mounted with a macro lens (Nikon D5100). We then are absent (e.g., McPeek 1998). The experimental predator treat- measured individuals from their photographs using the computer ments consisted of replicates of four buckets with a cage only, program Image-J (version 1.45s; National Institutes of Health, seven buckets with a cage and one free-ranging late-instar Anax Bethesda MD). Six morphological measurements were recorded: larvae predator, and seven buckets with one Anax placed in a cage. head width, head length, maximum length of thorax, width of the More replicates of the predator treatments were used because we first abdominal segment, abdomen length, and femur length. All expected that fewer individuals would survive in these treatments. measurements were made to the nearest 0.1 mm. Treatments were randomly assigned to buckets. Cages consisted of small, clear acrylic boxes (10 × 10 × 8 cm) with fiberglass Data analysis for selection experiment mesh on the top-side to allow prey (Artemia)forAnax to feed on, We used a linear mixed model, with treatments as fixed effects and but the mesh was too small to allow Ischnura into the cages. A bucket nested within treatments as random effects, to determine small wooden dowel and fiberglass screen were placed in the cage if per-capita mortality rates differed among predator treatments. for dragonflies to perch on. This set-up maximized the chances This model design allowed us to use the full dataset and avoid that predator presence cues were available to the damselflies. The pseudoreplication within enclosures (Millar and Anderson 2004; one exception is that if damselflies somehow respond to chemical Strobbe et al. 2009). Tukey’s HSD was used to make comparisons cues given off as dragonflies consume them, such a cue would be among treatments. Per capita mortality rates were calculated sep- missing in the caged predator treatment. The experiment started arately for each experimental replicate (individual buckets were on March 26, 2012 when cages were added to the buckets. Ap- the unit of replication) as: (ln[recovered number of damselfles] – proximately 1.00×105 Artemia brine shrimp were placed in the ln[initial number of damselflies])/(duration of the experiment). experimental buckets for both damselfly and dragonfly larvae ev- This model assumes a constant mortality rate throughout the ex- ery other day as prey. The chamber was maintained at 17◦C with periment. Per capita mortality rates were log transformed to meet a 12 h light:dark cycle for the duration of the experiment, which the assumptions of normality and homogeneity of variance for the was 35 days as previous studies have found this period of time linear mixed model. sufficient to detect selection using the methods employed here To quantify selection on prey phenotypes, we first used prin- (e.g., McPeek 1997; Strobbe et al. 2009, 2010). cipal components analysis (PCA) because traits tended to be cor- related and we wanted to reduce the dimensionality of the differ- Behavioral assays ent datasets. Separate PCAs based on the correlation matrix of the We scored several different behavioral variables related largely traits were completed for behavioral and morphological traits. For to the foraging and predator evasive activities of these . both PCAs, all traits loaded positively and fairly uniformly with

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Table 1. PCA loadings based on the correlation matrix for (A) behavioral and (B) morphological traits (n = 301 damselflies).

(A) Behavioral trait PC1 PC2 PC3 PC4 Number of walks 0.492 − 0.394 0.646 0.420 Number of body moves 0.613 − 0.307 − 0.169 − 0.701 Number of prey attacks 0.544 0.264 − 0.599 0.523 Swimming propensity 0.290 0.824 0.437 − 0.225 Cumulative proportion of variation explained 0.420 0.671 0.877 1.000 (B) Morphological trait PC1 PC2 PC3 PC4 PC5 PC6 Head width 0.491 − 0.361 0.055 − 0.078 0.319 − 0.718 Head length 0.328 0.634 0.450 0.450 0.289 0.018 Thorax length 0.487 − 0.288 − 0.087 − 0.163 0.427 0.679 Abdomen width 0.382 0.284 0.302 0.685 − 0.460 0.010 Abdomen length 0.341 0.415 − 0.829 0.065 − 0.104 − 0.093 Femur length 0.389 − 0.359 0.089 0.538 − 0.639 0.111 Cumulative proportion of variation explained 0.495 0.642 0.761 0.869 0.967 1.000

√ PC1 (Table 1) and so we focus our analyses on these variables treatment differentials: z¯ f − z¯c/ vc,wherez¯ f is the mean of the because they explained the most variation and were readily in- PC1 score of surviving individuals in the free-ranging predator terpretable as synthetic measures of increased activity and larger treatment and z¯c is the mean PC1 score of the caged predator individuals. treatment, and vc is the variance of the PC scores of the caged Because damselflies grow through molting, we could not predator treatment (see, e.g., McPeek 1997; Perez and Munch individually mark them (any mark would be lost) and use tradi- 2010). The later selection differential calculation effectively sub- tional methods of quantifying selection by tracking the fate of tracts out the nonconsumptive mortality effect, leaving only the individuals (McPeek 1997). Instead, we compared the distribu- consumptive effect of selection. We used bootstrapping with 1000 tions of phenotypes among predator treatments. Such a design is replicates to calculate standard errors for the differentials. Essen- appropriate and sufficient for detecting phenotypic selection (see tially, these calculations of selection differentials are comparable McPeek 1997) even though it is not the most commonly used ap- to comparing the distributions of phenotypes before (e.g., the no proach of selection gradient analysis, which dominates the field predator treatment) and after selection (e.g., after exposure to the (e.g., Kingsolver et al. 2001; Siepielski et al. 2009). Evidence putative selective agent). Although directional selection is most consistent with directional selection imposed by nonconsumptive often calculated as the covariance of a trait on fitness (Lande mortality by dragonfly predators would be manifested as a direc- and Arnold 1983), this cannot be done given the biology of this tional shift in the means of phenotypes between the no predator system as outlined earlier. However, note that the difference in and caged predator treatments. Similarly, evidence consistent with mean trait values due to selection is equivalent to the covariance directional selection imposed by consumptive mortality by drag- between the trait and fitness (Price 1971; Falconer and Mackay onflies would be manifested as a significant directional shift in the 1996; Perez and Munch 2010). All analyses were performed in R means of phenotypes between the caged and free-ranging preda- (R development team). tor treatments. To determine if mean PC1 scores of behavioral and morphological phenotypes differed among treatments, we again EXPERIMENTAL TEST FOR PLASTICITY IN used a linear mixed model, with treatments as fixed effects and BEHAVIORAL RESPONSES bucket nested within treatments as random effects. Tukey’s HSD Experimental setup was then used to make comparisons among treatment levels. Differences in damselfly behavioral traits among predator treat- We calculated variance standardized selection differentials ments could be due to changes in behaviors that are not driven for the caged and free-ranging treatments as the difference in through differential consumption (i.e., phenotypic selection), but means of the behavioral and morphological PC1 scores between instead reflect short-term responses to the presence of predators the caged and the no predator treatment, and the caged and the (i.e., plasticity). Indeed, some damselfly species reduce their ac- free-ranging predator treatments, respectively (caged treatment √ tivity levels in response to the presence of predators (McPeek differentials: z¯c − z¯n/ vn,wherez¯c is the mean of the PC1 score 1990, 2004). To examine this possibility, we conducted an exper- of surviving individuals in the caged predator treatment and z¯n is iment to quantify damselfly larvae behaviors in the presence and the mean PC1 score of the no-predator treatment, and vn is the vari- absence of dragonflies. Our experimental protocol follows closely ance of the PC1 scores of the no predator treatment; free-ranging that of McPeek (1990).

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Ideally we would have sampled damselflies from the same containing Artemia that had sunk to the bottom. These were then population as the selection experiment, however, that pond had replaced with fresh Artemia, again maintaining a constant prey completely dried up before conducting this experiment. We there- supply of approximately 50–70 Artemia in each damselfly con- fore gathered Ischnura larvae from a nearby population found tainer for each replicate. The behavioral assay began once a single at Water of the Woods Pond in the Cleveland National Forest damselfly was gently introduced into the damselfly container. Af- (32◦5246N, 116◦2751W) on August 27, 2013. Ischnura per- ter a 1-min acclimation period, we then recorded the same set of parva was also present at this site, however, based on earlier sur- behavioral traits as noted above over a 15-min continuous obser- veys Ischnura cervula is the dominant damselfly present at this vation period. pond. Thus, we suspect that the Ischnura used in this experiment may represent a mix of species, again dominated by I. cervula,be- Data analysis for behavioral experiment cause the larvae were not consistently distinguishable to species We used a two-sample t-test to compare behavioral traits between at this stage in their development. Regardless, this should not the predator and no-predator treatments. Again, we used PCA confound our interpretations, because both species are members to reduce the dimensionality of the behavioral traits and focused of closely related clades (Chippendale et al. 1999). Although the our analysis on the first principal component (PC1; Table S1). larvae were earlier instars than those used in the selection experi- Importantly, the PC1 loadings (larger values of PC1 are indicative ment, qualitative behavioral phenotypic differences do not change of more active individuals) for the selection experiment and the substantially over instars (M. McPeek, pers. comm.). After col- plasticity experiment are similar in magnitude and the amount of lection, damselflies were housed in a room at 20◦C individually variation they account for (cf. Tables 1, S1). in 20 mL scintillation vials filled with filtered pond water and dechlorinated tap water with a small wooden dowl to perch on before being used in the experiment. Dragonflies were housed in- Results dividually in plastic tubs filled with 700 mL of filtered pond water DAMSELFLY MORTALITY RATES and dechlorinated tap water and a small piece of macrophyte. Per capita mortality rates of damselflies were significantly greater To conduct the experiment, we constructed observational when predatory dragonflies were present in the system regardless units composed of 36 × 20 × 12 cm plastic containers that housed if they were caged or free ranging (linear mixed model: F2, 15 = the dragonflies, with a separate small plastic container placed in 37.82, P < 0.0001, Tukey’s post hoc tests both P < 0.0001; the middle along one edge of the larger container to house the Fig. 1A). Per capita mortality rates were, however, about twice as damselflies (hereafter the “damselfly container”). The damselfly great in the free-ranging predator treatment relative to the caged containers were clear acrylic boxes (10 × 10 × 8cm)openon predator treatment (Tukey’s post hoc test P = 0.005; Fig. 1A). the top (but above water level). Four, 3mm holes were drilled on one side and covered with Nitex 100 μm mesh netting allowing PHENOTYPIC SELECTION ON DAMSELFLIES damselflies access to dragonfly olfactory and mechanoreceptor Dragonfly predators caused directional selection favoring in- cues, but preventing any damselflies or their prey from moving creased activity levels of the damselfly prey (Fig. 1B). The means into the larger predator container. Fiberglass netting covered the of the behavior-associated PC1, which reflect increased activity bottom of both the predator and dragonfly containers for footing. levels (i.e., higher prey attack rates, swimming propensity, and The observational units were filled to a depth of 6 cm with filtered movement; Table 1), were all greater when a predator was present pond and dechlorinated tap water. (linear mixed model: F2, 15 = 6.33, P = 0.01; Fig 1B). However, Each container was randomly assigned a treatment, either: only the nonconsumptive mortality resulted in significant phe- (1) two late instar Anax larvae; or (2) no predator. These treatment notypic selection (caged treatment selection differential: 0.78 ± assignments to containers remained the same for the duration of 0.16[SE], Tukey’s post hoc test P = 0.001). The greater levels of the experiment to prevent any possible predator olfactory clue mortality imposed through consumptive mortality did not result contamination. Twenty-eight damselflies were used in the preda- in stronger selection for increased activity levels (free-ranging tor treatment, and 26 in the no-predator treatment (two larvae died predator selection differential: −0.10 ± 0.13[SE], Tukey’s post before conducting the experiment). Two observers conducted the hoc test P = 0.898). That is, after taking into account the shift in behavioral assays. The order in which observers recorded a given phenotype associated with nonconsumptive mortality, consump- treatment replicate was also randomly assigned. tive mortality had little overall effect on directional selection. During the behavioral assays, approximately 50–70 Artemia We detected no evidence of phenotypic selection on PC1 of were added to the damselfly containers as a food source. Because the morphological traits, which largely reflects prey body size removing the water after each experiment would greatly disrupt (Table 1; linear mixed model: F2, 15 = 0.862, P = 0.442; Fig 1D). the dragonflies, we removed a small portion (∼5mL)ofwater The corresponding selection differentials were −0.20 ± 0.16 (SE)

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A Per capita mortality 0.00 0.01 0.02 0.03 0.04 0.05 caged free none

B Treatment PC1 (Overall activity level) 0.5 1.0 1.5

No Predator Predator Treatment

Figure 2. Activity levels of damselfly larvae do not differ in the

PC1 (Overall activity level) presence and absence of dragonfly predators. Shown are the

-1.0 -0.5 0.0 0.5 1.0 mean and 95% CIs for activity-level–associated phenotypes (prin- caged free none cipal components [PC1] scores from behavioral traits; Table S1) for Treatment C predator (n = 28 larvae) and no-predator treatments (n = 26).

for the free-ranging predator treatment and 0.01 ± 0.14 (SE) for the caged treatment. -2 -1 0 1 2 3 PC1 (Overall activity level) DAMSELFLY BEHAVIORAL RESPONSES TO

caged free none PREDATORS D Treatment We found no evidence that damselfly activity levels changed in response to the presence or absence of dragonfly predators. Al- though mean PC1 scores were slightly lower in the predator (mean PC1 =−0.13 ± 0.22 SE) versus the no predator treatment (mean PC1 = 0.14 ± 0.28 SE), the difference was not statistically sig- nificant (t = 0.730, df = 52, P = 0.468; Fig. 2). PC1 (Overall body size) -0.6 -0.4 -0.2 0.0 0.2 0.4

caged free none Treatment Discussion The results of our experimental study show that predatory drag- Figure 1. Evidence for nonconsumptive and consumptive mor- onflies cause both consumptive and nonconsumptive mortality on tality imposed by predators (A) and the resulting phenotypic se- their damselfly prey and that this mortality is nonrandomly associ- lection on behavioral (B), but not body size (C), associated phe- ated with differences in phenotypic traits associated with activity notypes. (A) Per capita mortality rates (mean and 95% confidence levels. These findings thus reveal how nonconsumptive mortality interval [CI], n = 4–7 replicates per treatment, N = 18 experimental replicates; each replicate has one estimated per capita mortality contributes to directional selection. In combination with previous rate) among predator treatments. (B) Mean and 95% CI for behav- studies demonstrating how consumptive mortality causes direc- ioral phenotypes (principal components [PC1] scores from behav- tional selection (McPeek 1997; Stoks et al. 1999; Strobbe et al. ioral traits; larger values of PC1 are associated with more active 2009; 2010), these collective works reveal the multifarious effects individuals; see Table 1) among surviving damselflies in the no of predator-driven mortality to directional selection on damselfly = = = predator (n 109 larvae), caged (n 122), and free ranging (n prey phenotypes. 70) treatments. (C) Individual larvae behavioral PC1 scores (sample Consistent with evidence for nonconsumptive mortality, we sizes as listed earlier); a small amount of jitter was added to each found that per capita mortality rates of damselflies were sig- point. (D) Mean and 95% CI for morphological phenotypes (prin- cipal components [PC1] scores from morphological traits; larger nificantly greater when predatory dragonflies were present in values of PC1 are associated with larger individuals see Table 1; the system regardless if they were caged or free ranging. Al- sample sizes as listed above). though the causes of any direct mortality imposed by predators are

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obvious, the causes of nonconsumptive mortality are unknown. (2004) found that I. verticalis did not change the number of Indeed, the causes of nonconsumptive mortality are difficult to walks, number of prey captured, or the longest period of time ascertain and remain largely speculative for most studies of non- spent inactive. However, that study did find that the total number consumptive mortality. Studies that have investigated noncon- of prey stalks was lower in the presence than absence of drag- sumptive mortality have identified a number of possible causes onfly predators. Second, the recording of behavioral phenotypes including physiological stress (Creel et al. 2009; Preisser 2009; for the selection analyses was all accomplished in the absence of Sheriff et al. 2009; Zanette et al. 2011), susceptibility to pathogens the predator. Although any possible plastic responses to predators (Ramirez and Snyder 2009; McCauley et al. 2011), and reduced could have become fixed, there is no evidence of latency effects nutritional status (Benard 2004). As with many prey, damselflies in the response to the predators as there are no significant correla- will frequently avoid patches with greater food availability when tions between activity levels (PC1 scores) and approximate time a predator is present, which could lead to death through starvation (based on the length of the observations and the number of assays (Heads 1986). However, death through starvation alone is unlikely completed per day) since removal from the experimental buckets

(Lawton et al. 1980). Elevated levels of stress have been detected and the recording of the behavioral assays (caged: rs = 0.025, when damselflies are exposed to predators, which could contribute P = 0.782; free-ranging: rs = 0.117, P = 0.335). This result is to mortality either directly or through a compromised immune re- also consistent with previous studies in Ischnura damselflies that sponse (De Block and Stoks 2008; Slos and Stoks 2008). Finally, have not implicated, but did not explicitly investigate, any kind cannibalism, which has been shown in damselflies (Delclos and of behavioral latency effects (e.g., McPeek 2004). In addition, Rudolf 2011), could cause mortality not attributable to direct con- if plasticity alone were responsible we would expect that in the sumption by dragonfly predators (including the treatments with no-predator treatment individuals should not exhibit as high of no predators). However, why cannibalism would be higher among activity levels as the predator treatments. Comparisons of the in- treatments with predators is unclear. The presence of dead, intact dividual behavioral PC1 scores among treatments show that some larvae found in the buckets at the end of the experiment veri- individuals in the no predator treatment are just as active as those fies that not all mortality could have been through cannibalism. recovered in the predator treatments (Fig. 1C). Thus, we suspect, but cannot confirm, that some combination of The greater levels of mortality imposed through consumptive factors acts in concert to cause nonconsumptive mortality (Stoks mortality did not result in stronger selection for increased activity 2001; McCauley et al. 2011). Clearly, future studies are needed levels. In fact, nonconsumptive mortality appears to be the main to understand the exact mechanisms generating nonconsumptive driver of overall selection imposed by the predator as consumptive mortality and this remains a formidable task (e.g., McCauley mortality did not result in any detectable selection. One possibil- et al. 2011). ity is that the effect of selection imposed through consumptive Results from this experiment demonstrate that nonconsump- mortality is in the opposite direction and was overwhelmed by tive, but not consumptive, mortality resulted in directional selec- selection through nonconsumptive mortality. The observed sign tion favoring increased activity levels of damselflies. Shifts in of the selection coefficient for consumptive mortality was much the distributions of the behavior-associated PC1, which reflect weaker and in the opposite direction (favoring less active individu- increased activity levels (i.e., higher prey attack rates, swimming als) of selection through nonconsumptive mortality, however, this propensity and movement), were greater when a caged preda- effect was not statistically significant. Nevertheless, this implies tor was present. Although behavioral plasticity could account for that the strength of the interaction (per capita mortality rates) may some of this shift in phenotypes, such changes are unlikely due not always directly translate into comparable differences in the entirely to plasticity for several reasons. First, our experimental strength of selection (e.g., Benkman 2013). These results there- test of this possibility showed no differences in damselfly activ- fore show that the effects of even a single “agent” of selection ity levels in the presence or absence of dragonfly predators. This are multifarious. Dragonfly consumption clearly has an impor- indicates that plasticity in behaviors is unlikely. We do note that tant ecological effect, but its effect on selection is much weaker. the damselflies used in the behavioral experiment were from a Simply manipulating a causal agent of selection may therefore not different population and were earlier instars than those used in detect differences in the way such causal agents drive selection the selection experiment. It is possible that plastic responses dif- through variation in fitness components. In effect, this experi- fer among populations and ages (e.g., Schlichting 1986; Porlier ment removed an important source of selection on traits (direct et al. 2012). The results of our plasticity experiment are, however, consumption) and such relaxed selection allowed us to more fully largely consistent with previous studies in a related species of understand the dynamics of predator-related mortality (e.g., Lahti damselfly, Ischnura verticalis, which also revealed that by and et al. 2009). large they do not exhibit plastic responses in activity levels to The selection imposed by dragonfly nonconsumptive mor- the presence of predatory dragonflies (McPeek 2004). McPeek tality was comparable to that observed in field-based experiments

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(McPeek 1997; Stoks et al. 1999; Strobbe et al. 2009, 2010). bined with density-mediated competitive effects could influence Namely, selection imposed by predatory dragonflies favors indi- phenotypic selection (e.g., Calsbeek and Cox 2010). viduals that are more active, with a greater propensity to evade In contrast to the evidence for selection on prey behavior, we predators. Although dragonflies are much larger and faster than detected no selection on PC1 of the morphological traits, which damselflies, damselflies potentially out maneuver dragonflies, largely reflects prey body size. In fact, the distributions of body which favors more active individuals (McPeek 1997; Strobbe size were nearly completely coincident among the treatments, al- et al. 2009, 2010). However, little evidence of nonconsumptive though the estimated selection differentials were of opposing sign. mortality was apparent in these previous field-based experiments Such a finding also implies that selection for increased activity lev- utilizing a similar experimental design (McPeek 1997; Stoks et al. els did not appear to translate into differences in damselfly growth 1999; Strobbe et al. 2009, 2010; but see Stoks 2001). We suspect rates. Higher levels of activity, including elevated damselfly at- this could due to the fact that the see-through predator enclosures tack rates on their prey, were found in both predator treatments. in the present indoor lab-study likely made the predator much All else being equal if more food is consumed body size should more visually detectable to damselflies. Although damselflies are increase but this was not found. One possibility is that the more able to detect olfactory cues of their predators, visual cues are active surviving individuals imposed through selection by drag- likely the dominant mode of predator detection (McGuffin and onflies resulted in less food being assimilated into biomass. In Baker 2012). This suggests the possibility that in the wild, the addition, damselflies that did survive were likely experiencing el- magnitude of these nonconsumptive effects could be linked with evated physiological stress levels as well, just insufficient to cause variation in the extent of cover or prey refugia from predators. In- mortality, which could affect food assimilation. Damselfly growth deed, variation in cover can affect indirect mortality rates of prey is density dependent and food limited (McPeek 1998). In the (Orrock et al. 2013) as well as the dynamics of natural selection no-predator treatment, the abundances of damselflies were much (Calsbeek et al. 2009). greater, meaning that any competitive effects for food were greater An alternative to predator-caused mortality explaining shifts as well, which would have been manifested as a smaller body size in the distributions of activity levels among treatments is that com- relative to the predator treatments. In contrast, where predators petitive effects varied among the treatments as well. Both dragon- were present there were fewer damselflies present, which should flies (as an intraguild predator) and damselflies competed for the have allowed individuals to grow larger because competition was shared prey (Artemia) resource in the experiment. Thus, selection less intense. Although the duration of the experiment may have may not all be due entirely to the effects of mortality by predatory not allowed us to detect this effect, it appears that any reduced dragonflies, but may also be due to competition for food. To some competition was compensated for by the greater activity levels extent this is possible, but we suspect that any competitive effects of surviving individuals, along with increased stress responses, of dragonflies would be quite low as there was a constant sup- which may account for the lack of size differences among treat- ply of food provided. Previous studies have shown that damselfly ments. Indeed, reduced prey growth is a common result of the growth is food limited (McPeek 1998), but as noted earlier, death presence of predators (reviewed in Peacor 2002). Finally, we do through starvation is unlikely (e.g., Lawton et al. 1980). An ad- note, however, that our analyses of selection only reflect total se- ditional possibility is that changes in the distributions of activity lection on phenotypes. The analyses do not allow us to infer the levels among treatments could be due to differences in density targets of selection in the way that selection gradient analyses do (e.g., Van Buskirk et al. 2011). The latter would be most impor- (e.g., Lande and Arnold 1983). The lack of observed selection on tant if activity levels were plastic, which as noted above does morphology may be the result of counteracting direct and indirect not appear to be the case for Ischnura. Although our experiment selection, rather than no selection at all. was not explicitly designed to test this possibility, we used an Understanding the contributions of selection through con- ANCOVA model including treatment and final density to exam- sumptive and nonconsumptive mortality informs us of the diverse ine the relative importance of predator treatments and final larval ways in which predators shape the dynamics of selection on their densities at the end of the experiment on the activity levels (PC1 prey. With the exception of apex predators, almost all are scores). This analysis revealed that only treatment (F2, 14 = 4.65, potential prey to a predator and the incredible array of defensive

P = 0.028) and not density (F1, 14 = 0.123, P = 0.730) was im- strategies that organisms have evolved is a testament to the force of portant in explaining PC1 scores (the interaction term was not predator-driven natural selection (Vermeij 1987). Indeed, numer- significant, F2, 12 = 0.057, P = 0.943, and was not included in ous studies have shown that variation in phenotypes influencing the results presented in the above model). Thus, density does not survival is ubiquitous in nature (Kingsolver et al. 2001; Siepielski seem to be an important determinant of activity levels. Regard- et al. 2011); however, only recently have we begun to understand less, future multifactorial experiments may provide further insight the consequences of nonconsumptive effects of predators. Our into how both consumptive and nonconsumptive mortality com- experimental decoupling of consumptive and nonconsumptive

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mortality implies that not all adaptations are necessarily adap- Langerhans, R. B., M. E. Gifford, and E. O. Joseph. 2007. Ecological specia- tations to avoid being consumed, as much as they may reflect the tion in Gambusia fishes. Evolution 61:2056–2074. evolutionary consequence of the joint problem of avoiding being Lande, R. and S. J. Arnold. 1983. The measurement of selection on correlated characters. Evolution 37:1210–1226. consumed and dealing with other sources of mortality attributable Lawton, J. H., B. A. Thompson, and D. J. Thompson. 1980. The effects of to predators. prey density on survival and growth of damselfly larvae. Ecol. Entomol. 5: 39–51. Lima, S. L., and L. M. Dill. 1990. Behavioural decisions made under the ACKNOWLEDGMENTS risk of predation: a review and prospectus. Can. J. Zool. 68: 619– The authors thank C. Benkman, S. Carlson, and M. McPeek for discus- 640. sions on the nature of selection and C. Benkman, T. Bird, S. Carlson, M. Losos, J. B., T. W. Schoener, and D. A. Spiller. 2004. Predator-induced be- Forister, S. McCauley, M. McPeek, T. Parchman, C. terHorst, and one haviour shifts and natural selection in field-experimental lizard popula- anonymous reviewer for valuable comments on earlier versions of this tions. Nature 432:505–508. manuscript. The authors also thank A. E. Siepielski for help with feed- McCauley, S. J., L. Rowe, and M. J. Fortin. 2011. The deadly effects of ing damselflies and dragonflies during the experiment, and A. Nickerson ‘non-lethal’ predators. Ecology 92: 2043–2048. and M. Cattiverra for help with the plasticity experiment. The authors McGuffin, M. A., and R. L. Baker. 2012. Larvae Ischnura verticalis (: declare no conflicts of interest. This research was supported in part by Cooenagrionidae) respond to visual cues of predator presence. J. the National Science Foundation (DEB-1255318). Behav. 25: 143–154. McPeek, M. A. 1990. 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Supporting Information Additional Supporting Information may be found in the online version of this article at the publisher’s website:

Table S1. Principal components analysis (PCA) loadings based on the correlation matrix for behavioral traits in the phenotypic plasticity experiment (n = 54 damselflies).

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