Behaviour 124 (2017) 153e159

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Animal Behaviour

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Selection on escape performance during ecological speciation driven by predation

* J. Swaegers a, , 1, F. Strobbe a, b, 1, M. A. McPeek c,R.Stoksa a Department of Biology, Laboratory of Aquatic Ecology, Evolution and Conservation, University of Leuven, Leuven, Belgium b Directorate Natural Environment, Biodiversity and Ecosystems Data and Information Centre, Royal Belgian Institute of Natural Sciences, Brussels, Belgium c Department of Biological Sciences, Dartmouth College, Hanover, NH, U.S.A. article info Despite the many study systems in which predation has played a major role in phenotypic diversification Article history: and speciation, the underlying selective regimes imposed by different predator assemblages have rarely Received 4 September 2016 been quantified. We did so for the damselfly genus which strongly diverged in antipredator Initial acceptance 12 October 2016 traits when the ancestral occupying lakes containing fish (hereafter fish lakes) repeatedly Final acceptance 24 November 2016 invaded fishless lakes with dragonfly larvae as top predators (hereafter dragonfly lakes). In two selection Available online 18 January 2017 experiments in field enclosures we quantified the selection on two key escape traits of two fish-lake MS. number: 16-00784R Enallagma species associated with survival selection by fish in the ancestral fish lakes and by drag- onfly predators in the invaded fishless, dragonfly lakes. In accordance with the different hunting modes, Keywords: fish imposed selection for a decreased swimming propensity while dragonfly larvae imposed selection antipredator behaviour for increased swimming speed in one of the two species. In two complementary quantitative genetic ecological speciation fi fl rearing experiments, we found relatively low but signi cant broad-sense heritabilities for both escape Enallagma damsel ies fi habitat shifts traits. Integrating these estimates for the selection coef cients and the heritabilities suggests that the phenotypic diversification evolutionary increase in swimming speed associated with the habitat shift may have occurred rapidly. Our study suggests that the phenotypic evolution of ecologically important traits related to habitat shifts may occur at an ecological timescale. © 2017 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Predators are a major selective force (reviewed in Endler, 1986; 2009; Stoks & McPeek, 2006; Vamosi, 2005; Wellborn, Skelly, & Tollrian & Harvell, 1999) and their role in phenotypic diversification Werner, 1996). has attracted considerable attention both at the intraspecific level The underlying selective regimes imposed by different predator (e.g. Carlson, Rich, & Quinn, 2009; Marchinko, 2009; Urban, 2010; assemblages have been quantified in relatively few study systems Ghalambor et al., 2015; Harris, Eroukhmanoff, Green, Svensson, & in which different predator assemblages have played a major role in Pettersson, 2011; Stoks, Govaert, Pauwels, Jansen, & De Meester, phenotypic diversification and speciation (Carlson et al., 2009; 2016) and at the interspecific level, where diversification is ex- Gordon, Feit, Gruber, & Letnic, 2015; Marchinko, 2009; Nosil & pected to have occurred on a much longer timeframe (e.g. Arbuckle Crespi, 2006; Svanback€ & Eklov,€ 2011). Such studies are impor- & Speed, 2015; Langerhans, Gifford, & Joseph, 2007; McPeek, tant to rule out alternative hypotheses underlying the phenotypic Schrot, & Brown, 1996; Mikolajewski et al., 2010; Nosil & Crespi, diversification such as differential habitat use and differences in 2006). Predator assemblages that differ in hunting mode can other biotic interactions (Goodman, Miles, & Schwarzkopf, 2008; impose different selection pressures on antipredator behaviour. Irschick, Bailey, Schweitzer, Husak, & Meyers, 2007; Urban & This may lead to phenotypic diversification of prey populations Richardson, 2015). Moreover, links between the phenotype and between habitats with different predator assemblages, eventually its adaptive value against certain predators, such as the survival accumulating into ecological speciation (Nosil, 2012; Schluter, value of a higher escape speed, cannot be taken for granted (Holmes & McCormick, 2009; Walker, Ghalambor, Griset, Mckenney, & Reznick, 2005). For example, Johnson, Burt, and Dewitt (2008) showed that a higher burst swimming speed in tadpoles of Rana sphenocephala did not influence survival in the * Correspondence: J. Swaegers, Charles Deberiotstraat 32, 3000 Leuven, Belgium. presence of dragonfly predators. Of the studies explicitly quanti- E-mail address: [email protected] (J. Swaegers). 1 First and second author contributed equally. fying selective regimes imposed by contrasting predator http://dx.doi.org/10.1016/j.anbehav.2016.12.012 0003-3472/© 2017 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved. 154 J. Swaegers et al. / Animal Behaviour 124 (2017) 153e159 assemblages nearly all have focused on intraspecific differentiation two fish-lake species, Enallagma geminatum and Enallagma hageni (for the only examples of incipient speciation see Marchinko, 2009; (Brown et al., 2000; McPeek & Brown, 2000; Turgeon et al., 2005), Nosil & Crespi, 2006). Moreover, no studies have reconstructed the that represent the two clades (and the associated ancestral phe- initial stages of predator-driven diversification in a system in which notypes) that independently gave rise to the dragonfly-lake Enal- the direction of the evolutionary change in predator assemblage is lagma. We quantified selection by fish on these traits in their known. Ideally, studies quantifying the predator-mediated selec- natural fish-lake habitat and by dragonfly predators in the derived tion strength should also estimate the heritability of the traits dragonfly lakes. These coupled experiments thus simulate the under selection to evaluate the potential of the selection pressures initial change in phenotypic selection regime presumably experi- to drive the evolutionary trajectories when predator regimes enced by the ancestral fish-lake species when they invaded drag- changed (Arnold, Pfrender, & Jones, 2001). onfly lakes within the last 20 000 years (McPeek & Brown, 2000; An elegant study system to explicitly quantify predator-driven Turgeon et al., 2005). We expected fish predation to select for a survival selection on escape behaviour is provided by the North lower propensity to swim but not to impose selection on escape American species of the damselfly genus Enallagma. Most Enal- swimming speed, while we expected dragonfly predation to select lagma species occur in lakes containing fish (hereafter called fish for a higher propensity to swim and a higher escape swimming lakes), the ancestral habitat, and three independent invasions have speed. In a previous paper (Strobbe, McPeek, De Block, & Stoks, occurred to fishless lakes where large predatory dragonfly larvae 2011) we quantified selection on foraging activity (number of are the top predators (hereafter called dragonfly lakes) (Brown, food items eaten) based on the enclosure experiment in the fish- McPeek, & May, 2000; McPeek & Brown, 2000; Turgeon, Stoks, lake habitat; here we focus on selection on escape traits. In Thum, Brown, & McPeek, 2005). These invasions into dragonfly another study (Strobbe et al., 2009) we documented selection on lakes were associated with the evolution of higher values for two escape speed by a derived dragonfly-lake Enallagma species in a related escape traits: swimming propensity and escape swimming dragonfly lake, allowing a qualitative comparison with ongoing speed (McPeek, 1999; McPeek et al., 1996). Escape swimming in selection pressures after the habitat shift in the evolved dragonfly- damselfly larvae occurs by moving the abdomen from side to side lake species. Moreover, by estimating the heritabilities of both (Brackenbury, 2002). This includes a behavioural component: escape behaviours for the two species of the lineages sharing most larvae swim faster if they beat their abdomens faster (McPeek, recent ancestry with current dragonfly-lake species, we were able Schrot, & Brown, 1996). The evolution of both traits is linked to to assess the scope for evolution by natural selection on these traits. the different efficacy of escape swimming as an antipredator strategy against fish and dragonfly predators. Damselfly larvae have METHODS little chance of outswimming a fish (McPeek, 2000; Stoks & De Block, 2000); moreover, swimming attracts the attention of the Selection Experiments fish predators (Baker, Elkin, & Brennan, 1999). Instead, damselfly larvae have a good chance of avoiding capture when attacked by We quantified selection by fish and by dragonfly larvae on larval dragonfly predators (McPeek, 1990b; McPeek et al., 1996; Stoks & escape traits of the two fish-lake Enallagma species in field enclo- De Block, 2000). In line with this, ongoing survival selection for a sures. We did so by contrasting trait values at the end of the higher swimming propensity and a higher swimming speed has enclosure experiment between two predator treatments: in one, been documented in a derived dragonfly-lake Enallagma species predators had been able to consume damselfly larvae (‘free-ranging using an enclosure experiment (Strobbe, McPeek, De Block, De predator’) and in the other predators had been caged (‘caged Meester, & Stoks, 2009). predator’) and hence had not been able to consume damselfly Two important pieces of information to assess the role of se- larvae (see also McPeek, 1997; Siepielski, Wang, & Prince, 2014; lection imposed by different predator assemblages in the ecological Strobbe et al., 2011, 2009). In the enclosures with a free-ranging speciation in this genus (and in most other study systems) are, predator three drivers of phenotypic change through time may be however, still missing. First, while we have quantified ongoing se- present: plasticity, nonconsumptive predator-driven selection and lection on the two key escape traits (swimming propensity and consumptive predator-driven selection. Indeed, the presence of fish swimming speed) in a derived dragonfly-lake Enallagma species and dragonfly predators may cause plastic changes in Enallagma (Strobbe et al., 2009), whether these traits are under different se- damselfly larvae: for example, a growth reduction and differential lection between fish lakes and dragonfly lakes in the ancestral fish- allocation of energy (McPeek, Grace, & Richardson, 2001; Stoks, De lake Enallagma species has not been investigated. This is crucial to Block, & McPeek, 2005) and a reduction in swimming speed caused reconstruct what happened under natural conditions during the by stress-induced oxidative damage (Janssens & Stoks, 2014). initial stages of the habitat shifts when fish-lake Enallagma species Further, predation risk may impose mortality in damselfly larvae invaded the fishless dragonfly lakes. For example, when escape caused not by consumptive killing by the predator but by physio- speed is so low that even the fastest individuals do not have a better logical stress (Siepielski et al., 2014; Stoks, 2001 see also McCauley, chance of escaping the new top predator, no survival selection on Rowe, & Fortin, 2011). It has been shown in damselfly larvae that this trait will be detected (Brodie, 1999), and directional selection this stress-induced mortality may not be random in relation to cannot have played its assumed role. Second, we need estimates phenotype and hence may impose nonconsumptive predator- not only of survival selection but also of heritabilities for these key driven selection (Siepielski et al., 2014). Given that any plasticity traits to evaluate the potential of directional selection to drive the and nonconsumptive predator-driven selection would also be observed evolutionary trajectories associated with the shift in present in a treatment with a caged predator, this is a more predator regimes and obtain a tentative timescale of the evolution appropriate control than a treatment without predators to quantify of these antipredator behaviours during the habitat shift. the selection imposed by consumptive survival selection by the Here, we present the results of two field enclosure experiments predators. Because all larvae were randomized across the enclo- in which we quantified selection pressures on both escape traits sures of the two treatments at the start of the experiment, it is (swimming propensity and swimming speed) in two fish-lake highly unlikely that there were initial differences in the trait dis- Enallagma species in the ancestral fish lakes and in the derived tributions between treatments. Any differences in the trait means dragonfly lakes to test for different patterns of directional selection at the end of the enclosure experiment between the treatments between habitats with different predator assemblages. We studied with caged predators and with free-ranging predators are therefore J. Swaegers et al. / Animal Behaviour 124 (2017) 153e159 155 likely to reflect selection imposed by consumption by the preda- stocked with damselfly larvae were placed in each lake. These en- tors. As all three drivers of trait change may be at work through closures were still without damselfly larvae by the end of the time in the enclosures with a free-ranging predator, the alternative experiment, indicating that no damselfly larvae of the natural lake approach of comparing the phenotypic distribution of the larvae populations entered the enclosures through the netting. In between the start and end of the enclosure experiment is also less contrast, all enclosures were colonized in high numbers by prey appropriate. (mainly midge larvae, mayfly larvae and zooplankton). The experiments were performed in a fish lake and in a drag- At the start of the experiment, on 8 September 2003, we onfly lake so that the natural selective environments were matched introduced one predator and 30 E. hageni and 30 E. geminatum as closely as possible and to enable reconstruction of the change in larvae in each enclosure. These larval densities reflect densities in selection strength experienced by the ancestor species when they natural Enallagma populations (McPeek, 1990a). All larvae were switched from fish lakes to fishless, dragonfly lakes. In Strobbe et al. collected from Little Salem Lake (Derby, VT, U.S.A.). So, in neither (2011) we reported the survival data and focused on selection on experiment did we test larvae in their native lake, thereby avoiding foraging activity; here we focus on unpublished data on selection potential effects of local adaptation (Siepielski, Nemirov, Cattivera, on escape behaviour. In addition, here we present data on a similar & Nickerson, 2016). In the larger enclosures in the fish-lake unpublished dragonfly-lake experiment with the same two species experiment we also added 60 damselfly larvae of other genera to quantify selection on escape behaviour when fish-lake Enallagma than Enallagma to mimic total densities of damselfly larvae in fish invaded dragonfly lakes. We describe the common experimental lakes. This also ensured that we recovered enough larvae of the protocols implemented in the two lake types and indicate where focal species in the presence of a free-ranging sunfish. After 35 differences occurred. days, the experiment was stopped. Mortality rates were calculated We used semipermeable enclosures that allowed small prey per species and per enclosure as e [ln (final number of damselfly items to enter the enclosures, but prevented damselfly larvae from larvae) ln (initial number of damselfly larvae)]/35 days. escaping. These enclosures were 1.2 m high cylindrical chicken wire Recovered larvae with three intact lamellae were kept individ- frames (mesh size 2 cm) with a diameter of 65 cm for the fish-lake ually in plastic cups (100 ml) until their escape traits were quan- experiment and 30 cm for the dragonfly-lake experiment (McPeek, tified (within 48 h and frozen afterwards). We measured both 1990a,1998). Enclosures were placed at a depth of 90 cm, with their escape traits (swimming propensity and swimming speed) by open top extending 30 cm out of the water. The enclosures were videotaping larvae swimming in a container (34 26 cm and 6 cm covered with mosquito netting and had a plastic dish with pebbles high) in the laboratory. We followed the methodology described in at the bottom. To provide natural structure, we added local den- McPeek et al. (1996) and Strobbe et al. (2009). Briefly, a single larva sities of stonewort, Chara vulgaris, stems. Note that we used larger was placed in the container, allowed to settle, and then gently enclosures in the fish lake as fish are larger predators than drag- prodded to swim by lightly tapping behind the larva with blunt onfly larvae (following McPeek, 1990a; McPeek, 1998, 2004). It is forceps. A larva was given a swimming propensity score 1 when it unlikely, however, that the enclosure size would affect the sign of swam away, and 0 when it did not swim away. This measure is the selection coefficient imposed by the predator on the perfor- highly repeatable for a given larva (Strobbe et al., 2009). Three mance traits. Moreover, mortality rates and growth rates in en- swimming bouts per larva were videotaped and digitized and the closures of these sizes and where selection can occur (enclosures fastest swimming speed was retained for analysis. As heavier larvae with predators that could kill the damselfly larvae) do not differ swam faster we also weighed the larvae to the nearest 0.01 mg on from those in natural Enallagma populations in both lake types an electronic balance after gently blotting them dry with towel (McPeek, 1990a, 2004). This enclosure set-up therefore probably paper. In the fish-lake experiment the final body masses were on allowed us to obtain realistic estimates of selection imposed by fish average 15.95 ± 0.32 mg (mean ± 1 SE) for E. hageni and and dragonfly predators. 18.94 ± 0.38 for E. geminatum. In the dragonfly-lake experiment The predators used were sunfish, Lepomis gibbosus (standard final body masses were on average 17.50 ± 0.51 for E. hageni and length ca. 6 cm) in the fish-lake experiment and antepenultimate 20.13 ± 0.43 for E. geminatum. instar Anax junius larvae (standard length ca. 4 cm) in the We quantified swimming propensity of 274 larvae and swim- dragonfly-lake experiment. For the caged-predator treatment, one ming speed of 221 larvae (not all larvae swam when prodded, hence predator was placed in a small cage covered with mosquito netting the lower number). Specific sample sizes per combination of spe- within the enclosure. Damselfly larvae had all their usual means of cies and predator enclosure treatment are given in the Results. detecting that a predator was present in the enclosure (e.g. vision and olfaction), but could not be consumed by the predator. In the fish-lake selection experiment this cage was a 20 20 20 cm Quantitative Genetic Rearing Experiments cube made from plastic tubes and surrounded with a mosquito netting bag, and in the dragonfly-lake selection experiment it was a To estimate the broad-sense heritabilities of both antipredator coarse-mesh (openings 1.7 cm 1.0 cm) plastic container behaviours for both study species, we carried out common-garden (11 11 cm and 6 cm high) similarly covered by a mosquito netting full-sib rearing experiments. Females in copula were collected in bag. For the free-predator treatment, identical cages without a JuneeJuly at the fish lakes McDaniel's Marsh (E. geminatum) and predator were placed in the enclosures, and one predator that Little Salem Lake (E. hageni) in 2003 and 2004, respectively. In the could freely consume damselflies was introduced in each enclosure. laboratory, females were individually placed in glass jars covered We placed the enclosures in the lakes on 1 September 2003. We with mosquito netting in a temperature-controlled room at 21 C placed 12 enclosures (caged-fish treatment: 4; free-ranging-fish (15:9 h light:dark photoperiod). To provide oviposition substrate, treatment: 8) in the fish lake McDaniels Marsh (Enfield, NH, filter paper was provided. After oviposition, the filter papers with U.S.A.) and 17 enclosures (caged-dragonfly treatment: 4; free- eggs were placed in plastic containers (18 12 cm and 7 cm high) ranging-dragonfly treatment: 13) in the dragonfly lake Sylvester filled to a height of 1 cm with filtered pond water. Although female Pond (Norwich, VT, U.S.A.). Given that we expected lower survival damselflies can store sperm from previous partners, a study on in the enclosures where the predators could consume the damselfly E. hageni showed that the last male to mate fertilized up to 95% of larvae, we set up more replicates of the free-ranging predator the eggs of the first clutch laid after mating (Fincke, 1984). There- treatments. In addition, three control enclosures that were not fore, the incidence of paternal half-sibs in a clutch is expected to be 156 J. Swaegers et al. / Animal Behaviour 124 (2017) 153e159 very low. The number of full-sib families included in the experi- 0.1 ment was 28 for E. geminatum and 30 for E. hageni. (a) Enallagma hageni Larvae were reared individually in nontransparent plastic cups 0.08 Enallagma geminatum (diameter 4 cm, height 10 cm, filled to a height of 5 cm with water). Larvae were fed Artemia nauplii ad libitum daily. When larvae 0.06 moulted into the final instar, swimming propensity and swimming speed were scored using the same methodology as used in the 0.04 selection experiment. Depending on the species, 5e16 larvae per full-sib family were measured for swimming propensity and speed (total of 770 larvae). 0.02

Statistical Analyses 0

We tested for effects of predator treatment and species on –0.02 mortality rate using a mixed-model ANOVA. Enclosure nested in Caged fish Free-ranging fish predator treatment was added as a random variable to take the two mortality rates per enclosure into account, one for each species. 0.05 (b) To specifically test for phenotypic selection on the escape be-

haviours, we directly compared the caged and free predator treat- Mortality rate (per day) 0.04 ments for each species separately. For swimming propensity, a binary response variable, we defined a binomial error structure and the logit link using the lme package in R 3.3.0 (The R Foundation for 0.03 Statistical Computing, Vienna, Austria, http://www.r-project.org). fi For swimming speed, we de ned a normal error structure and the 0.02 identity link and added mass as a covariate. In these models, we included enclosure as a random variable to take advantage of the full data set while overcoming the problem of pseudoreplication 0.01 within enclosures (Brown & Prescott, 2014; Millar & Anderson, 2004). Given that we had a priori expectations that fish (drag- 0 onfly) predation would select for a lower (higher) swimming pro- Caged dragonfly Free-ranging dragonfly pensity, and dragonfly predation would select for a higher Predator treatment swimming speed, we provide one-tailed P values for these tests. Note that we did not expect selection by fish predation on swim- Figure 1. Daily mortality rates of Enallagma geminatum and Enallagma hageni larvae in fi fl ming speed. The value of the corresponding selection coefficient the caged- and free-predator treatments of the (a) sh-lake and (b) dragon y-lake selection experiments. Least square means ± 1 SE are shown. Means are based on (a) was estimated by dividing the difference in swimming traits be- four caged-fish and eight free-fish enclosures and (b) four caged-dragonfly and 13 free- tween the free-ranging predator and caged-predator treatments by dragonfly enclosures. the pooled standard deviation (Lande & Arnold, 1983). ) ¼ To estimate broad-sense heritabilities, we analysed each trait Enallagma species (Species Predator treatment: F1,9 0.48, ¼ separately per species using animal model analyses (see Alho, P 0.51; Fig. 1a). Leinonen, & Merila,€ 2011) in the MCMCglmm package (Hadfield, Swimming propensity was lower for E. hageni larvae recovered 2010) with R 2.10.1. In the models, the term ‘animal’ (which is from the free-ranging predator treatment than for those recovered c2 ¼ ¼ referenced back to the pedigree) was included as a random effect. from the caged-predator treatment ( 1 3.73, P 0.026; Fig. 2a). c2 ¼ ¼ The heritability estimates are reported as posterior means together This was not the case for E. geminatum ( 1 0.02, P 0.44; fi with 95% highest posterior density intervals (95% HPDIs). We ob- Fig. 2a). The associated standardized selection coef cient on tained an estimate of the broad-sense heritability by applying the swimming propensity for E. hageni was 2.87 standard deviation 2 units. Swimming speed did not differ between predator treatments basic formula h ¼ VA/VP, where VA is the additive genetic variance in either species (both P > 0.06; Fig. 2b). and VP the phenotypic variance. Using Bayesian inference, more specifically Markov chain Monte Carlo methods, we estimated the 95% highest posterior density intervals to see whether they span- Dragonfly-lake Selection Experiment ned zero. For swimming speed, the Markov chains were run for 65 000 iterations. The first 15 000 iterations were discarded as Dragonfly larvae imposed similar strong mortality on both these are less reliable. Iterations were sampled every 50th sample Enallagma species (Predator treatment: F1,30 ¼ 8.88, P ¼ 0.006; to reduce autocorrelation between successive samples (Wilson Species)Predator treatment: F1,30 ¼ 1.04, P ¼ 0.32; Fig. 1b). et al.,2010). For swimming propensity (a binary trait) we used a Swimming propensity did not differ between larvae recovered probit link. The analysis was run for 1000 000 iterations where the from both predator treatments (both P > 0.30; Fig. 2c). Swimming first 10 000 iterations were discarded and an interval of 100 sam- speed was higher for larvae recovered in the free-ranging dragonfly ples was used (de Villemereuil, 2012). treatment than for those recovered in the caged-dragonflytreatment in E. hageni (t14 ¼ 2.07, P ¼ 0.028) but not in E. geminatum (t10 ¼ 0.45, RESULTS P ¼ 0.331; Fig. 2d). The associated selection coefficient on swimming speed for E. hageni was þ0.74 standard deviation units. Fish-lake Selection Experiment Quantitative Genetic Rearing Experiments Fish imposed strong mortality on both Enallagma species (Predator treatment: F1,9 ¼ 12.32, P ¼ 0.007), and the increase in The full-sibling estimated heritabilities of the two escape be- mortality rate due to direct fish predation did not differ for the two haviours were significantly different from zero in each species and J. Swaegers et al. / Animal Behaviour 124 (2017) 153e159 157

1 110 (a) Enallagma hageni (b) 100 0.8 Enallagma geminatum 50 90 9 0.6 71 80 38 21 0.4 70 46 15 0.2 24 60

0 50 Caged fish Free-ranging fish Caged fish Free-ranging fish

1 110 (c) (d) 100 Swimming propensity 0.8 43 12 Swimming speed (mm/s)' 90 8 0.6 48 14 80 9 0.4 49 70 43

0.2 60

0 50 Caged dragonfly Free-ranging dragonfly Caged dragonfly Free-ranging dragonfly Predator treatment

Figure 2. (a, c) Swimming propensity and (b, d) swimming speed of Enallagma geminatum and Enallagma hageni larvae in the caged- and free-predator treatments of the (a, b) fish- lake and (c, d) dragonfly-lake selection experiments. Least square means ± 1 SE are shown. Numbers with symbols represent sample sizes. varied between 0.14 and 0.28 (Table 1). Given the full-sibling design propensity to swim and a higher escape swimming speed (McPeek, and hence potential maternal effects, the heritability estimates may 2000; McPeek et al., 1996), and genetic evidence indicates that be biased upwards. E. hageni is the fish-lake progenitor from which one of the habitat shifts into the dragonfly lake habitat was derived (Turgeon et al., 2005). DISCUSSION Fish predation favoured larvae with a lower propensity to swim in E. hageni. Not swimming in the presence of fish is favoured for fi fl In line with the strong mortality imposed by sh and dragon y two reasons. Swimming makes larvae more detectable by fish predators, the results of this study demonstrate different patterns predators (Baker et al., 1999), and swimming away to escape fish of phenotypic selection on each type of escape traits between the predation is not effective because fish can swim much faster than two habitats for E. hageni. Some mortality may have been caused by damselfly larvae (Stoks & De Block, 2000). This also explains why cannibalism, yet this would have occurred in both treatments with no selection on swimming speed was detected in the fish-lake caged and with free-ranging predators and therefore is unlikely to experiment: if larvae do not express the behaviour to swim, se- have affected treatment differences. The observed patterns were lection cannot operate on swimming speed. Field studies evalu- expected based on a priori knowledge of the role of swimming to ating survival selection on the propensity to escape when attacked fi fl survive sh attacks versus dragon y attacks in Enallagma damsel- are rare. One notable exception is the study by Janzen (1995) who fl ies (McPeek, 1990b, 1997; McPeek et al., 1996). These results are reported similar negative survival selection on the propensity of also consistent with evolutionary reconstructions within this genus turtle hatchlings to run. The proposed underlying explanation was fl showing that species that invaded dragon y lakes evolved a higher similar to that for our study: motionless are cryptic and therefore have increased survivorship over more active individuals Table 1 that flee when they are faced with a predator that they have little 2 fi Heritabilities (h ) of swimming propensity and escape swimming speed for two sh- chance of escaping. lake Enallagma species: E. geminatum and E. hageni based on a full-sib rearing fl experiment In contrast, we could detect no selection by dragon y predation for a higher swimming propensity. Given that larvae of Enallagma Performance trait E. geminatum E. hageni species native to dragonfly lakes use swimming to escape attacks h2 HPDI h2 HPDI by dragonfly predators and we documented ongoing selection for a Swimming propensity 0.23 <0.001e0.675 0.28 0.078e0.755 higher swimming propensity in a derived dragonfly-lake Enallagma Swimming speed 0.24 0.039e0.601 0.14 0.052e0.547 species (Strobbe et al., 2009), such selection pressure was expected fl Confidence intervals are expressed as 95% highest posterior density intervals in this study. Phenotypic variability among the damsel y larvae (HPDI). used in this experiment may have been too small to detect 158 J. Swaegers et al. / Animal Behaviour 124 (2017) 153e159 phenotypic selection on swimming propensity over a month of and dragonfly predators may indeed result in evolutionary responses exposure to dragonfly predators. These results may also suggest contributing to the differentiation in both escape traits when fish- that an ordering effect is important to make escape from attacking lake Enallagma invaded dragonflylakes(McPeek & Brown, 2000; predators an effective antipredator adaptation, that is, first a higher McPeek et al., 1996). Admittedly, some degree of caution must be swimming speed is needed before swimming propensity can be an exercised when interpreting the estimates of the variance compo- advantage. The dragonfly-lake Enallagma larvae of comparable nents for swimming propensity as quantitative genetic analyses of sizes to individuals used in the present study have swim speeds of binary data are not without caveats (de Villemereuil, Gimenez, & 10e25 cm/s, whereas the fish-lake E. hageni and E. geminatum had Doligez, 2013). Also, the relatively wide 95% HPD intervals indicate maximum speeds of 7e10 cm/s (this study and McPeek et al., 1996; low precision of the heritability estimates. Nevertheless, our data McPeek, 2000). Perhaps the escape swimming speeds of the fish- suggest minimal heritability for both traits. lake Enallagma species when attacked by dragonfly predators By integrating data on selection strength and heritabilities, were too low to give animals with a higher propensity to swim crude estimates can be made of how rapidly these evolutionary away a detectable survival advantage. changes during habitat shifts may have occurred. For example, Despite no significant phenotypic selection on swimming pro- phylogenetic analyses suggest that E. hageni is the fish-lake pensity, we did detect significant survival selection imposed by the ancestor of the dragonfly-lake clade including E. annexum dragonfly predators for a higher swimming speed in E. hageni. This (Turgeon et al., 2005). Based on swimming speed data obtained is consistent with previous laboratory studies showing that larvae from larvae recovered from the caged-predator treatments in that swim faster have a higher probability of surviving dragonfly E. hageni (mean ± SD: 77.99 ± 6.91 mm/s, current study) and attacks (McPeek et al., 1996). E. annexum (104.95 ± 5.32 mm/s, Strobbe et al., 2009), swimming In contrast to these results for E. hageni, we could detect no speed differs between these species by 5.07 SD units. Given the significant phenotypic selection on E. geminatum larvae in either degree of heritability of swimming speed we estimated in E. hageni habitat. The E. geminatum larvae recovered from the fish predation (0.14) and the documented selection coefficient (0.74 SD units) it experiment already had a much lower swimming propensity than may have taken only ca. 43 years (Enallagma have one generation E. hageni (Fig. 2a), suggesting a lack of significant variation on which per year) to evolve the higher swimming speed in the derived selection could have acted. The lack of a response for swimming dragonfly-lake species. A similarly short period has been estimated propensity or speed in the dragonfly-lake selection experiment is from similar information on lamellae size (McPeek, 1997). Such more puzzling. Possibly, the dragonfly predators may have rapid evolutionary responses would be critical for a successful preferred other prey with less efficient escape traits thereby pre- habitat shift to turn the founder population from a sink population cluding detecting selection on escape traits in E. geminatum. being driven extinct by dragonfly predation to a source population Our results do not support the hypothesis of divergent survival that is adapted to living with dragonflies. The associated evolu- selection pressures imposed by fish and dragonfly predators on tionary rate of 0.10 haldanes indicates rapid evolution (sensu swimming propensity. Our results demonstrate in one species Hendry & Kinnison, 1999). Interestingly, the observed rapid evo- (E. geminatum) that selection in the ancestral fish-lake environ- lution in escape performance is similar to the reported rapid ment operated against the use of swimming as an evasive tactic. (26e36 generations) evolution of escape ability in guppies. Poecilia Consistent with an overall scenario of opposing selection on reticulata, when they invaded high-predation habitats (O'Steen, swimming propensity across lake types, a previous experiment Cullum, & Bennett, 2002). This would suggest that for predator showed that survival selection imposed by dragonfly predators escape traits, phenotypic evolution associated with ecological favoured higher swimming propensities in the derived dragonfly- speciation linked to habitat shifts may at least have the potential to lake species Enallagma annexum (Strobbe et al., 2009). Yet, we occur as rapidly as evolutionary responses within species, although could not detect dragonfly-imposed survival selection for an counteracting gene flow might have slowed down the speciation increased swimming propensity in the present study utilizing fish- process. By embedding selection experiments in an evolutionary lake Enallagma. This may not be that surprising. When a lineage historical analysis, a deeper understanding of the genesis of bio- invades a new ecological environment, individuals in many founder logical diversity can be gained. populations are often likely to be too maladapted for selection to act (McPeek, 2000). This is because only a very weak phenoty- Acknowledgments peefitness covariation will be present when phenotypes are too far from the phenotypic optimum (Brodie, 1999; Toju & Sota, 2006). Two anonymous referees and the Editor provided very useful Only the rare invasion will be successful, by invaders that probably comments to improve the manuscript. J.S. was supported by a BOF by chance are phenotypically closest to the new adaptive peak Postdoctoral Mandate (PDM) from KU Leuven. F.S. was supported as (McPeek, 2000); survival selection will be strong for these invaders, a PhD fellow of IWT-Flanders. This study was funded by research thereby rapidly pushing the phenotype to the new optimum. grants from FWO and the KULeuven Centre of Excellence Program Our results provided some support for the hypothesis that fish PF/2010/07 to R.S. and NSF grant DEB-0516104 to M.A.M. predation did not impose survival selection on swimming speed in the ancestral fish lakes, while dragonfly predation imposed survival References selection for a faster swimming speed. Yet, the latter was only observed in E. hageni. Together with the selection for increased Alho, J. S., Leinonen, T., & Merila,€ J. (2011). Inheritance of vertebral number in the swimming speed on the fish-lake Enallagma by the new predator in three-spined stickleback (Gasterosteus aculeatus). PLoS One, 6, e19579. http:// dx.doi.org/10.1371/journal.pone.0019579. the dragonfly lakes (which is still ongoing in dragonfly-lake Enal- Arbuckle, K., & Speed, M. P. (2015). Antipredator defenses predict diversification lagma, Strobbe et al., 2009) that we found in the present study, this rates. Proceedings of the National Academy of Sciences of the United States of may generate differentiation in swimming speed between species America, 112, 201509811. http://dx.doi.org/10.1073/pnas.1509811112. Arnold, S. J., Pfrender, M. E., & Jones, A. G. (2001). The adaptive landscape as a in both lake types. conceptual bridge between micro- and macroevolution. Genetica, 112,9e32. For both escape traits, we have shown significant broad-sense Baker, R. L., Elkin, C. M., & Brennan, H. A. (1999). Aggressive interactions and risk of heritabilities that are close to measured estimates of heritability of fish predation for larval damselflies. Journal of Behavior, 12,213e223. ± & Brackenbury, J. (2002). Kinematics and hydrodynamics of an invertebrate undula- other antipredator behaviours (0.33 0.038, Stirling, Reale, Roff, tory swimmer: The damsel-fly larva. Journal of Experimental Biology, 205, 2002). This indicates that the selection pressures imposed by fish 627e639. J. Swaegers et al. / Animal Behaviour 124 (2017) 153e159 159

Brodie, E. D. (1999). Predator-prey arms races. BioScience, 49,557. Mikolajewski, D. J., De Block, M., Rolff, J., Johansson, F., Beckerman, A. P., & Stoks, R. Brown, M., McPeek, M. A., & May, M. L. (2000). A phylogenetic perspective on (2010). Predator-driven trait diversification in a dragonfly genus: Covariation habitat shifts and diversity in the North American Enallagma damselflies. Sys- in behavioral and morphological antipredator defense. Evolution, 64, tematic Biology, 49,697e712. 3327e3335. Brown, H., & Prescott, R. (2014). Applied mixed models in medicine. Chichester, U.K.: J. Millar, R. B., & Anderson, M. J. (2004). Remedies for pseudoreplication. Fisheries Wiley. Research, 70,397e407. Carlson, S. M., Rich, H. B., & Quinn, T. P. (2009). Does variation in selection imposed Nosil, P. (2012). Ecological speciation. Oxford, U.K.: Oxford University Press. by bears drive divergence among populations in the size and shape of sockeye Nosil, P., & Crespi, B. J. (2006). Experimental evidence that predation promotes salmon? Evolution, 63, 1244e1261. divergence in adaptive radiation. Proceedings of the National Academy of Sciences Endler, J. A. (1986). Natural selection in the wild. Princeton, NJ: Princeton University of the United States of America, 103, 9090e9095. Press. O'Steen, S., Cullum, A. J., & Bennett, A. F. (2002). Rapid evolution of escape ability in Fincke, O. M. (1984). Sperm competition in the damselfly Enallagma hageni Walsh Trinidadian guppies (Poecilia reticulata). Evolution, 56,776e784. (: ): Benefits of multiple mating to males and females. Schluter, D. (2009). Evidence for ecological speciation and its alternative. Science, Behavioral Ecology and Sociobiology, 14,235e240. 323(5915), 737e741. Ghalambor, C. K., Hoke, K. L., Ruell, E. W., Fischer, E. K., Reznick, D. N., & Hughes, K. A. Siepielski, A. M., Nemirov, A., Cattivera, M., & Nickerson, A. (2016). Experimental (2015). Non-adaptive plasticity potentiates rapid adaptive evolution of gene evidence for an eco-evolutionary coupling between local adaptation and expression in nature. Nature, 525,372e375. intraspecific competition. American Naturalist,447e456. Goodman, B. A., Miles, D. B., & Schwarzkopf, L. (2008). Life on the rocks: Habitat use Siepielski, A. M., Wang, J., & Prince, G. (2014). Nonconsumptive predator-driven drives morphological and performance evolution in lizards. Ecology, 89, mortality causes natural selection on prey. Evolution, 68, 696e704. 3462e3471. Stirling, D. G., Reale, D., & Roff, D. A. (2002). Selection, structure and the heritability Gordon, C. E., Feit, A., Gruber, J., & Letnic, M. (2015). Mesopredator suppression by of behaviour. Journal of Evolutionary Biology, 15,277e289. an apex predator alleviates the risk of predation perceived by small prey. Pro- Stoks, R. (2001). Food stress and predator-induced stress shape developmental ceedings of the Royal Society B: Biological Sciences, 282, 20142870e20142870. performance in a damselfly. Oecologia, 127, 222e229. Hadfield, J. D. (2010). MCMC methods for multi-response generalized linear mixed Stoks, R., & De Block, M. (2000). The influence of predator species and prey age on models: The MCMCglmm R package. Journal of Statistical Software, 33,1e22. the immediate survival value of antipredator behaviours in a damselfly. Archiv Harris, S., Eroukhmanoff, F., Green, K. K., Svensson, E. I., & Pettersson, L. B. (2011). für Hydrobiologie, 147,417e430. Changes in behavioural trait integration following rapid ecotype divergence in Stoks, R., De Block, M., & McPeek, M. A. (2005). Alternative growth and energy an aquatic isopod. Journal of Evolutionary Biology, 24, 1887e1896. storage responses to mortality threats in damselflies. Ecology Letters, 8, Hendry, A., & Kinnison, M. (1999). Perspective: The pace of modern life: Measuring 1307e1316. rates of contemporary microevolution. Evolution, 53, 1637e1653. Stoks, R., Govaert, L., Pauwels, K., Jansen, B., & De Meester, L. (2016). Resurrecting Holmes, T. H., & McCormick, M. I. (2009). Influence of prey body characteristics and complexity: The interplay of plasticity and rapid evolution in the multiple trait performance on predator selection. Oecologia, 159,401e413. response to strong changes in predation pressure in the water flea Daphnia Irschick, D., Bailey, J., Schweitzer, J., Husak, J., & Meyers, J. (2007). New directions for magna. Ecology Letters, 19,180e190. studying selection in nature studies of performance and communities. Physio- Stoks, R., & McPeek, M. A. (2006). A tale of two diversifications: Reciprocal habitat logical and Biochemical Zoology, 80,557e567. shifts to fill ecological space along the pond permanence gradient. American Janssens, L., & Stoks, R. (2014). Chronic predation risk reduces escape speed by Naturalist, 168, S50eS72. increasing oxidative damage: A deadly cost of an adaptive antipredator Strobbe, F., McPeek, M. A., De Block, M., De Meester, L., & Stoks, R. (2009). Survival response. PloS One, 9,e101273. selection on escape performance and its underlying phenotypic traits: A case of Janzen, F. J. (1995). Experimental evidence for the evolutionary significance of many-to-one mapping. Journal of Evolutionary Biology, 22,1172e1182. temperature-dependent sex determination. Evolution, 49, 864e874. Strobbe, F., McPeek, M. A., De Block, M., & Stoks, R. (2011). Fish predation selects Johnson, J. B., Burt, D. B., & Dewitt, T. J. (2008). Form, function, and fitness: Pathways for reduced foraging activity. Behavioral Ecology and Sociobiology, 65, to survival. Evolution, 62, 1243e1251. 241e247. Lande, R., & Arnold, S. J. (1983). The measurement of selection on correlated Svanback,€ R., & Eklov,€ P. (2011). Catch me if you canepredation affects divergence in characters. Evolution, 37,1210e1226. a polyphenic species. Evolution, 65,3515e3526. Langerhans, R. B., Gifford, M. E., & Joseph, E. O. (2007). Ecological speciation in Toju, H., & Sota, T. (2006). Adaptive divergence of scaling relationships Gambusia fishes. Evolution, 61, 2056e2074. mediates the arms race between a weevil and its host plant. Biology Letters, 2, Marchinko, K. B. (2009). Predation's role in repeated phenotypic and genetic 539e542. divergence of armor in threespine stickleback. Evolution, 63,127e138. Tollrian, R., & Harvell, C. D. (1999). The ecology and evolution of inducible defenses. McCauley, S. J., Rowe, L., & Fortin, M. J. (2011). The deadly effects of “nonlethal” Princeton, NJ: Princeton University Press. predators. Ecology, 92, 2043e2048. Turgeon, J., Stoks, R., Thum, R. A., Brown, J. M., & McPeek, M. A. (2005). Simulta- McPeek, M. A. (1990a). Behavioral differences between Enallagma species (Odo- neous quaternary radiations of three damselfly clades across the Holarctic. nata) influencing differential vulnerability to predators. Ecology, 71,1714e1726. American Naturalist, 165, E78eE107. McPeek, M. A. (1990b). Determination of species composition in the Enallagma Urban, M. C. (2010). Microgeographic adaptations of spotted salamander morpho- damselfly assemblages of permanent lakes. Ecology, 71,83e98. logical defenses in response to a predaceous salamander and beetle. Oikos, 119, McPeek, M. A. (1997). Measuring phenotypic selection of an adaptation: Lamellae of 646e658. damselflies experiencing dragonfly predation. Evolution, 51, 459e467. Urban, M. C., & Richardson, J. L. (2015). The evolution of foraging rate across local McPeek, M. A. (1998). The consequences of changing the top predator in a food and geographic gradients in predation risk and competition. American Natu- web: A comparative experimental approach. Ecological Monographs, 68(1), ralist, 186,E16eE32. 1e24. Vamosi, S. M. (2005). On the role of enemies in divergence and diversification of McPeek, M. (1999). Biochemical evolution associated with antipredator adaptation prey: A review and synthesis. Canadian Journal of Zoology, 83, 894e910. in damselflies. Evolution, 53, 1835e1845. de Villemereuil, P. (2012). Estimation of a biological trait heritability using the animal McPeek,M.A.(2000).Predisposedtoadapt?Clade-leveldifferencesin model. devillemereuil.legtux.org/wp-content/uploads/2012/12/tuto_en.pdf. characters affecting swimming performance in damselflies. Evolution, 54, de Villemereuil, P., Gimenez, O., & Doligez, B. (2013). Comparing parent-offspring 2072e2080. regression with frequentist and Bayesian animal models to estimate heritabil- McPeek, M. A. (2004). The growth/predation risk trade-off: So what is the mech- ity in wild populations: A simulation study for Gaussian and binary traits. anism? American Naturalist, 163, E88eE111. Methods in Ecology and Evolution, 4(3), 260e275. McPeek, M. A., & Brown, J. M. (2000). Building a regional species pool: Diversifi- Walker, J. A., Ghalambor, C. K., Griset, O. L., Mckenney, D., & Reznick, D. N. (2005). Do cation of the Enallagma damselflies in eastern North America. Ecology, 81, faster starts increase the probability of evading predators? Functional Ecology, 904e920. 19, 808e815. McPeek, M. A., Grace, M., & Richardson, J. M. L. (2001). Physiological and behavioral Wellborn, G. A., Skelly, D. K., & Werner, E. E. (1996). Mechanisms creating com- responses to predators shape the growth/predation risk trade-off in damsel- munity structure across a freshwater habitat gradient. Annual Review of Ecology flies. Ecology, 82, 1535e1545. and Systematics, 27,337e363. McPeek, M. A., Schrot, A. K., & Brown, J. M. (1996). Adaptation to predators in a new Wilson, A. J., Reale, D., Clements, M. N., Morrissey, M. M., Postma, E., Walling, C. A., community: Swimming performance and predator avoidance in damselflies. et al. (2010). An ecologist's guide to the animal model. Journal of Animal Ecology, Ecology, 77,617e630. 79,13e26.