8

Behavioral Plasticity to Risk of Predation: Oviposition Site Selection by a in Response to its Predators

Leon Blaustein1, 2 and Douglas W. Whitman3 1Community Ecology Laboratory, Institute of Evolution, Department of Evolutionary and Environmental Biology, Faculty of Sciences, University of Haifa, Haifa 31905, . 2Center for Vector Biology, Rutgers University, New Brunswick, New Jersey 08901, USA. E-mail: [email protected] 34120 Department of Biological Sciences, Illinois State University, Normal, IL 61790, USA. E-mail: [email protected]

Abstract Oviposition habitat selection in response to risk of predation is an environmentally induced phenotypic plastic response. We suggest predator- prey characteristics for which such a response is more likely to evolve: high vulnerability of progeny to the predator; deposition of all eggs from a single reproductive event in a single site (i.e., inability to spread the risk spatially); few opportunities to reproduce (i.e., unable to spread the risk temporally); during habitat assessment by the gravid female, high predictability of future risk of predation for the period in which the progeny develop at the site; the predator is common but some sites are predator-free. We summarize work done on a particular system—the mosquito longiareolata Macquart and its predators in pool habitats, a likely candidate system for oviposition habitat selection in response to risk of predation given these proposed characteristics. Adult C. longiareolata females can chemically detect various predatory backswimmer species () but do not appear to chemically detect odonate and urodele larvae. Evidence suggests however that ovipositing females may detect other predators by nonchemical cues. C. longiareolata females can also detect and respond to larval food resource levels and conspecific larvae when choosing an oviposition site. When given only the two poor habitat choices of high conspecific larval densities or ! & Phenotypic Plasticity of

Notonecta, overall oviposition rates drop and a larger proportion of the females oviposit in predator pools suggesting that females may operate in an ideal-free distribution manner. When comparing versus non- predator pools, the proportion of egg rafts in predator-free pools increases when the proportion of predator-free pools increases. The most likely explanation among competing hypotheses is that the mosquito females that oviposit in predator pools are those that have encountered only predator pools when “sampling” the environment and ultimately choose to oviposit in a poor quality pool than no pool at all. A growing body of literature suggests that predator avoidance when ovipositing is particularly prevalent among pool/pond species with a mobile adult stage (amphibians and insects). We suggest that this is because risk of predation during the period in which offspring will grow is predictable based on risk of predation at the time that the female assesses habitats. Nonrandom selection of oviposition sites in response to predators likely influences adult populations and community structure. In the case of C. longiareolata, a model suggests that this behavior, compared to nonrandom oviposition, results in a larger adult population. Nonrandom selection of oviposition sites in response to risk of predation also indicates that experiments that set up predator and nonpredator plots and then compare the abundance of prey immatures are overestimating the predator’s effect on the prey population.

Introduction

Numerous studies over the past couple of decades have revealed a great diversity of induced responses by prey to risk of predation (see Whitman and Blaustein, this volume). The term “phenotypic plasticity” generally brings to mind developmental plasticity—e.g., altered growth rates (Peacor and Werner 2004), morphology (Trembath and Anholt 2001), life history (Blaustein 1997; Bernard 2004; Li 2002), or body color (Garcia et al. 2004). However, behavior, which is essentially an expressed phenotype of a genotype as a function of the environment, can also be considered a type of phenotypic plasticity (DeWitt and Scheiner 2004; Sih 2004). According to this definition, behaviors such as altered foraging (e.g., Kotler 1984; Brown and Kotler 2004) or altered oviposition site selection (Blaustein 1999; Resetarits 2005) in response to environmental conditions such as predation risk are examples of phenotypic plasticity. In general, behavioral plasticity allows a more rapid response and is generally less costly than induced morphological responses (e.g., Teplitsky et al. 2005). Moreover, behaviors are more easily reversible. Behavioral Plasticity to Risk of Predation ! '

That gravid females could detect risk of predation and choose a site for oviposition based on risk of predation was rarely examined in the literature several decades ago. This has been explored considerably more recently and there is a quickly growing body of literature that this behavioral plasticity is far from rare. A number of examples have been demonstrated for terrestrial insects (see Whitman and Blaustein, this volume). But this behavioral phenotypic plasticity is apparently common and particularly strong in pond and pool habitats (Blaustein 1999, Resetarits 2005). In this chapter, we first consider predator and prey characteristics in which evolution of this behavior is more likely to evolve. We then review a specific case of this behavioral phenotypic plasticity—oviposition habitat selection by a mosquito in response to risk of predation to its progeny.

What Factors Favor the Evolution of Oviposition Plasticity in Prey?

A species may evolve in two ways to avoid ovipositing where predators are prevalent. There may be evolutionary responses to predictors of predation risk without detecting the predator itself. For example, larger and more permanent pools are more likely to have higher predator densities (Spencer et al. 1999, Wilcox 2001, Chase and Knight 2003) and the ovipositing female may cue in on the size of the pool without being able to detect the predator itself. A second way is where detection of the predator itself induces a behavioral oviposition response. Not all species respond in this way to their predators. In fact, probably most do not (Blaustein et al. 2004). Certain predator-prey properties that likely increase the probability that oviposition habitat selection will evolve are outlined by Blaustein (1999) and Blaustein et al. (2004) and are expanded here: (1) A gravid female lays all her eggs in a single patch—i.e., she cannot spread the risk spatially. For example, the green toad, Bufo viridis, appears incapable of dividing its clutch and thus lays all its eggs in a single clutch while the tree frog Hyla savignyi may oviposit in several water bodies on the same night (Hill and Blaustein, unpublished data). Likewise, some mosquito species lay their entire clutch in a single egg boat whereas other mosquitoes may spread their eggs across several water bodies (Colton et al. 2003). A female that spreads her progeny across a number of sites is (by chance) likely to deposit eggs in both low- and high-quality habitats, and thus is likely to have at least some offspring survive. For the female that places all her eggs in a single site, site discrimination is more crucial to her fitness. !  Phenotypic Plasticity of Insects

(2) A female has few lifetime reproductive events (cannot spread risk temporally). For example, some salamanders may live > 20 years, having at least one clutch per year (Warburg 1994). If a long-lived salamander deposits all of her progeny in a bad site during some years, it likely still has other opportunities. (3) High predator-induced mortality on immatures. In resource-limited habitats, moderate predation rates may even be beneficial by reducing intraspecific competition (e.g. Wilbur 1997), so vulnerability needs to be high for selective pressure favoring oviposition habitat selection. We would predict then that there would not be strong selection pressure for evolving oviposition habitat selection for prey species that have evolved successful ways of evading the predator when they co- occur at the same habitat. (4) The female has multiple sites from which to choose to oviposit and there is predator heterogeneity among patches. If suitable breeding patches are generally sufficiently distant, rare, or homogeneous, females may have evolved to oviposit into the first patch they encounter, without assessing patch quality. Otherwise, a female should search for a high quality site, though balancing costs of continued searching. (5) Predator abundance in a given site at time of oviposition predicts local predator abundance during subsequent larval development. In many systems, this is not the case. For example, an might oviposit on a leaf devoid of its predators or devoid of predator-released kairomones (Nakashima et al. 2004). But if the predator is mobile, then the likelihood of future risk of predation may not be sufficiently different on this leaf than a leaf that presently has a predator. On the other hand, many predators of discrete aquatic habitats or parasitoid larvae already in a host cannot move from patch to patch. In these cases, the present distribution of predators among sites at the time a female is searching for an oviposition site should be a good predictor of future predation risk for her offspring. (6) Immigration of prey individuals from geographic areas devoid of predators into areas having these predators is “negligible.” If the range of a prey species extends beyond that of the predator range and there is sufficient immigration from the predator-free zone into the predator zone, this could flood out the natural selection for oviposition habitat selection. However, prey outside the zone of a particular predator species may also be cueing in on other predator species possessing the same cues. If the specific cue is the same for multiple predator species, Behavioral Plasticity to Risk of Predation !

one might expect a response to predator “A” even if there are many prey individuals outside the predator “A” region dispersing into it. (7) The predator should be sufficiently common. If predators are rare, there will not be strong selection to detect and avoid this predator. Like number 6, this is not the case if the prey does not detect a specific predator but can use the same cue to detect many predator species.

Why is a Likely Candidate to Evolve Oviposition Habitat Selection in Response to Risk of Predation

The mosquito Culiseta longiareolata is found throughout the Middle East, Southern Mediterranean, and Africa, where it is ubiquitous in small lentic aquatic habitats (van Pletzen and van der Linde 1981, Ward and Blaustein 1994). This species fits the characteristics suggested above favoring the evolution of predator-induced plasticity in oviposition: • All eggs are laid in a single patch. Like all other congeners, it lays all eggs from each reproductive effort as a single clutch in a single pool (with rare exception, the laboratory: van Pletzen and van der Linde 1981). The eggs are deposited as an “egg raft” that floats on the water surface (Fig. 1a). • A female has few lifetime opportunities to reproduce. After oviposition, a new blood meal, taken from a bird, is needed to develop a new egg batch. The period between blood acquisition and egg maturation varies from 4 -18 days in the laboratory (van Pletzen and van der Linde 1981). There are no published survival studies on adults of this species, but mosquito adults in general experience quite high mortality (~20 percent per day; Service 1993). Assuming similar adult mortality rates, most individuals that do succeed to lay a single batch will not live long enough to lay a second batch. Therefore, if habitat quality is highly variable, then where the female places her egg batch is crucial to her fitness. • Choice of oviposition patches is generally available with predator heterogeneity among patches. Temporary pools in this region are often found in clusters along wadi bottoms and rock outcrops (Ward and Blaustein 1994, Spencer et al. 2002a) and are close enough that mosquitoes can visit a number of pools in a single night. Among these pools, predator densities vary greatly (Ward and Blaustein 1994, Blaustein et al. 1995, Spencer et al. 1999). • High predator mortality on immatures. When vulnerability of C. longiareolata larvae was compared to other aquatic prey including C M Y K

! Phenotypic Plasticity of Insects nymph

larvae do not distance not do larvae imperator Anax

Culiseta ; (c);

Notonecta maculata Notonecta C K M

(b) (d) Y Y M K C , and in fact, attempt to graze off the exoskeleton of this predator; (d) (d) predator; this of exoskeleton the off graze to attempt fact, in and ,

Anax imperator Anax egg raft (photo credit: D. Arav); (b) The backswimmer, The (b) Arav); D. credit: (photo raft egg larva.

Culiseta Culiseta longiareolata Culiseta

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(a) (a)

Fig. 1 Fig. themselves from the dragonfly predator predator dragonfly the from themselves consuming a consuming

K Y M C Behavioral Plasticity to Risk of Predation ! !

larvae of other mosquito species, C. longiareolata was always most vulnerable among species tested on many predator species (Blaustein and Margalit 1994a, Blaustein 1998, Eitam et al. 2002, Blaustein, unpubl. data). They are particularly vulnerable to notonectids (Fig. 1b) because both predator and prey are generally found in open, and not vegetated, habitats. Larvae of C. longiareolata do not shift to safer habitats when predators are present (Arav 2006). Figure 1c-d illustrates the lack of predator avoidance. The larvae do not distance themselves from predators such as nymphs of the dragonfly Anax imperator, and in fact even attempt to graze off the predator exoskeleton, making themselves easy prey. • Current among-pool predator distribution predicts future predator distribution. Common predators of C. longiareolata include odonates, notonectids and urodeles. Adults of odonates and most urodeles are not predators of aquatic prey. They deposit their progeny in the water and with the exceptions of flash floods along wadi bottoms that may redistribute the larval predators among pools, they are restricted to the pool in which they were deposited until they metamorphose. Hemipteran (e.g., , Fig. 1b) and coleopteran adults can from pool to pool, and many of these adults may be predators of C. longiareolata, but the predatory nymphs, which are much more abundant than the adults, are restricted to the pool in which their egg was deposited. Thus, if C. longiareolata, and other temporary pool dipterans, are able to assess among-pool distributions of aquatic predators, this distribution is a fairly good predictor of risk of predation during the mosquito’s larval period. • Some predators are abundant and ubiquitous across a wide radius from where we have conducted oviposition studies. For example, our studies are conducted at various places in Israel. The backswimmer Notonecta maculata is distributed hundreds to thousands of kilometers in each direction. Therefore, it is very unlikely that Culiseta females would have immigrated into our study site areas from areas not containing the predator. Despite the high vulnerability of this mosquito to many predators, C. longiareolata is the, or one of the, most abundant macroinvertebrate species inhabiting temporary pools in the region. This may be explained in part because these mosquitoes are abundant and ubiquitous early in the rainy season before most predators become abundant and disperse to a large fraction of the pools (Ward and Blaustein 1994). Another reason may be ! " Phenotypic Plasticity of Insects because predator and prey have different preferences for pools with respect to different pool characteristics, or at least the mosquito will colonize some types of pools that the predators will not colonize. For example, backswimmers and other predators are generally more abundant in larger pools (e.g. Wilcox 2001). While Culiseta oviposits more in intermediate sized pools than smaller ones (Blaustein et al. 2004, Arav 2006), the smaller pools may still provide predator-free space. Lastly, C. longiareolata may be so abundant because the females can assess predation risk to their progeny and oviposit accordingly.

Experimental Venue and Procedure for Oviposition Habitat Selection

We have conducted numerous studies on C. longiareolata oviposition behavior testing a number of hypotheses using a diversity of experimental designs and conditions. We have conducted experiments in different seasons and geographical areas, both in natural rock pools (Fig. 2a) and artificial mesocosms (Fig. 2b) with strikingly similar results (Blaustein et al. 2004). In some of our experiments, we have compared control (non-predator) pools versus ones having unconstrained predators. Females oviposit at night. We then count number of egg rafts on the water surface the following morning. If there are significantly fewer egg rafts in predator pools, this could indicate oviposition habitat selection in response to risk of predation. However, fewer egg rafts in predator pools does not necessarily demonstrate oviposition habitat selection. There could be fewer egg rafts because the predator has consumed females that alighted on the water surface to oviposit, or because the predator could have consumed or disrupted the egg rafts (Chesson 1984). When we cage predators (Fig. 2b), differences in egg raft numbers can only be attributed to differential oviposition responses of the mosquito females to the caged predators. When we compare predator- conditioned water without the predator to control water, oviposition differences can only be attributed to a chemical cue released by the predator.

Does Culiseta longiareolata Avoid Aquatic Predators When Ovipositing?: Experimental Evidence We have assessed oviposition avoidance by C. longiareolata to a number of predators (Table 1). When comparing pools with unconstrained predators to control pools (no predators), egg raft abundance is not different for some predators (Triturus vitattus [newt] and Lestes parvidens [damselfly]) but lower for most (Table 1). Assuming predator discrimination by prey at fine C M Y K

Behavioral Plasticity to Risk of Predation ! #

A (d)

B C K M Y Y M K C

Fig. 2 Experimental venues to test for oviposition habitat selection by mosquito females in response to risk of predation: (a) natural rock pool (photo credit: O. Segev); (b) artificial plastic pool with cage for predator.

taxonomic resolution, it is not surprising that neither T. vitattus nor L. parvidens influence oviposition by Culiseta. Both are presently rare. T. vitattus used to be more common but neither this species nor L. parvidens were likely found in a high proportion of pools potentially available to C. longiareolata.

When comparing egg raft abundance in nonpredator pools versus pools

K Y M C ! $ Phenotypic Plasticity of Insects w against w 05; — = not checked. not = — 05; Hill et al. unpublished al. et Hill unpubl. Blaustein, Reference and Arav 2004; al. et Blaustein 2006 Blaustein

Predator water only water Predator —-—-unpubl. al. et Blaustein 2002 al. et Eitam in response to various predators and various predator various and predators various to response in

Caged predator Caged —-No —-reduction NS —- —-—-—-No2004 Silberbush unpubl. —- al. et Eitam 1999; al. et Stav —- —-unpubl. Blaustein, unpubl. Blaustein, unpubl. Blaustein, and Eitam

Egg Raft reduction Raft Egg

Culiseta longiareolata Culiseta YesYesYes YesYes Yes Yes Yes Yes Yes Yes Yes Yes Ubiquitous Rare Ubiquitous distribution Limited not but Ubiquitous densities high Ubiquitous Rare?Ubiquitous Ubiquitous distribution Limited distribution No Limited No No No No —- 2000 al. et Stav sp. ? —-reduction NS —-unpubl. al. et Hill

Predator Species Predator maculata Notonecta predator Free Distribution Predator glauca Notonecta sardea Anisops debilis Anisops Sigara imperator Anax fonscolumbi Sympetrum parvidens Lestes arteriosa Trithemis chrysostigma Orthetrum salamandra Salamandra vitattus Triturus Experimental evidence for oviposition habitat selection by selection habitat oviposition for evidence Experimental conditions (unconstrained predator, caged predator, and predator-conditioned water only). Predator treatments are compared belo compared are treatments Predator p=0. only). at water significant predator-conditioned statistically and not NS= predator, caged treatment; predator, predator the in (unconstrained rafts conditions egg fewer statistically = Yes controls. non-predator larvae. or adults were hemipterans that except groups taxonomic all for used were stages Larval : Notonectidae Hemiptera: Hemiptera: Notonectidae Hemiptera: Notonectidae Hemiptera: Corixidae Hemiptera: Taxon Notonectidae Hemiptera: Aeshnidae Anisoptera: Anisoptera: Libellulidae Anisoptera: Lestidae Zygoptera: Libellulidae Anisoptera: Salamandridae Urodela: Salamandridae Urodela: Table 1 Table Anisoptera: Libellulidae Anisoptera: Behavioral Plasticity to Risk of Predation ! % containing odonate nymphs or fire salamander (Salamandra salamandra) larvae, egg raft abundance is much higher in nonpredator pools. In one documented case, a small fraction of reduced egg rafts in unconstrained predator pools can be attributed to egg raft predation or disruption (Anax imperator: Stav et al. 1999). In another predator (Salamandra salamandra; Blaustein, unpublished), most or all of the observed reductions can be attributed to egg raft predation or disruption. Like the newt, the fire salamander would be considered a weak natural selection agent for oviposition habitat selection as only a small proportion of the landscape used by Culiseta is a salamander-inhabited region. Some odonate species like A. imperator might not have high predation pressure on Culiseta even though Culiseta has been shown to be highly vulnerable to predation in an artificial pool experiment (Stav et al. 2000) because Anax prefers permanent to semi-permanent pools with macrophytes, and is found within the vegetation zone inside a pool. By contrast, Culiseta oviposits in pools with open areas and the larvae are found almost exclusively in the open areas (Blaustein and Margalit 1995). Of the four notonectid species that we tested—Notonecta maculata, N. glauca, Anisops sardea and A. debilis—only N. maculata is widespread in and around Israel. However, for all four notonectid species, Culiseta longiareolata respond by avoiding caged-predator pools (e.g., Blaustein et al. 2004, Eitam et al. 2002, Silberbush 2004, Blaustein, unpubl. data). We have thus far tested C. longiareolata oviposition to predator-conditioned water only of N. maculata only and the mosquito avoids the predator-conditioned water (Fig. 3). This indicates that the cue is one or more predator-released kairomones and that the kairomone(s) is/are found generally in all notonectids. The chemical characterization of the kairomone(s) remains unknown but we do know something about the properties. It does not appear to be a chemical released by consumed conspecific prey as has been demonstrated in other prey species and other predation risk avoidance behaviors (Wisenden and Millard 2001); the oviposition avoidance occurs regardless of whether or not the predator has been fed mosquito larvae (Blaustein, unpublished). A density of one predator per 30 liters has produced the oviposition avoidance response and the necessary concentration of predators may be even lower (Eitam and Blaustein 2004). The kairomone has been shown to actively repel oviposition by Culiseta for 7-8 days in a field trial (Fig. 3; Blaustein et al. 2004). Both boiling the kairomone for 20 minutes or evaporating and then reconstituting the predator-conditioned water reduces the proportion of individuals that avoid predator-conditioned water, but does not eliminate the avoidance response entirely (Eitam et al., unpublished data). These ! & Phenotypic Plasticity of Insects

1.0

rprino g at in rafts egg of Proportion

predator-fr

0.8

40

epools ee 30 0.6 20

10

Number of egg rafts 0 0.4 1 2 3 4 5 6 7 8 9 10 11 12 Phase I Phase III Phase II : Days without N. maculata Fig. 3 Oviposition response (percent of total and number) of Culiseta longiareolata when offered control pools (no predator) vs. pools containing the predator Notonecta maculata. In the first period, Notonecta is introduced in a cage each day but only during the daylight hours. Oviposition by Culiseta occurs at night. In the second period, the pools remain Notonecta-free. The x-axis is the number of days since Notonecta was last present in the pool. In the third period, Notonecta was returned to the pools. From Blaustein et al. (2004), with kind permission of Springer Science and Business Media. results suggest that a predator-released kairomone is not highly volatile. However, when mosquitoes are prevented from touching the predator- conditioned water, it still reduces the proportion avoiding the predator- conditioned water (Silberbush, unpublished data). These studies taken together suggest that there may be more than one kairomone—one fairly volatile and a second not very volatile.

Other Notonecta-Prey Combinations

We have assessed the oviposition response of other dipteran species to notonectids. These dipteran species, meet all the prey characteristics suggested earlier for oviposition habitat selection except that they range in vulnerability to the predator, and oviposition habitat selection is predicted based on vulnerability. The most vulnerable (Culiseta) and second most (Culex laticinctus) show oviposition avoidance while the less vulnerable, Culex pipiens, Chironomus riparius and Forcipomya sp. do not avoid Behavioral Plasticity to Risk of Predation ! ' ovipositing in the presence of backswimmers (Eitam et al. 2002, Kiflawi et al. 2003a, Blaustein et al. 2004, Arav and Blaustein 2006).

Why do Some Culiseta longiareolata Females Oviposit in Predator Pools?

C. longiareolata females cannot only detect predators but can also detect food levels for their larvae (Blaustein and Kotler 1993), interspecific competitors (Blaustein and Kotler 1993), and may also be able to detect the density of conspecific larvae irrespective of the resources (Kiflawi et al. 2003a). This being the case, is it possible that Culiseta can operate according to the ideal- free distribution in distributing their egg rafts among pools? As illustrated in Fig. 4, in the absence of predators, C. longiareolata progeny has increasing risk with increasing conspecific density due to intraspecific competition and cannibalism (Kiflawi et al. 2003a). Thus we would expect, and found, that females prefer to oviposit under conditions of point 1 (low conspecific density, no predator) than point 2 (high conspecific density, no predator) (Table 2). Likewise, we would expect, and found, that C. longiareolata females preferentially oviposit in pools with low conspecific density (point 1) over pools with Notonecta (point 2). When given two poor choices (points 2 and 3), Balancing risks: Experimental Design Notonecta pools (predation byNotonecta ) 3 2

Pools without Notonecta (Cannibalism and intra- specific competition)

Culiseta

Risk to1 progeny LarvalCuliseta density Fig. 4 Graphical representation of risk to Culiseta larvae given the absence and presence of Notonecta and a range of Culiseta larval densities. Point 1 is the condition of the absence or low density of Culiseta larvae in the absence of Notonecta. Point 2 is high density of Culiseta larvae in the absence of Notonecta. Point 3 is the presence of Notonecta with no or low densities of Culiseta larvae. !! Phenotypic Plasticity of Insects

Table 2 Oviposition by Culiseta longiareolata under various paired conditions in an outdoor artificial pool experiment. The three treatments that were compared were low Culiseta density with no predator, high Culiseta density with no predator, and the predator Notonecta. The second column represents the total number of Culiseta egg rafts laid for that paired comparison. Binomial tests are one tailed. Last column is the total number of egg rafts laid in the experimental array per night.

Comparison Ratio P(binom test) No. nights Egg rafts per night Low Culiseta: Notonecta 31:4 (89%) < 0.0001 6 5.8 Low Culiseta: High Culiseta 50:8 (86%) < 0.0001 7 8.2 High Culiseta: Notonecta 7:13 (35%) 0.132 8 2.5 the ratio of egg rafts oviposited in Notonecta pools increases dramatically which appears to support the ideal-free distribution hypothesis. However, this is open to interpretation. Given these two poor choices, the number compared to the low Culiseta larval density: Notonecta pairing, the number ovipositing total number of egg rafts deposited also drops instead of more evenly ovipositing all egg rafts to be expected at that night. We have consistently found that when C. longiareolata females are given an experimental array of half nonpredator pools and half N. maculata pools, and all other factors are kept equal including conspecific density, a consistently small fraction of approximately 5-15 percent of the females still oviposit in the predator pools (Blaustein et al. 1995, Blaustein 1998, Spencer et al. 2002b, Kiflawi et al. 2003a, Blaustein, unpublished data). Why? Two plausible explanations are as follows: (1) genetic differences: a fraction of the population may not possess the ability to detect the predator and/or the larvae of females that oviposit in predator pools are less vulnerable to predation than the larvae arising from females that avoid predator pools; (2) searching for a “good” pool is limited and after a certain period of time or a certain number of pools assessed by the female, the small fraction of females that encounter only Notonecta pools oviposit in a Notonecta pool. Laboratory predation studies have shown that larvae arising from egg rafts deposited in predator pools are not less vulnerable than those arising from egg rafts deposited in nonpredator pools (Arav 2006). Unfortunately, our lab has thus far failed to maintain a sustained colony to address the other questions by observation and experimentation. However, to gain insight as to which of these was the more likely explanation, we ran an artificial pool field experiment in which, on different nights, we changed the ratio of control pools to Notonecta pools. On different nights, nonpredator:predator pool ratios were 3:9, 9:9, and 9:3 (Kiflawi et al. 2003 and unpublished data). We Behavioral Plasticity to Risk of Predation !! found an increase in the proportion of females using predator pools as the proportion of predator pool was increased (Fig. 5) which more strongly supports the second hypothesis.

Perspective

Behavioral responses to the environment are phenotypically plastic responses. The oviposition response of the mosquito Culiseta longiareolata to some of its predators provides one example. Oviposition habitat selection as a phenotypically plastic response to predation was, until recently, largely ignored as an important factor in explaining species distributions and community structure. Though examples of this behavior exist in terrestrial systems (e.g. Agarwala et al. 2003, Whitman and Blaustein, this volume), much of the literature documenting this behavior suggests that the oviposition avoidance is strongest and most prevalent for amphibians (e.g. Murphy 2003, Binckley and Resetarits 2003) and insects (e.g., Resetarits 2001, Blaustein et al. 2004) utilizing pool or pond habitats. The reason for this seems to be due to the predator-prey characteristics outlined in this chapter including predictability of future risk of predation when progeny

100

80

60

40 Percent of Egg Rafts Oviposited in Control Pools 25 50 75 Percent of Pools without Notonecta Fig. 5 The relationship between the percent of egg rafts laid in nonpredator pools with the changing ratio of nonpredator to Notonecta pools. !! Phenotypic Plasticity of Insects hatch. This behavior also has consequences for populations. In the case of C. longiareolata and backswimmers, a linear stage-structured model suggests that this behavior, compared to random oviposition, results in a larger adult mosquito population (Spencer et al. 2002b). Oviposition habitat selection in response to risk of predation also has consequences for communities (e.g. Resetarits 2005). In the specific system reported here, C. longiareolata larvae themselves are influential as competitors and predators, so how these larvae are distributed among pools should cause differences in and algal community structure (Blaustein et al. 1995, Blaustein and Margalit 1994b, 1996). This behavior also has consequences for how experiments should be designed to assess the true effect of the predator on prey populations (Blaustein 1999, Spencer et al. 2002b).

Acknowledgements

We thank collaborators on this specific research problem for their valuable discussion, namely Derah Arav, Jonathan Blaustein, Jonathan Chase, Joel E. Cohen, Avi Eitam, Naomi Hill, Moshe Kiflawi, Burt P. Kotler, Marc Mangel, Joel Margalit, Shai Markman, Jerrold Meinwald, Alon Silberbush, Mathew Spencer, Gil Stav and James Vonesh. The work was funded by Israel Science Foundation Grant 699-02 awarded to L. Blaustein.

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