Mosquito females quantify risk of predation to their progeny when selecting an oviposition site

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1 Functional Ecology 2011, 25, doi: /j x Mosquito females quantify risk of predation to their progeny when selecting an oviposition site Alon Silberbush 1,2, * and Leon Blaustein 1 1 Community Ecology Laboratory, Institute of Evolution and Department of Evolutionary and Environmental Biology, Faculty of Natural Sciences, University of Haifa, Haifa 31905, Israel; and 2 Center for Biological Control, Department of Life Sciences, Ben-Gurion University of the Negev, PO Box 653, Beer-Sheva 84105, Israel Summary 1. Numerous studies demonstrate that given the dichotomous choice of predator-free habitats vs. habitats containing predators, prey choose predator-free habitats when foraging for food or ovipositing. However, predation risk is rarely dichotomous in nature, and very few studies have assessed whether prey can quantify predation risk when selecting habitats. 2. It was shown previously that gravid females of the mosquito Culiseta longiareolata, when simultaneously offered pools with multiple choices of densities of the predator Notonecta maculata, oviposited more in the zero-predator density pools but oviposited less frequently and similarly across all other densities. This flat oviposition response across various Notonecta densities was in contrast to a decrease in mosquito immature survival with increasing Notonecta density. Here, we reconsider this question with the same species but with a different experimental design; rather than experimentally assessing multiple predator densities simultaneously, we offered only pairwise choices on any given night. Specifically, we offered ovipositing Culiseta females all pairwise combinations from no, low and high predation risk (0, 1 and 4 Notonecta per pool). 3. Overall oviposition was lower when mosquitoes could only choose pools containing Notonecta (1 or 4). In all pairwise comparisons, more females chose pools of lesser predation risk. Thus, gravid females of this species, and probably many other species, can quantify predation risk, and not only assess presence or absence of predation risk, when choosing oviposition sites. 4. This is the first demonstration that an ovipositing female of any species can quantify risk of predation. We suggest, based on statistical and behavioural factors, that pairwise comparisons, and not simultaneous multiple-choice experiments, are the experimental design of choice to adequately test this ability. Key-words: Culiseta longiareolata, Experimental design, Notonecta maculata, oviposition habitat selection, pairwise test, predation gradient, predation risk Introduction *Correspondence author. alonsil@gmail.com Prey responses to predation risk are diverse and can include developmental, morphological and behavioural responses (Stephens & Krebs 1986; Allan, Flecker & McClintock 1987; Lima & Dill 1990; Lima 1998; Brown & Kotler 2004; Whitman & Blaustein 2009). Generally, predation risk is a continuous variable across a landscape, and increasing risk of predation can be negatively correlated to fitness (Eitam & Blaustein 2004; Thomson et al. 2006). Predictably, when a prey species is confined to a specific site, increasing predator or predator-released kairomone concentrations cause an increasing effect on prey behaviour (Zhao, Ferrari & Chivers 2006; Ferrari, Messier & Chivers 2007; Kesavaraju, Damal & Juliano 2007), morphology (Benard 2004; Relyea 2004; Teplitsky, Ple net & Joly 2005) or other various measures of prey performance (Sih 1987; Wilbur 1987; Abrams & Rowe 1996; Beachy 1997). Similarly, when a prey species is not confined to a single patch or habitat, but selects its habitat, all else being equal, a habitat without predation risk should be preferable to one of low predation risk, and one of low predation risk should be preferable to one of high predation risk (but see Rieger, Binckley & Resetarits 2004). Yet, assessments of the ability of prey to quantify risk of predation when selecting a habitat are exceptionally rare (Abramsky, Rosenzweig & Subach 1997). Similar to foraging for food (Morris, Clark & Boyd 2008), oviposition habitat selection can be influenced by predation Ó 2011 The Authors. Functional Ecology Ó 2011 British Ecological Society

2 1092 A. Silberbush & L. Blaustein risk. In aquatic systems, a growing body of literature is demonstrating that gravid females of many aquatic insect and amphibian species avoid ovipositing in sites containing predators of their progeny (aquatic insects, e.g. Chesson 1984; Petranka & Fakhoury 1991; Blaustein, Kotler & Ward 1995; Resetarits 2001; Brodin, Johansson & Bergsten 2006; Munga et al. 2006; amphibians, e.g. Kats & Sih 1992; Holomuzki 1995; Binckley & Resetarits 2002; Orizaola & Braña 2003). Mosquito oviposition habitat selection in response to predation risk has received considerable attention in recent years, and a meta-analysis shows this behaviour to be common (Vonesh & Blaustein 2010). Several studies have assessed oviposition responses of females across a range of predator densities or concentrations of predator-conditioned water: Culiseta longiareolata and Culex laticinctus mosquitoes in response to the predatory backswimmer, Notonecta maculata (Eitam & Blaustein 2004); Hyla femoralis tree frogs in response to the predatory fish, Umbra pygmaea (Rieger, Binckley & Resetarits 2004); and Hyla chrysoscelis and Hyla squirella tree frogs and Tropisternus lateralis beetles in response to the predatory fish Enneacanthus obesus (Binckley & Resetarits 2008). In each of these experiments, ovipositing females could choose among all predator densities simultaneously. In each case, there was a significant nonlinear response: there was drop in oviposition at a low predator density without a further reduction in oviposition as predator density increased. Yet, larval performance in the form of survival to metamorphosis, which was measured across these predator densities in two of these three studies, increasingly declined with predator density (Eitam & Blaustein 2004; Rieger, Binckley & Resetarits 2004). We suggest that such tests that provide prey females simultaneously with a range of choices in predator densities, including no predators, cannot clearly test for the ability to quantify predation risk. This is because most females, in the absence of high prey densities causing an ideal-free distribution effect (Fretwell & Lucas 1970), will simply pick the pools with no predators. Instead, pairwise tests of two concentrations at a time, and particularly a pairwise choice of a low and high predator density, should more clearly discriminate whether the female can quantify predation. The mosquito, Culiseta longiareolata (Fig. 1), has been shown in numerous experiments to avoid ovipositing in pools containing the predatory backswimmer, Notonecta maculata (e.g. Blaustein, Kotler & Ward 1995; Spencer, Blaustein & Cohen 2002; Kiflawi, Blaustein & Mangel 2003a,b). Here, by using various pairwise comparisons of predator densities in an outdoor mesocosm experiment, we assess whether the female can quantify risk of predation to her progeny, when making oviposition habitat selection decisions. We demonstrate that while a previous study simultaneously testing multiple N. maculata densities failed to demonstrate such an effect by gravid C. longiareolata females (Eitam & Blaustein 2004), the current pairwise tests clearly showed that this mosquito can indeed quantify risk of predation. We suggest that the current pairwise approach provides a much stronger test of the ability of mosquitoes to quantify risk. Fig. 1. An adult female Culiseta longiareolata. Photo credit: Ido Tsurim. Materials and methods STUDY SYSTEM The mosquito, Culiseta longiareolata Macquart (Becker et al. 2003), and the predatory backswimmer, Notonecta maculata Fabricius (Baena & Vázquez 1986; Larsen & Blaustein 2005), are common inhabitants of pools in the Mediterranean, Middle East and North Africa. C. longiareolata females, whose larvae are highly vulnerable to predation by N. maculata (Blaustein 1998), can chemically detect this predator in the water and avoid ovipositing in pools containing this predator (e.g. Blaustein et al. 2004; Silberbush & Blaustein 2008; Silberbush et al. 2010). This mosquito clusters its reproductive batch into a single egg raft. Most oviposition at our study site occurs between late March and early June. EXPERIMENTAL DESIGN An artificial pool experiment was conducted at the Hai-Bar Carmel Nature Reserve Center on Mount Carmel, Israel (32 44 N E; elevation: 363 m ASL). We used 15 artificial pools (plastic green pools: cm) set in a 3-column 5-row array with c. 1-m distance between adjacent pools. This array was >100 m from any other natural pool. On 21 March 2006, we added to each pool 15 L of tap water and one gram of sera Bio-Granulat fish pellets (25.9% protein) to encourage mosquito oviposition (Blaustein & Kotler 1993). Two days after filling the pools, 0, 1 or 4 adult N. maculata per pool were randomly assigned to the three pools of each row, creating a randomized block design with five replicate pools per N. maculata density. Eitam & Blaustein (2004) found that the equivalent density of one N. maculata per 15 L caused an intermediate (c. 65%) reduction in emergence success by C. longiareolata and the equivalent of two N. maculata per 15 L caused an almost complete elimination of C. longiareolata emergence. Thus, in the current experiment, 0, 1 and 4 N. maculata densities represented no, intermediate and very high risk of mortality by predation to C. longiareolata progeny. Adult N. maculata were collected from a nearby natural pool. Predators were caged in 2-L plastic bottles half submerged in each pool with window screen-covered openings in the sides to allow an exchange of water and air. We checked the pools daily for dead N. maculata, which were replaced immediately upon detection. All N. maculata were removed and replaced with new individuals every 7 days. We observed no natural colonization of N. maculata or any other predators into the pools during the course of the experiment. On any night, one of the three predator densities was covered, leaving wild ovipositing mosquito females with pairwise choices. The

3 Quantifying predation risk during oviposition 1093 order of the pairwise comparisons was randomly chosen until the triplet of all combinations was used. Logistical problems sometimes dictated the sequence of the triplet of combinations and continued to approximate a random sequence. The pools were checked daily for egg rafts, which were removed and identified to species. Only C. longiareolata mosquito egg rafts were found in sufficient numbers to assess with sufficient statistical power. Oviposition counts were made during 59 of 67 days of the experimental period (28 March 3 June 2006) yielding 19, 20 and 20 nights for the 0 vs. 1, 0 vs. 4 and 1 vs. 4 predator density combinations, respectively. Because overall oviposition rates were not high, and because we removed egg rafts daily, we likely avoided or reduced ideal-free distribution issues, i.e. that females ovipositing later in the night might not choose the otherwise best option because of high densities of larvae (Kiflawi, Blaustein & Mangel 2003b) or egg pheromones (Clements 1992) from previous nights. STATISTICAL ANALYSIS We statistically addressed two questions: Fig. 2. Pairwise comparisons for oviposition by Culiseta longiareolata (mean number of egg rafts per pool per night) for each uncovered pair of treatments. All comparisons were significantly different (see text for statistical tests). The vertical lines in the x-axis separate the different paired comparisons. Error bars are one standard error. 1. When given two choices of predation risk, are ovipositing C. longiareolata able to quantify risk? To statistically assess these pairwise comparisons (0 vs. 4 N. maculata per pool, 0 vs. 1, 1 vs. 4), we used t-tests (one-tailed given the apriorihypothesis that oviposition would always be greater in the paired treatment with fewer N. maculata). 2. Total combined oviposition rates: How do the three pairwise combinations (0 plus 1, 0 plus 4 and 1 plus 4) affect overall oviposition (number of egg rafts laid per night)? To assess whether overall oviposition differed for the three paired combinations, we combined the egg raft values for the pairwise comparison for each pair in a row, giving five values for each pairwise comparison, and then conducted an analysis of variance on the three groups (0 plus 1, 0 plus 4 and 1 plus 4). We used Tukey s HSD post hoc comparison test for detecting significant differences among paired treatments. Because the total numbers of nights for specific pairwise treatment combinations were not exactly the same (19 or 20 nights), we converted values to egg rafts per two pools per night for analyses. Also, because of low nightly oviposition rates (resulting in many zero counts on a given pool on a given night) and the absence of any treatment time effect, we report only on egg counts per pool across summed the entire experiment. To statistically assess both questions, we added 0.5 to all values and then square root transformed prior to analysis to homogenize among-treatment variance (following Yamamura 1999). Using this transformation, there were no violations of homogeneity of variance (for both Bartlett and Levene tests). regardless of which of the two other densities it was paired with, oviposition in pools of that density remained rather constant. The pairwise combinations strongly influenced overall oviposition rates (F 2,12 =4.82;P = 0.029; Fig. 3): oviposition rates were highest when mosquitoes had choices of 0 plus 1 N. maculata, intermediate when there were choices of 0 plus 4 N. maculata and lowest when the choices were 1 plus 4 N. maculata. The difference was only statistically significant for 0 plus 1 vs. 1 plus 4 (Tukey HSD Test). Discussion To our knowledge, this is the first study demonstrating the ability of ovipositing females of any species to quantify risk of predation when making oviposition habitat selection decisions. Our results show that a gravid female selects the pool with lowest predator density available. Previous attempts to assess oviposition choice across a predation gradient have been few (Eitam & Blaustein 2004; Rieger, Binckley & Resetarits 2004; Binckley & Resetarits 2008), and these limited Results A total of 227 C. longiareolata egg rafts were observed and collected over the course of the experiment. Results demonstrated that gravid C. longiareolata could quantify risk of predation (Fig. 2). In each of the three pairwise comparisons, more egg rafts were laid in the pools with the lower density of N. maculata [0 vs. 1: t(8 d.f.) = 2.42, P = 0.042; 0 vs. 4: t(8 d.f.) = 8.25; P < 0.001; 1 vs. 4: t(8 d.f.) = 2.67; P = 0.028]. The data also indicated that for a given N. maculata density, Fig. 3. Mean total oviposition in both treatments of uncovered pools. Error bars are one standard error.

4 1094 A. Silberbush & L. Blaustein number of studies assessed multiple predator densities, including predator-free pools, simultaneously. Two of these (Eitam & Blaustein 2004; Rieger, Binckley & Resetarits 2004) also measured risk to progeny across the predator densities. In both Rieger, Binckley & Resetarits (2004) (H. femoralis in response to a predator gradient of the predatory fish Umea pygmaea) and Eitam & Blaustein (2004) (C. longiareolata and C. laticinctus, in response to a N. maculata gradient), the ovipositing female selected zero densities preferentially with no significant differences between all other predator densities even though risk to progeny increased with increasing predator density. Our current study might, at first consideration, appear inconsistent with results of these two other studies. We suggest that an experimental design simultaneously assessing multiple predator densities is not optimal to address the question of whether ovipositing females can quantify predation risk for two reasons. First, there is a statistical power issue: because the great majority of females oviposited in predator-free pools, it clouds the possibility of detecting any significant differences between the other predator densities. Particularly in the case of Eitam & Blaustein (2004), for both mosquito species tested, there was no trend in oviposition whatsoever that might have suggested a relationship. It might be that a fraction of the population is genetically incapable of responding to the predator, and then they distribute their eggs randomly across all densities (Kiflawi, Blaustein & Mangel 2003a) where the fraction that can detect predators may all choose predator-free pools. A second issue involves the behaviour of the animal. A theory in the psychology literature (Loewenstein 1999) predicts that the need to make too many choices could result in numerous costs, such as time consumption, confusion and stress. These costs often result in making bad choices when faced with numerous options. The probability for making a bad choice increases if the consumer is trying to make the best choice rather than a satisfactory one (Loewenstein 1999; Schwartz 2004). Similarly, ovipositing mosquito females, faced with numerous options, may fail to demonstrate their ability to quantify. Such studies then, that consider simultaneously multiple predator densities, may provide information on the minimum predator density threshold that the ovipositing female can detect, but cannot necessary assess for the ability to quantify risk of predation. Pairwise tests have also been used to demonstrate that ovipositing seed beetles can respond to risk of competition in a quantitative manner (Messina & Renwick 1985). We found that the number of egg rafts laid in the experimental array on a given night was proportional to the number of predators regardless of the paired alternative, suggesting that the females were ovipositing in a probabilistic manner. This is consistent with the victim s isocline theory (Abramsky, Rosenzweig & Subach 1997) that predicts that when complete avoidance is impossible, prey will always forage for food in the sites containing lower predator densities. In nature, where there occurs a mosaic of pools with a wide range in predator densities, the predicted distribution of egg rafts across these pools might be the distribution found in Eitam & Blaustein (2004), i.e. that mosquitoes would discriminate only between presence and absence of the predator, and not differentiate between different predator densities, at least to the point where mosquito densities were below the idealfree distribution and would not impact the distribution. 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