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Oecologia (2010) 162:893–902 DOI 10.1007/s00442-010-1564-x BEHAVIORAL ECOLOGY - ORIGINAL PAPER DiVerential habitat use and antipredator response of juvenile roach (Rutilus rutilus) to olfactory and visual cues from multiple predators Charles W. Martin · F. Joel Fodrie · Kenneth L. Heck Jr. · Johanna Mattila Received: 16 June 2009 / Accepted: 6 January 2010 / Published online: 3 February 2010 © Springer-Verlag 2010 Abstract The indirect, behavioral eVects of predation and predator–predator interactions can signiWcantly alter the trophic ecology of many communities. In numerous instances, the strength of these eVects may be determined by the ability of prey to identify predation risk through predator-speciWc cues and respond accordingly to avoid capture. We exposed juvenile roach (Rutilus rutilus), a common forage Wsh in many brackish and freshwater environments, to vision and/or olfactory cues from two predators with diVerent hunting methods: northern pike (Esox lucius, an ambush predator) and European perch (Perca Xuviatilis, a roving predator). Our results demonstrated that responses of roach to perceived risk (as evidenced by their selection of structured or open-water habitats) were highly dependent on cue type and predator identity. For instance, roach responded to olfactory cues of pike by entering Communicated by Anssi Laurila. C. W. Martin (&) · K. L. Heck Jr. Dauphin Island Sea Lab, 101 Bienville Boulevard, Dauphin Island, AL 36528-0369, USA e-mail: [email protected] C. W. Martin · K. L. Heck Jr. University of South Alabama, 307 University Boulevard N, Mobile, AL 36688-0002, USA F. J. Fodrie Department of Marine Sciences, Institute of Marine Sciences, University of North Carolina at Chapel Hill, 3431 Arendell Street, Morehead City, NC 28557, USA J. Mattila Husö Biological Station, Åbo Akademi University, Tykistökatu 6, 20520 Turku, Finland open-water habitat, but entered structured habitat when presented with a vision cue of this predator. Opposite responses were elicited from roach for both olfactory and visual cues of perch. Interestingly, roach defaulted to selection of structured habitat when presented with vision + olfaction cues of either predator. Moreover, when presented individual cues of both predators together, roach responded by choosing open-water habitat. Upon being presented with vision + olfaction cues of both predators, however, roach strongly favored structured habitat. DiVerences in habitat selection of roach were likely in response to the alternative foraging strategies of the two predators, and suggest that prey species may not always use structured habitats as protection. This appears particularly true when a threat is perceived, but cannot immediately be located. These results provide insight to the complex and variable nature by which prey respond to various cues and predators, and oVer a mechanistic guide for how behaviorally mediated and predator–predator interactions act as structuring processes in aquatic systems. Keywords Antipredator behavior · Predator–prey interactions · Olfaction · Vision · Multiple predator eVects · Non-consumptive eVects Introduction The non-consumptive eVects of predation (also referred to as trait or behaviorally mediated indirect interactions) are increasingly recognized to be an important, yet understudied, component of predator–prey interactions and food-web dynamics (Dill et al. 2003; Grabowski 2004). Recent metaanalyses have indicated that the mere threat of predation can have impacts that are as strong, if not stronger, than 123 894 direct consumption (Dill et al. 2003; Werner and Peacor 2003; Pressier et al. 2005). For instance, indirect interactions that alter the foraging behavior of mid-trophic-level species can initiate trophic cascades (Trussell et al. 2002; Schmitz et al. 2004). A key element of these non-lethal predator–prey exchanges is the ability of prey to recognize and evade risk once a threat is perceived through visual, olfactory, mechanoreception, electroreception, or social cues. Thus, separating the behavioral responses of prey to various cue types should lead to a better understanding of the circumstances in which trait-mediated interactions will dominate trophic exchanges and regulate energy Xow through food webs. Although the roles of all antipredator sensory cues have been evaluated in aquatic systems [e.g., mechanoreception via lateral line sensitivity (Montgomery and MacDonald 1987) and social cues via schooling (Hager and Helfman 1991; Brown et al. 2009)], many experiments have focused on the role of vision (Mathis et al. 1993; Heithaus et al. 2002, 2006; Wirsing et al. 2007) and olfactory cues in mediating predator–prey exchanges (Smith 1992; Kats and Dill 1998; Chivers and Smith 1998; Brown 2003; Amo et al. 2004; Kusch et al. 2004; Ylönen et al. 2007). Within aquatic environments, we still know little about the relative roles of each in governing predator–prey interactions (Wahle 1992; Mathis and Vincent 2000; Hickman et al. 2004; Kim et al. 2009), even though it could be expected that prey rely heavily on olfaction within relatively turbid environments. In the future, eutrophication (Utne-Palm 2002; Engström-Öst and Mattila 2008) and the loss of sediment-stabilizing foundation species such as submerged aquatic vegetation (Waycott et al. 2009) should lead to increasingly turbid conditions. This may force prey to rely even more heavily on olfaction for guiding defensive responses to predator detection (Lehtiniemi et al. 2005). Therefore, data are needed to evaluate the relative eVects of vision and olfaction, which are recognized as the most important sensory cues used by prey within shallow-water environments (Mikheev et al. 2006), on the predator-avoidance responses of prey. Moreover, quantifying the magnitude and direction of prey responses elicited by these cues, both individually and in combination, has the potential to reveal new insights for predicting how food webs will respond to anthropogenic stressors aVecting water quality (sensu Lindquist and Bachmann 1982; Shivik 1998). Since omnivory is common in natural systems (Pimm and Lawton 1978), most species at lower and intermediate positions in food webs (i.e., forage Wsh in estuarine environments) not only receive multiple cues from single predators, but also simultaneous threat stimuli from multiple predator species. Therefore, prey must respond to an amalgam of risk cues. Where predator species diVer in foraging behaviors, there is growing interest in quantifying multiple 123 Oecologia (2010) 162:893–902 predator eVects on shared prey, especially relative to the impacts of predator species operating alone (Sih et al. 1998). In some cases, multiple predators can operate synergistically, resulting in enhanced risk for their shared prey (Fodrie et al. 2008). Nearly all reports of predator facilitation that result in enhanced risk for a shared prey are based on two elements: one predator alters the habitat selection of prey, and this makes prey highly vulnerable to attacks from another predator (Sih et al. 1998). In other scenarios, predators interfere with one another resulting in reduced risk for prey (Crowder et al. 1997). Often, this occurs if prey are capable of rapidly switching between predator-speciWc defense behaviors/mechanisms (Sih et al. 1998). Regardless of the outcome, the ability of prey to receive, process, and act upon multiple cues is put to a stern test in instances when there is more that one threatening predator species. Although tests of multiple predator eVects have thus far focused on prey mortality as the response variable, multiple predator eVects should be equally important determinants of non-consumptive eVects. To our knowledge, the speciWc cues used by prey in multiple predator scenarios and subsequent eVects on habitat selection have not been evaluated. To investigate cue-mediated predator–prey interactions, we designed an experiment to address the following questions: (1) what are the relative roles of olfactory and visual cues from two common predators on the habitat selection of a widespread prey species, and (2) do interspeciWc combinations of predator cues induce responses in prey habitat selection that could be predicted by averaging the responses of prey to each predator individually? Materials and methods Study organisms We explored cue-driven predator–prey interactions using commonly encountered species in brackish and freshwater habitats throughout Europe. Juvenile roach (Rutilus rutilus), a numerically dominant forage Wsh that inhabits both open-water and structured habitats [e.g., emergent reeds (Phragmites australis) as well as numerous species of submerged aquatic vegetation], were used as prey. While roach are known to school, especially under threat of predation (Christensen and Persson 1993; Eklöv and Persson 1995), we used individual roach in this experiment to tease apart their responses to various cue inputs as a starting point to understanding their behavior. We selected northern pike (Esox lucius) and European perch (Perca Xuviatilis), two of the most commonly encountered piscivores in this region (BonsdorV and Blomqvist 1993; Ådjers et al. 2006) as predators. These two species have diVerent foraging strategies: Oecologia (2010) 162:893–902 northern pike hide in vegetation and ambush prey (Savino and Stein 1989), while perch forage by continually roving among habitats (Eklöv and Persson 1995). Despite these divergent foraging strategies, pike and perch are both capable predators of roach and could be deWned by qualitatively similar interaction coeYcients. Furthermore, these predators are known to elicit strong antipredator responses in other species of prey (Christensen and Persson 1993; Mathis and Smith 1993; Mathis et al. 1993). Experimental design and procedures Our experiment was conducted during 14 August–7 September 2008 at Husö Biological Station in the Åland archipelago. We collected roach, pike, and perch by seining or dip netting in Husö Bay adjacent to Husö Biological Station, in the Åland archipelago (60°04’N, 20°48’E). Following collection, Wshes were held in 75-l holding tanks (654 cm long £ 29 cm wide £ 9.5 cm tall) until their use in experimental trials (each species in separate tanks). Holding tanks were devoid of structure and completely surrounded with plastic dividers to minimize Wsh stress. We exchanged water daily in holding tanks and provided aeration with a single airstone in each tank. Predators (pike and perch) were fed two roach (31.6 § 5 mm) each day until needed for experiments. Roach were always collected the day before their use in experimental trials and therefore not fed while in the holding tank. Individual prey were used once and then released in Husö Bay. Experimental trials were conducted within six 17-l experimental aquaria (33 cm long £ 24.5 cm wide £ 21 cm tall). In each aquarium, we placed artiWcial seagrass units (ASUs) over half of the bottom (16.5 cm long £ 24.5 cm wide £ 21 cm tall) to provide structured habitat. The other half of the aquarium remained unstructured, open-water habitat. ASUs were assembled by tying green ribbon to Vexar mesh to mimic the morphology of many common aquatic plants [e.g., eelgrass (Zostera marina)] at a density of approximately 1,000 shoots m¡2, a value within the range of typical eelgrass beds in the Baltic Sea (Baden and Boström 2001). During each experimental run, Wltered water (180 m) from Husö Bay was used to Wll each aquarium. Although predator olfactory cues could be present in the incoming water, we assumed these to be at trace levels and equally introduced among all experimental aquaria and holding tanks. Since chemical cues were involved in these experiments, we did not circulate water in aquaria during these trials, but did use an airstone to ensure the aquaria were well aerated. The airstone was placed in the ASU section of each aquarium to prevent the introduction of structure to the open half of the aquaria. A pilot study veriWed that prey were neither attracted nor deterred by the presence of the airstone. Between trials, experimental aquaria were 895 drained, rinsed thoroughly, and reWlled with Wltered water to eliminate any lingering olfactory cues from previous trials. Salinity and temperature were checked periodically throughout the experiment and found to range between 4.7–5.0 and 15.5–18.5°C. Fluorescent lighting, placed approximately 20 cm above each aquarium, was used for illumination. The behavioral responses of roach [95% conWdence interval (CI): 31.6 § 5 mm; n = 162] to pike (95% CI: 157.8 § 13 mm; n = 10) and/or perch (95% CI: 144.2 § 14 mm; n = 6) cues were investigated by examining habitat selection (open water vs. structured) in a twoway experimental manipulation within experimental aquaria. First, we allowed individual roach to select between habitats during exposure to three diVerent cue types: olfaction, vision, and vision + olfaction. Second, we manipulated the predator Weld that generated each of our three cue types: no predator (control), one pike, one perch, one pike + one perch, two pike, two perch. This resulted in a 6 £ 3 orthogonal design with 16 unique treatments (we were unable to include the one-pike and one-perch treatments during trials made with just olfactory cues because of predator availability). We conducted six replicates of each unique treatment combination, resulting in 96 trials in which we observed the behavioral response of roach. Runs of cue type were blocked by time for logistic reasons (number of available pike and perch to generate olfactory or visual cues), while the six predator Welds were completely randomized among aquaria and experimental cycles. Including six levels of predator Weld allowed us to evaluate if multiple predator eVects (i.e., do pike and perch foraging together aVect the behavior of prey diVerently than the additive eVects of single predators?) inXuenced the habitat selection of roach using both substitutive (comparing results from the one pike + one perch treatment with results of the two-pike and two-perch treatments) and additive (comparing results from the one-pike and one-perch treatments against the one pike + one perch treatment) designs (GriVen 2006). Both methods have advantages. The substitution design allows for the teasing apart of total density and species richness eVects (e.g., Schmitz and Sokol-Hessner 2002; Vance-Chalcraft et al. 2004). The additive design acknowledges the reality that species richness and overall density usually scale together, and does not alter the strength of intraspeciWc interactions among treatments (e.g., Finke and Denno 2002; Lang 2003; Warfe and Barmuta 2004). We designated six additional holding tanks (also without structure and with opaque partitions) for generating and recovering olfaction cues from each level of predator Weld. Water from nearby Husö Bay was Wltered through a 180m sieve and used to Wll tanks (24.5 cm long £ 16.5 cm wide £ 21 cm tall; Wlled to »3–1), and then we added one 123 896 of the six combinations of predators to each tank. To recover predator-derived olfactory cues, we kept predators inside these tanks for 24 h to standardize scent accumulation. Between trials, we rinsed tanks thoroughly. This procedure was completed each time an experimental cycle was run. We also placed six additional aquaria immediately behind our six experimental aquaria (devoid of any structure, and with an airstone). In treatments requiring vision or vision + olfaction cues from predators, we randomly placed one of the six combinations of predators in these aquaria (moving pike and perch out of the holding tanks as needed). Thus, roach were able to see these predators but not receive olfactory cues (unless separately added, see below). For each trial, we Wrst allowed a single roach to acclimate to the experimental aquarium for 1 h. In treatments that included olfactory cues, we sampled a 100-ml aliquot from each of the six tanks in which predators had been soaking for 24 h. These aliquots were immediately poured into the center of the appropriate experimental aquaria. In trials that employed visual cues, we placed predators in the tanks adjacent to the experimental aquaria at the same time roach were added. To allow acclimation for both predator and prey, we placed an opaque divider between the two aquaria and then removed it after 1 h. In vision + olfaction cue trials, we combined the steps from the olfaction and vision treatments. To observe the behavioral response of roach to cues and minimize handling artifacts, we recorded Wsh movements in the aquaria using a Sony digital video camera (model DCRH36). Video recordings were initiated following the acclimation period (immediately after the addition of predator cues) and the experiment then ran for 1 h. Pairs of roach/ predator aquaria were placed immediately beside each other so we could capture all six in the video recording, and therefore opaque dividers were placed between the six pairs to avoid transmission of visual cues among aquaria and achieve independent replicates. Using a white background behind the aquaria pairs, the silhouettes of roach were highly visible in all videos, making it easy to determine if each individual was in the structured or open-water half of each of the six aquaria. After the experiment, all aquaria and holding tanks were reset as described above. During the Wrst six trials, roach occupancy was recorded every minute and compared at intervals of 1, 2, or 3 min. No statistical diVerence was detected among sampling regimes (two-way ANOVA with trial number and time interval as factors; F1,16 = 39.350, P = 0.125; Tukey’s post hoc: 1 versus 2 min, P = 0.985; 1 versus 3 min, P = 0.932; 2 versus 3 min, P = 0.979), thus 3-min intervals were used to quantify roach occupancy. The frequency of ASU selection by roach was used as the response variable in all subsequent analyses. 123 Oecologia (2010) 162:893–902 Statistical analyses We used a series of one-way ANOVAs to determine if diVerent cue types and predator treatments aVected the roach’s selection of ASU habitat (not having olfactory treatments from the one-pike or one-perch treatments precluded the use of a two-way analysis). First, three separate ANOVAs were conducted to determine if predator Weld generated diVerences in roach habitat selection. For these analyses, we considered the data from each cue treatment (i.e., olfaction, vision, or vision + olfaction) individually. Similarly, we conducted six additional ANOVAs to assess how cue type aVected roach habitat selection. This required parsing the data among the individual predator treatments [i.e., no predator (control), one pike, one perch, one pike + one perch, two pike, two perch]. In cases with signiWcant ANOVA results ( = 0.05), Tukey’s post hoc tests were performed to make pairwise comparisons between treatments. The presence of multiple predator eVects on the habitat selection of roach for both the additive and substitutive designs was evaluated by comparing “expected” habitat selection of roach (based on single-predator species treatments) to observed habitat selection of roach in the mixed-predator treatment. If predator cues aVected roach independently in the one pike + one perch treatment, expected habitat selection of prey in the mixed-predator aquaria for the additive experimental design can be predicted by averaging ASU selection (%) by roach in the separate one-pike and one-perch treatments. A similar approach was true for the substitution design: expected habitat selection of roach in the 1 pike + 1 perch treatment was calculated by averaging results from the individual two-pike and two-perch treatments. We averaged the results of separate predator treatments to calculate expected habitat selection, rather than using the additive or multiplicative models suggested in Sih et al. (1998) or GriVen (2006), because we measured a non-consumptive variable and our measured response could be bi-directional. For example, roach could shift away from one habitat for one predator, and toward that habitat for the other, relative to our controls, with the expectation that in combined predator treatments these two eVects should cancel one another. Thus, the methods proscribed in consumptive multiple predator eVect experiments were not logically or quantitatively appropriate and had to be amended. For both the additive and substitution designs, we used two-sample unpaired t-tests to compare observed outcomes in multiple predator treatments (one pike + one perch) to calculated, expected outcomes as prescribed above. Using this statistical approach, a signiWcant diVerence ( · 0.05) between observed and expected values would indicate that the combined eVects of pike and perch on the habitat selection Oecologia (2010) 162:893–902 897 Parametric assumptions were satisWed in all instances and therefore data transformations were not required. Because each statistical test applied to separate and easily distinguishable hypotheses, we also made no corrections to experiment-wise during this study (Moran 2003). Table 1 Results of one-way ANOVAs testing for the eVects of either cue type or predator Weld on selection of structured habitat by roach Source df Predator Weld (olfaction only treatments) 3 Error Predator Weld (vision only treatments) Error Predator Weld (vision + olfaction treatments) Error Cue type (control) 18,404.2 2,939.2 35 27,448.6 5 10,007.1 36 11,107.1 1 Error Cue type (one perch) Error Error Cue type (two perch) Error Cue type (one pike + one perch) Error 21.3 P 4.10 0.020 7.50 <0.001 6.49 <0.001 0.01 0.989 0.03 0.872 12.92 <0.001 13.95 <0.001 12.76 <0.001 8.49 0.003 Results Juvenile roach responded strongly to the cues of pike and perch, but the speciWc responses (i.e., habitat selection) of roach varied based on the predator Weld and cue type. Within all levels of predator Weld except the control and one-pike treatment, the eVect of cue type on roach habitat selection was highly signiWcant (Table 1). Likewise, predator Weld had a signiWcant eVect on the response of roach during trials run with the three cue combinations (Table 1). For instance, roach were observed in structured habitat only »30% of the time when provided olfactory cues from two pike (we did not have a one-pike treatment with olfactory cues). In contrast, in both the one-pike and two-pike treatments, vision and vision + olfaction cues drove roach into the structured habitat more than 80% of the time (Fig. 1). For the treatments that included only perch as predators, olfaction (two perch) and vision + olfaction (one and two perch) cues resulted in roach selecting structured habitat nearly 80% of the time. However, roach only utilized structured habitat 25–30% of the time when presented with just a visual cue of one or two perch (Fig. 1). If roach were presented with only olfactory or visual cues from one pike + one perch together, the prey selected structured habitat 20–25% of the time. Conversely, when roach were introduced to the vision + olfaction cues of one pike + one 15,970.8 7 12 3,186 1 10,314 12 Cue type (two pike) 11,319.8 5 16 Cue type (one pike) F 20 2 Error SS 9,579 2 12,686.1 17 7,732.5 2 13,570.9 17 9,042.9 2 11,430.6 17 11,449.4 SigniWcant values (P · 0.05) are shown in bold (behavioral response) of roach were not independent. For the additive design, separate analyses were conducted for the trials run with vision and vision + olfaction cues. For the substitution design, separate analyses were run for all three cue types. 2 p ik e 1 p ik e 2 perch 1 perch Time in structured habitat (%) 100 A,2 B,1 1 pi ke +1 p e r ch contr ol A,1 A ,2 A,1 80 AB A, 2 AB 60 40 A,2 A, 1 B B ,1 A ,1 A,1 B,2 B,1 20 0 No Data No Data Olfaction Vision Vision + olfaction Cue type Fig. 1 Frequency of roach (Rutilus rutilus) selection of artiWcial seagrass habitat (ASU; mean + 1 SE) when exposed to diVerent cue types (olfaction, vision, and vision + olfaction) and predator Welds (no predator, one pike, one perch, one pike + one perch, two pike, two perch). DiVerent letters indicate diVerences at P · 0.05 among predator treatments within each cue treatment and numbers indicate diVerences at P · 0.05 among each cue treatment within each predator Weld (ANOVA results provided in Table 1) 123 898 Oecologia (2010) 162:893–902 100 Expected (additive) Expected (substitutive) Observed Time in structured habitat (%) perch they selected the ASU half of the aquaria 70% of the time (Fig. 1). Notably, no diVerences in prey response were found between single predator species treatments regardless if cues from one or two individuals were used (i.e., vision or vision + olfaction cues from either one pike and two pike or one perch and two perch), suggesting that cue saturation was achieved with the addition of a single predatory Wsh (Fig. 1). Statistical support for the occurrence of multiple predator eVects was highly dependent on the cue type presented to roach (Table 2). For olfactory cues, only the substitutive design was used to evaluate if pike and perch together generated non-linear behavioral responses from the roach. Based on the separate two-pike and two-perch treatments, we estimated that roach should select structured habitat »55% of the time in the one pike + one perch treatment. Interestingly, observed roach selection of ASU habitat was signiWcantly less than what we expected (»25%; P = 0.036; Fig. 2). When roach were presented with visual cues of one pike + one perch, both the additive and substitutive designs demonstrated that the roach again used structured habitat less than would be predicted based on the separate pikeprey and perch-prey interactions. We expected roach to select structured habitat »60% and »55% of the time in the one pike + one perch treatment based on the additive and substitutive designs, respectively. However, we observed that roach selected structured habitat in the mixed-predator treatment only »25% of the time, which was unambiguously diVerent from our expectations (additive, P = 0.017; substitutive, P = 0.024). When roach were presented with vision + olfaction cues, both the additive and substitutive experimental approaches revealed that the behavioral response of roach to multiple predators could be predicted by averaging individual predator–prey interactions. Using the additive and substitutive 80 60 40 20 0 Olfaction Vision Vision + olfaction Cue Type Fig. 2 “Expected” and observed results for roach habitat selection in one pike + one perch treatments. Both additive (black bars) and substitutive (gray bars) approaches were employed to calculate expected and assess multiple predator eVects on the frequency of ASU habitat selection by roach (mean + 1 SE) designs, we expected that roach would select structured habitat »90% and »85% of the time in the mixed-predator treatment, respectively. Ultimately, we observed that roach selected ASU habitat »75% of the time, which was not a signiWcantly diVerent result (additive, P = 0.118; substitutive, P = 0.362). We did note that in all Wve analyses, observed selection of structured habitat in mixed-predator treatments was less than expected by averaging the separate pike-roach and perch-roach results. Discussion Table 2 Results of t-tests for the diVerences in “expected” and observed habitat selection of roach using both the additive and substitutive designs Source df t P Vision 12 2.77 0.017 Vision + olfaction 12 1.68 0.118 Olfaction 10 2.43 0.036 Vision 12 2.57 0.024 Vision + olfaction 12 0.95 0.362 Additive Substitutive SigniWcant values (P · 0.05) are shown in bold and are indicative of non-linear multiple predator eVects 123 Juvenile roach responded strongly to the cues of the pike and perch predators, but the speciWc responses (habitat selection) of roach were varied and partially counter-intuitive (Fig. 3). While fear is known to inXuence the behavior of prey (Brown 2003; Wirsing et al. 2007), our pike-perchroach data indicate that fear-driven responses are contextspeciWc. SpeciWcally, our results suggest that roach are not only able to distinguish between species-speciWc predator cues, but also demonstrate unique responses based on the type of cue that is detected. For instance, roach responded to the olfactory cues of pike by entering open-water habitat, but entered structured habitat when presented with a visual cue of this predator. When presented with visual or olfactory cues of perch, the opposite responses were elicited from roach. Interestingly, roach defaulted to selection of Oecologia (2010) 162:893–902 Fig. 3 Conceptual diagram illustrating the strength of habitat preference for open or structured habitat by roach with olfactory and/or visual cues from pike and/or perch. The length of the arrow scales with the magnitude of observed preference for either habitat type during trials with each combination of cue type and predator Weld (calculated in comparison to the average of all control treatments in which no predator cues were included) structured habitat when presented with vision + olfaction cues of either predator. Moreover, when roach were presented with olfactory cues of both predators, the roach behaved as though they were ignoring the perch, and responded just as they did during the pike-only treatments (choosing open-water habitat). When visual cues of both predators were presented to the prey, roach responded as they did in the perch-only treatments (again selecting open-water habitat). Upon being presented with vision + olfaction cues of both predators, however, roach strongly favored structured habitat; consistent with their responses to detecting pike visually or perch through olfaction. Our results indicating increased use of structured habitat by roach when presented with vision + olfaction cues agree with previous studies that have examined the foraging eYciency of roach predators (i.e., both visual and olfactory stimuli are available to roach; Nelson and BonsdorV 1990; Mattila 1992), but also highlight the more detailed, cue- and predator-speciWc responses of this common forage Wsh. The speciWc antipredator responses of roach likely reXect two interacting factors: the foraging strategies of predatory pike and perch and the diVerence between only perceiving a predation threat versus perceiving and locating that threat. Northern pike forage primarily by occupying structured habitats and ambushing prey (Savino and Stein 1989). We hypothesize that roach may escape structured habitat when a pike is detected through only olfactory cues, because, although roach are aware of threat, they may not 899 be able to determine the direction from which a camouXaged, stationary pike will attack. As a result, they seek open habitat to increase their opportunity to locate pike visually (sensu Horinouchi et al. 2009; Schultz et al. 2009). Conversely, once a stationary pike is located visually (alone or in combination with olfaction), roach can use structured habitat for the mechanical defense it provides against directed pike attacks (Fig. 3). Alternatively, perch move continuously while foraging in structured and unstructured habitats (Eklöv and Persson 1995). As a result, olfactory cues may be received by roach as an unambiguous signal that perch have entered the immediate vicinity, and therefore present a pressing, short-term threat. In this circumstance, our data suggest that roach prefer structured habitat as refuge. Within structured habitats, visual encounters with perch are informative but potentially less reliable than with ambush predators since roving predators will likely move in and out of the visual Weld routinely. Therefore, once a perch has been visually detected, roach may be conditioned to seek open habitats in an attempt to maintain more constant visual contact with this roving predator (unless the immediate threat associated with perch scent cues is also perceived). In fact, we frequently encountered roach in open habitats adjacent to structured habitats while capturing organisms for our trials. The emergent theme of our results is that structured habitat serves as optimal refuge habitat only if roach are able to detect the speciWc location (direction) from which a predation threat will come from (Horinouchi et al. 2009; Schultz et al. 2009). Although aquatic vegetated habitats can decrease the foraging eYciency of predators (Nelson and BonsdorV 1990; Mattila 1992), our results suggest that prey may not always perceive structure as optimal refuge space: a pattern previously documented in terrestrial studies. For example, Valeix et al. (2009) found that lions utilized tall grass as cover during the day while stalking/ambushing prey. In instances that prey (multiple ungulate species) became aware of threatening lions, they spent more time during the day in open habitat away from grasslands. In this case, tall grass did serve as the preferred refuge for these prey species at night, when lions were able to stalk/ambush prey equally well in open habitat (FischhoV et al. 2007). Recently, several marine studies have identiWed speciWc predator–prey scenarios that can result in prey beneWting from less-structured habitats. Notably, these studies and our own experiment all suggest that if structure increases uncertainty for prey in locating predation threats, prey species do not necessarily associate complex habitats with suitable refuge. Studies on gobies under pressure from cryptic ambush predators (sculpin) have shown that prey can experience elevated mortality while occupying dense seagrass patches (Horinouchi et al. 2009). Similarly, James and Heck (1994) showed that increasing density of artiWcial 123 900 vegetation had no impact on the foraging eYciency of another well-camouXaged ambush predator, the seahorse. In tropical environments, the Weld of vision for damselWsh can be limited by complex coral reefs. Subsequently, the behavior of damselWsh is altered such that mating and feeding opportunities are lost, negatively aVecting individual Wtness (Rilov et al. 2007). While behaviors can be observed, determining the decision rules that produce those behaviors is extremely diYcult. With this in mind, we are left to speculate on the role of uncertainty in mitigating the defensive responses of roach to evaluate behavior-related multiple predator eVects. In both olfaction- and vision-only treatments, we observed a non-linear response by roach to the simultaneous detection of one pike + one perch. In each instance, we suspect this occurred because roach eVectively ignored the predator for which the introduced cue should reveal the predator’s position (perch in olfaction trials, pike in vision trials). Rather, the roach behaved as if only the predator that could be detected but not consistently located determined the response that should minimize overall risk (Table 2; Fig. 3). Conversely, when vision + olfaction cue combinations of both predators were presented to roach, thereby providing the prey with information to detect and locate both species, roach responded as expected by balancing its response to account for two equally capable predators (Table 2; Fig. 3). Thus, it is not only the fear of predators that aVects the behavior of prey (Pressier et al. 2005), but also the fear of ambiguity in knowing where attacks will come from. More broadly, our data contribute to a growing literature that indicates community dynamics cannot be predicted by simply summing or averaging all pairwise predator–prey interactions. Although previous studies have mostly focused on changes in prey abundance (e.g., Fodrie et al. 2008), quantifying non-consumptive eVects in scenarios with multiple predators should also elucidate important trophic dynamics. First, several studies have demonstrated distinct and complex behavioral responses to visual and olfactory cues that are known to aid prey in escaping single predators (e.g., Brown and Cowan 2000; Vincent et al. 2005; Brown et al. 2006). Second, emergent multiple predator eVects typically follow from the behavioral response(s) of a shared prey after detecting one or more predators (Sih et al. 1998). Ultimately, quantifying these non-consumptive eVects are valuable because: (1) a shift in prey activity can have impacts that propagate through the food web (Grabowski 2004), and (2) understanding the defensive responses (habitat selection) of prey against predators provides a framework for predicting whether multiple predators should have independent, risk-reducing, or riskenhancing eVects. For instance, our results strongly suggest that, for all of the sensory cues we investigated, roach 123 Oecologia (2010) 162:893–902 responded to multiple predators by shifting toward open water. However, we also noted anecdotally that individual roach switched between unstructured and structured habitats more often when simultaneously presented with cues from both pike and perch. Such behavior has been previously documented with roach under predation threat (Christensen and Persson 1993). We propose that this increase in emergence rates would increase their risk of being captured (Sih 1997). As a result, we predict that multiple predator scenarios will result in enhanced mortality for roach despite its Wne-tuned defensive behaviors. While GriVen (2006) has demonstrated that additive and substitutive experimental approaches can lead to quantitatively and qualitatively diVerent results, we found that these approaches supported one another in investigating the antipredator responses of roach (Table 2). Although these approaches diVer in the way predator density and identity are manipulated, roach responded similarly whether we included one or two pike, or one or two perch in singlepredator treatments (Fig. 1). Essentially, the presence of a single individual pike or perch was suYcient to induce roach to demonstrate their full antipredator response. This is not surprising given the relative size of our experimental mesocosms and that of predators/prey in these systems, but it may also suggest that roach do not respond as though there is intraspeciWc facilitation or interference among pike or perch. As a result, there was little diVerence in expected habitat use for the one pike + one perch treatment regardless of whether we employed the additive or substitutive design. Ultimately, this study should be a gateway to further experiments of roach-pike-perch interactions. We conducted our experiments on single roach, ignoring the social cues that might be relied on by this schooling species to avoid predators (Magurran and Seghers 1994). Schooling, for example, should increase the awareness of each individual roach to the presence and location of predators by the increased probability of detecting predator olfactory and/or visual cues when multiple prey species are present. While collecting roach for our experiments, we routinely observed individuals swimming together in open water near emergent or submerged vegetation. Thus, additional tests are needed to determine whether schooling and solitary roach respond diVerently to threats perceived though olfactory and visual cues. Also, a future experiment should examine if multiple predators (pike and perch) interact to generate enhanced or reduced mortality risk for juvenile roach in landscape mosaics of open and structured habitats. Lastly, we recognize that the habitat selection of roach may be the result of instinctual responses or learned antipredator behaviors (Ferrari et al. 2005; Brown and Chivers 2006; Leduc et al. 2007) prompted by earlier attacks. Thus, conditioning experiments could investigate if the responses Oecologia (2010) 162:893–902 we observed are plastic, and therefore capable of evolving to meet the demands of temporally and spatially varying predator Welds and changing environmental conditions (e.g., increasing turbidity or loss of vegetated habitats). For instance, as turbidity increases, roach are likely to demonstrate a bias for olfactory cues to sense predators. In instances with nearby multiple predators, this bias should lead to greater pike-avoidance behaviors by roach (Table 2), regardless of the distribution of perch. As a result, roach-perch encounters may increase (ultimately, predation rates will also be aVected by other co-occurring changes in submerged aquatic vegetation cover and capture eYciency in turbid water). Clearly, there is considerable opportunity to further explore the complexity of predator– prey interactions and the non-intuitive outcomes that can result from defensive behaviors of prey beyond simple habitat preference (although this likely represents one of the foremost antipredator defenses). Although applied to a freshwater and estuarine ecosystem here, our results may be broadly applicable to many other environments. Acknowledgments Support for this project was provided through general funds from the University of South Alabama’s Department of Marine Science, as well as Husö Biological Station, Åbo Akademi University. We thank S. Scyphers, M. Scheinin, M. Ajemian, and M. 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