Transactions of the American Fisheries Society 136:1778–1790, 2007 Ó Copyright by the American Fisheries Society 2007 DOI: 10.1577/T06-026.1
[Article]
Use of Techniques from Foraging Theory to Quantify the Cost of Predation for Benthic Fishes KARL M. POLIVKA*1 Department of Ecology and Evolution, University of Chicago, 1101 East 57th Street, Chicago, Illinois 60637, USA Abstract.—Field assays of survival and foraging behavior were used to estimate the energetic cost of predation risk in terms of reduced prey consumption for two freshwater benthic cottid fishes that (1) opportunistically exploit high resource availability, particularly during their early life history, and (2) compete for resources at the patch scale in estuaries. Both species’ spatial occurrence tended to reflect avoidance of a larger marine predatory cottid, the Pacific staghorn sculpin Leptocottus armatus, but the predator overlapped more with prickly sculpin Cottus asper than with coastrange sculpin C. aleuticus. Survival of coastrange sculpin was reduced more than threefold in experimental assays that exposed juveniles to predation risk, which was statistically consistent with the principle of mortality-to-growth ratio (l/g) minimization. A subsequent experiment measured foraging on depletable food patches during exposure to the threat of predation risk (from an enclosed predator that was prevented from causing lethal effects); juvenile and adult coastrange sculpin reduced their foraging effort 20–30% relative to a predator-free situation. Examining the foraging cost of predation for both coastrange sculpin and prickly sculpin yielded ambiguous results regarding the partitioning of resources and predator avoidance. Adults of each species differed in their responses to predation risk, but the juvenile comparison was complicated by variable resource densities (marine invertebrates) for each species.
The trade-off encountered by foragers consuming resources under the risk of predation is widely studied, and clear behavioral alternatives exist when animals perceive differences in foraging opportunities and mortality risk (reviewed by Lima and Dill 1990; Brown and Kotler 2004). The prevailing conceptual framework consists of models that predict behaviors that optimize Darwinian fitness (e.g., Fretwell and Lucas 1970; Fretwell 1972; Stephens and Krebs 1986; Mangel and Clark 1988; Brown 2000). Extensive theoretical and experimental studies have shown that animals vary considerably in their response to the foraging and predation risk trade-off. Responses include strong predator avoidance in patch choice or foraging effort (e.g., Gilliam and Fraser 1987; Brown 1999), temporal variation in risk allocation (Lima and Bednekoff 1999), and relatively constant foraging effort, even in riskier patches or habitats (e.g. Fraser and Huntingford 1986; Alofs and Polivka 2004). When multiple models of feeding and mortality trade-offs are appropriate, these alternative behaviors might determine which model provides the best fit to the study system (Skalski and Gilliam 2002). Conceptual tools * E-mail:
[email protected] 1 Present address: Pacific Northwest Research Station, Wenatchee Forestry Sciences Laboratory, 1133 North Western Avenue, Wenatchee, Washington 98801, USA. Received February 1, 2006; accepted April 17, 2007 Published online December 10, 2007
that consider behavioral responses can be used to quantify the cost of predation in field studies, but the results may differ between differing scales of comparison—for example, average mortality rates across broad habitat types versus within a habitat characterized by spatial or temporal variability in mortality rates (i.e., safe and risky patches). Quantifying the Cost of Predation Risk in Field Studies Predation risk in highly productive habitats limits the ability of foragers to exploit resources, and early theoretical and empirical work provides a foundation for addressing predation-dependent habitat selection in heterogeneous landscapes. For example, distributions across habitat types or patches where productivity and mortality risk differ can be compared with field approaches that predict habitat selection patterns that minimize the ratio of mortality l to growth g (Gilliam and Fraser 1987). Theory predicts that in heterogeneous landscapes, any habitat that offers a more favorable l/g should be selected over a less-favorable habitat; an equilibrium distribution should occur when l/g is minimized for each habitat. Density dependence causes variation in both predation mortality and growth; thus, the optimal habitat selection pattern may vary as major habitat types become mosaics of patches that differ in relative risks and resources (Morris and Davidson 2000; Morris et al. 2004). At the patch scale, foraging theory predicts a response to the changing harvest rate of food resources relative to costs
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such as predation risk (e.g., Brown 1988, 2000; Brown and Kotler 2004). On depletable experimental food patches, the point at which foragers quit foraging is equivalent to the harvest rate at which foraging gains no longer outweigh the costs according to the equation H ¼ P þ C þ MOC; where H ¼ harvest rate, P ¼ energetic cost of predation (in terms of missed foraging opportunities due to vigilance or other predator avoidance), C ¼ other foraging costs, and MOC ¼ missed opportunity costs for other activities that contribute to fitness (reproduction, searching for mates, etc.). If C and MOC are held constant in an experimental situation, then the H at which the animal is predicted to quit foraging approximates the cost of predation in terms of energetic resources. The quantity of food remaining on the patch at this point is the giving-up density (GUD; Brown 1988) and should vary depending on foraging costs. If all foraging costs except predation risk are controlled experimentally, then differences in GUDs should reflect the cost of predation and should be higher in risky patches than in safe patches. Using these techniques, it is possible to estimate the cost of predation in terms of the relative amount of food remaining on patches where perceived predation risk is higher. Predation Risk and Species Coexistence The stable coexistence of competing species depends upon the presence of at least one axis of environmental heterogeneity along which species can partition resources (e.g., MacArthur and Pianka 1966) or tradeoff opportunities for multiple resources (Tilman 1982; Brown et al. 1994). Predation risk can have a positive, negative, or neutral effect on competition depending on (1) the nature of the interactions between the competitors and their resource and (2) where the predators exert their effects (Gurevitch et al. 2000; Chase et al. 2002). However, predator-mediated coexistence may be manifested by differences in foraging behavior in habitats that differ in food resources and foraging costs (e.g., Kotler and Brown 1988; Kotler et al. 1993; Brown et al. 1994). Foraging theory can elucidate community-level organization of species among habitats in a heterogeneous environment when foraging strategies and perceived predation risk separate competitors in time and space (Brown 2000; Brown and Kotler 2004). Some systems show more or less complete resource or niche partitioning of food resources (e.g., Werner and Gilliam 1984; Kotler et al. 2001), but substantial overlap of species is frequently observed. Foraging theory can identify less-obvious patterns that facilitate species coexistence, including
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energetic trade-offs between metabolic costs and reproduction (Mitchell and Porter 2001) or different habitat-specific vulnerabilities to predators during foraging (Grand and Dill 1999; Grand 2002). Estuarine Fishes, Habitat Selection, and Predation Risk Fish species with nearshore distributions in tidal creeks benefit from high food availability in estuaries (e.g., Kneib 1984; Limburg et al. 1997; Alofs and Polivka 2004, Polivka 2005), but predation risk can have a direct negative effect on the survival of individuals in some systems (Kneib 1987, 1993). Predation can also have sublethal effects in estuaries, such as increasing fish density in microhabitats with macrophytes that provide better refugia but less food availability than other estuarine microhabitats (Sogard 1992; Crowder et al. 1997; but see Alofs and Polivka 2004). Variation in individual condition factor (mass/ length3) among estuarine cottids depended on whether a trade-off between resources and refuge existed (Alofs and Polivka 2004). Fish given the opportunity to select microhabitats offering a trade-off between food and safety (i.e., highly productive estuarine patches containing algal beds as a structural refuge from predation risk) had lower variability in growth and condition factor than fish in unvegetated patches lacking a refuge from predation risk (Alofs and Polivka 2004). Predation risk may also limit estuarine habitat use by fish that move across the freshwater–estuarine ecotone, and I predict that field manipulations will not only verify the existence of predation costs but that foraging theory will also enable me to roughly quantify these costs. The foraging–predation-risk trade-off and the ways in which ecologically similar species respond to it form a continuum along which two or more strategies can coexist. The benthic coastrange sculpin Cottus aleuticus is widely distributed in estuarine and freshwater systems, but strong competition from prickly sculpin C. asper reduces both the growth rate and condition factor of coastrange sculpin (Polivka 2005). For species with distributions that span both freshwater and estuarine portions of tidal creeks, estuarine habitat selection is partially driven by high resource availability (Polivka 2005). Thus, identifying the behavioral differences between species can yield insight into the mechanism of coexistence. Using several types of observational and experimental data, I show that (1) coastrange sculpin and prickly sculpin differ in their spatial distribution relative to Pacific staghorn sculpin Leptocottus armatus, an abundant estuarine predator and (2) the Pacific staghorn sculpin has strong lethal and nonlethal effects contributing to distributional and behavioral patterns of estuarine-
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opportunist fishes that cross the freshwater–estuarine ecotone. However, the mechanism of species coexistence is only partially explained by foraging mode and is confounded by resource variability. Methods Study system.—Cottid fishes in the U.S. Pacific Northwest occupy a variety of intertidal habitats and include freshwater species that opportunistically use estuaries (Moyle 1976; Lee et al. 1980). Big Beef Creek is a low-order tidal creek draining into Hood Canal in western Puget Sound. The lower 1 km (active channel at low tide) is in the mixohaline zone, and the freshwater segment extends 8 km upstream (Polivka 2005). Coastrange sculpin and prickly sculpin use upper mixohaline zone habitats with slightly differing distributional patterns (Ringstad and Narver 1973; Polivka 2005). They consume marine invertebrates, including gammarid amphipods (Eogammarus confervicolus and Corophium spinicorne) and a marine isopod (Gnorimosphaeroma oregonense); the diets of coastrange sculpin consist almost entirely of E. confervicolus (Polivka 2005). The primary freshwater resources for these species include stonefly larvae (Hesperoperla spp.) and small mayfly larvae (e.g., Baetis spp.; Polivka 2005). The exact extent of dietary overlap is unknown, but competitive interactions between these cottids are apparent (Polivka 2005). The predatory marine cottid, the Pacific staghorn sculpin, is also abundant in the estuary (Bayer 1985; Yoklavich et al. 1991; Armstrong et al. 1995; Barry et al. 1996), where it can affect the habitat selection and behavior of large invertebrates (Posey 1986; Fernandez et al. 1993). This species is also a threat to small fishes (Mace 1983; Alofs and Polivka 2004) and can tolerate long periods .1 wk) of exposure to the low salinities characteristic of the upper mixohaline zones of tidal creeks (K.M.P., unpublished data). Its abundance in this estuary, especially during high tides (Anderson and Chew 1972), make it a strong candidate for mediating habitat selection and foraging behavior in fishes through competitive and predatory interactions. Co-occurrence of Cottus spp. and Pacific staghorn sculpin.—I conducted censuses throughout the estuary to determine the abundance of cottids that used the mixohaline zone opportunistically (e.g., Polivka 2005) and the extent to which coastrange sculpin and prickly sculpin encounter predators. Sampling was conducted every 2–4 weeks during the summers of 2000–2002 at 12 permanent stations. Fish were captured using a minnow seine (2.0 3 1.2 m; 3-mm mesh) by taking two short hauls over an area of approximately 6.25 m2, resulting in a consistent census of adults and juveniles in most habitats. Based on depletion sampling (K.M.P.,
unpublished data), very small (,25 mm standard length [SL]) individuals and less than 5% of all other size-classes escaped capture by the seine, but this method reliably detected the spatial and temporal variation in distribution and abundance of estuarine fishes at low tide (Polivka 2005). At each census station, all fish were identified, measured to the nearest millimeter SL, and released. I compared the distribution of adult Pacific staghorn sculpin (.50 mm SL) and predation-vulnerable size-classes (,45 mm SL) of both Cottus spp. by calculating the mean abundance of each species at each census station; I then examined the distribution qualitatively for patterns that indicated overlap. Susceptible size-classes were determined previously by analysis of gut content samples from Pacific staghorn sculpin (Alofs and Polivka 2004) and the distribution of larger size-classes I reported recently (Polivka 2005). Estimating coastrange sculpin mortality.—Physiological stress due to changing salinity and exposure to predators while foraging are the most likely causes of mortality when freshwater fishes use estuaries opportunistically. To examine the effects of two tidal regimes independently of predation risk, a short-term assay was conducted to estimate the survival rate of coastrange sculpin in individual enclosures (predator free) in the upper or lower estuary. After 2 weeks, the mean survivorship of individuals in each section of the estuary was calculated and compared (N ¼ 6 enclosures/section, 1 fish/enclosure). This assay enabled me to determine whether physiological limitations substantially limit estuarine habitat use by coastrange sculpin, possibly depreciating the importance of predation risk. I made the assumption that predator-free patches in the estuary were equivalent to patches in the stream in terms of mortality and justified it by comparison with my previously reported data (Polivka 2005). Thus, an experiment in which the Pacific staghorn sculpin was present or absent in enclosures could adequately represent the growth and mortality trade-off between upstream and estuarine habitats (sensu Gilliam and Fraser 1987). I placed juvenile coastrange sculpin (30– 38 mm SL) in enclosures constructed with galvanized hardware cloth (61 3 61 3 31 cm; 3.25-mm mesh). The narrow range of fish sizes was used to limit treatments to growth or survivorship differences due to density or predator presence alone and to avoid other size-specific differences in demographic parameters. The experiment consisted of control enclosures stocked at ambient density and two treatments that compared the effects of Pacific staghorn sculpin on coastrange sculpin with density-dependent effects (via resource depletion) from increased numbers of coast-
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range sculpin. Ambient densities (3–4 juveniles) were based on the total biomass of coastrange sculpin (including adults) per square meter, which was observed in censuses of abundance (also reported in Polivka 2005). In the second treatment, the numbers and biomass of coastrange sculpin were doubled; in the third treatment, a Pacific staghorn sculpin of sufficient size to be predatory (55–70 mm SL) was added such that the total biomass of fish was equivalent to that in the double-density treatment. I estimated both growth and survival of coastrange sculpin in each treatment by measuring SL (nearest mm) and mass (nearest 0.1 g) of each fish at the beginning and end of the experiment. To identify individual variation in growth, I marked all individuals with a small subcutaneous injection of water-based acrylic paint (Ceramcoat; Delta Technical Coatings, Whittier, California) on the ventral side of the fish (Polivka 2005). After 4 weeks in situ, growth and survivorship rates were calculated based on remaining individuals and were compared among treatments with one-way analysis of variance (ANOVA) on the mean values per replicate enclosure. From my prior results (Polivka 2005) and the predictions of Gilliam and Fraser (1987), I calculated the predicted survivorship of juvenile coastrange sculpin in the estuary with predators present. If no habitat offers a lower l/g ratio, the estuarine mortality rate for coastrange sculpin in the presence of predators should be two- to threefold greater (based on the difference in growth found in Polivka 2005) than the predator-free treatment, which was assumed to have the same l/g as the stream. I used a conservative reduction in mean survivorship of 2.0 to calculate the expected value of l (E[l]) for the enclosures containing predators. However, it is not sufficient to calculate E(l); it is also necessary to incorporate the variance in survivorship for comparison with the experimental treatment. Thus, the survivorship from each replicate was reduced by 2.0 in the calculation so that the E(l) could be compared with the experimental results using ANOVA. I did not conduct a similar experiment with prickly sculpin because a comparison among the stream and estuarine environments was not warranted by distributional data (e.g., Polivka 2005). Giving-up densities of coastrange sculpin.—During August 2000, I conducted a field experiment to determine whether predation risk from Pacific staghorn sculpin changed the value of estuarine patches in terms of food resources (i.e., GUDs) for coastrange sculpin juveniles and adults. To create a depletable and measurable food patch, I placed dry gravel substrate of the same size (;0.5–2.0 cm in diameter) as that found in the active channel of the estuary inside 475-
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mL circular plastic food containers (diameter ¼ 18 cm, depth ¼ 3 cm; Newspring, Inc., Kearny, New Jersey) and incubated these inside enclosures identical to those used in the growth and survivorship experiment. The enclosures contained loose substrate in which the tray was embedded, so that the tray served as a means of taking a standard sample from the foraging patch inside the enclosure. After 7–10 d, patches and trays contained a stable prey assemblage consisting primarily of amphipods and isopods. Thus, my experimental patches allowed me to use a natural abundance of prey in the upper intertidal zone where coastrange sculpin probably forage most frequently, but use of a standardized starting density was not possible. Because these trays provided a standardized foraging patch (total volume before substrate ¼ 763 m3) in all replicates, prey availability is reported as total grams of prey biomass remaining per tray. The experiment to measure GUDs was a 2 3 2 factorial design with coastrange sculpin age-class and predator presence as treatment factors. I kept 21 replicate enclosures free of fish during the foraging period as controls. Experimental cages contained a large (80–85 mm SL) Pacific staghorn sculpin enclosed in a smaller cage to prevent lethal effects on coastrange sculpin and any incidental consumption of the invertebrate prey items from the foraging patch. I then added four to five juvenile (30–35 mm SL; N ¼ 11) or one to two adult (45–60 mm SL; N ¼ 10) coastrange sculpin to these enclosures and to a second set of enclosures that lacked a predator (juveniles N ¼ 10; adults N ¼ 9). To avoid confounding effects of fish biomass on consumption of invertebrate prey, I kept the total coastrange sculpin biomass in juvenile and adult treatments equal although it is unknown whether there is any size-specific scaling of feeding or metabolic rate in this species. After a 7-d foraging period that allowed coastrange sculpin to both acclimate to the enclosures and begin consuming prey, the unconsumed portion of the available prey (i.e., the GUD) was collected by sealing the tray with its lid before removing it from the cage. I then washed the prey from the substrate, filtered them through a 0.3-mm-mesh screen, and preserved them in 70% ethanol for later analysis in the laboratory. To help validate the assumption that declines in prey biomass were attributable to fish growth rather than prey emigration, I reweighed fish to verify increases in total fish biomass during the experiment. After the prey were sorted, the total remaining prey biomass (GUD; nearest 0.0001 g) was obtained and log-transformed for comparison. I used one-way ANOVA to ensure that foraging by coastrange sculpin
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showed a measurable depletion on the food patches. The GUDs were then log transformed and compared with a two-way ANOVA using coastrange sculpin sizeclass and predator presence as treatment factors that might show differences in the response to predators among size-classes of fish. The log transformation of GUDs was performed to facilitate comparisons with results from the second experiment (see below). Giving-up densities and foraging patterns among Cottus congeners.—In a second experiment, I examined whether GUDs differed between the coastrange and prickly sculpins when under predation risk. In August 2001, I established replicates with juveniles and adults of both species by use of techniques identical to those described above. Because each treatment (species 3 age-class 3 predator presence) required enclosures and creation of individual depletable food patches, five rounds of trials were necessary to attain 10 replicates of each treatment. Each round included five control replicates (no fish) that were used to calculate mean prey availability during the foraging period. During the course of the experiment, the total availability of prey measured in the controls changed substantially (ANOVA: F ¼ 59.34, df ¼ 19, P , 0.001). Due to the enclosure limitations, recruitment timing, and occasional loss of replicates due to tidal activity, the species 3 age-class 3 predator treatments could not be balanced across all experimental rounds and a randomized block design could not be used. This high variability in amphipod availability on control and experimental patches necessitated log transformation of GUDs and the use of average food availability during each round of trials as a covariate in an analysis of covariance. I performed a second analysis in which I considered the effects of predation risk within each species separately. Results Co-occurrence of Cottus spp. and Pacific Staghorn Sculpin During low-tide censuses, Pacific staghorn sculpin were found in all areas of the estuary but primarily in the middle to low intertidal census stations, whereas coastrange sculpin were found primarily in upper intertidal census stations (Figure 1). Age-0 prickly sculpin overlapped with coastrange sculpin but were found at all intertidal census stations. Overlap between adult Pacific staghorn sculpin and juvenile coastrange sculpin occurred primarily in the upper intertidal, but downstream of station 7, Pacific staghorn sculpin densities increased and coastrange sculpin were rare. In contrast, prickly sculpin overlapped substantially with Pacific staghorn sculpin in the lower intertidal.
FIGURE 1.—Mean (þSE) density (fish/6.25-m2 station) of juvenile coastrange sculpin (Cottus aleuticus) and prickly sculpin (C. asper) and adult Pacific staghorn sculpin (Leptocottus armatus) at estuarine census stations in the lower (stations 1–4), intermediate (stations 5–8), and upper mixohaline zones (stations 9–12) in Big Beef Creek, western Puget Sound, during 10 census occasions between May and September 2000 and 2001.
Estimating Coastrange Sculpin Mortality Coastrange sculpin showed essentially equivalent survival rates in upper- and lower-estuary individual enclosure assays. In the lower estuary, one individual escaped and one died (survivorship ¼ 0.800); in the upper estuary, one individual died (survivorship ¼ 0.833). Change in mass among remaining individuals was not statistically distinguishable among the two sections and was 0.018-g/week greater in the lower estuary on average (t ¼ 1.0, P ¼ 0.36). In the experimental test of predation mortality, coastrange sculpin individuals suffered a nearly fourfold reduction in survivorship in the presence of Pacific staghorn sculpin (F ¼ 4.61, df ¼ 12, P ¼ 0.033, Figure 2A) relative to survivorship in predator-free enclosures. Using the observed variation in survivorship and assuming that habitat selection minimizes (and equalizes) l/g between the predator-free control (equivalent to upstream survivorship) and the predatorpresent treatment, the predicted survivorship of juvenile coastrange sculpin is 0.367 6 0.082 (mean 6 SE; N ¼ 5), which is not significantly different from survivorship in the presence of Pacific staghorn sculpin (0.181 6 0.110, N ¼ 6; t ¼ 1.39, P ¼ 0.200; Figure 2A). High coastrange sculpin densities reduced survivorship slightly, but pairwise tests between density treatments indicated that this effect was not significant (Fisher’s least-significant-difference test: P . 0.05). There were no significant treatment differences in fish growth, but data could only be obtained from surviving individuals. The ANOVA showed a lack of heterogeneity among all treatments whether the response variable was change in SL (F ¼ 0.61, df ¼ 9, P ¼ 0.564) or change in mass (F ¼ 1.00, df ¼ 9, P ¼ 0.405); such results were probably due to a lack of statistical power. These
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FIGURE 3.—Giving-up density (GUD) of coastrange sculpin, measured as the mean (þSE) total prey biomass remaining on a tray in enclosures (N ¼ 8–10) containing juveniles or adults in the presence or absence of nonlethal predation risk (i.e., a larger Pacific staghorn sculpin). Data were log transformed prior to analysis, and predator effects were significant (twoway ANOVA: F ¼ 19.87, df ¼ 34, P ¼ 0.0009).
FIGURE 2.—Mean (þSE) (A) survivorship (F ¼ 4.61, df ¼ 12, P ¼ 0.033) and (B) growth (SL: F ¼ 0.61, df ¼ 9, P ¼ 0.564; mass: F ¼ 1.00, df ¼ 9, P ¼ 0.405) per enclosure of juvenile coastrange sculpin stocked allopatrically at ambient density (control) and twice the ambient density (high density) and in enclosures (N ¼ 4–6) that also contained a larger (50–65 mm SL) Pacific staghorn sculpin (Leptocottus armatus). Differing lowercase letters indicate significant pairwise differences (Fisher’s least-significant-difference test: P , 0.05). The asterisk indicates predicted mean survivorship (l) under predation risk based on the rule of l/growth ratio minimization.
analyses were conducted with nine degrees of freedom because enclosures that had no survivors were excluded. A comparison of control and double-density treatment enclosures also showed no significant growth differences (one-tailed t-test for SL: t ¼ 1.17, df ¼ 6, P ¼ 0.14; mass: t ¼ 1.63, df ¼ 6, P ¼ 0.077). Giving-up Densities Despite variability in the starting biomass of prey as indicated by the control patches, GUDs were higher for adult and juvenile coastrange sculpin in the presence of predators (Figure 3) than for those in predator-free enclosures. Adults consumed 60% of the prey in predator-free enclosures relative to the control trays but only 8% of the prey when predators were present. Juveniles consumed 38% in predator-free enclosures and 9% in the presence of predators. The ANOVA of log-transformed data confirmed significant predator effects (F ¼ 13.91; df ¼ 1, 36; P ¼ 0.001), indicating that coastrange sculpin reduced prey biomass more in
predator-free enclosures. The analysis further showed no significant differences in overall foraging effort by size-class (F ¼ 1.71; df ¼ 1, 36; P ¼ 0.199) and a marginally significant age-class 3 predation interaction term (F ¼ 3.99; df ¼ 1, 36; P ¼ 0.053). Giving-up Densities and Foraging Patterns among Cottus Congeners In the second GUD experiment, amphipod densities varied considerably between sets of replicates, leading to different prey biomass on each set of control patches. Furthermore, limitations due to the availability of juvenile prickly sculpin, which did not recruit to the estuary in sufficient numbers until the later stages of the experiment, resulted in imbalances in the distribution of species and age-classes among treatments. Different starting prey availability during each set of experimental trials led to different consumption patterns for the species and age-class combinations tested at a particular time. Adults of both prickly sculpin and coastrange sculpin had higher GUDs in the presence of predators than in the absence of predators (F ¼ 5.76; df ¼ 1, 29; P ¼ 0.023). Within-species analysis showed that adult coastrange sculpin had GUD values (in terms of amphipod biomass; Figure 4 [upper panel]) that were nearly identical to those in the 2000 experiment (Figure 3) and were significantly lower in the absence of predation (log-transformed biomass: F ¼ 4.59; df ¼ 1, 14; P ¼ 0.050). However, adult prickly sculpin showed no difference in GUDs whether or not predators were present (F ¼ 1.12; df ¼ 1, 14; P ¼ 0.306; Figure 4 [upper panel]). Despite this difference, the species 3 predator interaction term was not significant (F ¼ 0.03; df ¼ 1, 29; P ¼ 0.844). In contrast with the 2000 results (Figure 3), the predator effect in the two-species analysis of juvenile GUDs for
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FIGURE 5.—Proportion of the prey biomass (g) eaten by juvenile coastrange sculpin relative to initial prey biomass (average patch availability) during measurements of giving-up density in the presence or absence of nonlethal predation risk (i.e., a larger Pacific staghorn sculpin) within enclosures in Big Beef Creek, western Puget Sound.
FIGURE 4.—Comparison of coastrange sculpin (Cottus aleuticus) and prickly sculpin (C. asper) giving-up densities (GUDs), measured as the mean (þSE) total prey biomass (g) remaining on trays within enclosed foraging patches (N ¼ 10– 12) for (upper panel) adults and (lower panel) juveniles in the presence or absence of nonlethal predation risk (i.e., a larger Pacific staghorn sculpin).
both species was not significant (Figure 4 [lower panel]). Variable prey availability in the 2001 experiment particularly affected replicates in which juvenile GUDs were measured. Although most replicates in both years had an average initial prey availability of around 0.12 g, several replicates in 2001 averaged 0.25 g, whereas only one replicate in 2000 was at this starting density. Further complications resulted from a set of predatorfree replicates in 2001, where average initial amphipod availability was very close to the GUD of 0.08 g measured for coastrange sculpin in 2000 (Figures 3, 4 [lower panel]). The biomass of the available food eaten increased with initial amphipod biomass (regression b ¼ 0.224, F ¼ 8.45, R2 ¼ 0.17, P ¼ 0.006; Figure 5). In the presence of predation risk, GUDs in 2000 were around 0.10 g; although half of the replicates in 2001 were conducted at a starting biomass near this GUD, the other half of the replicates (0.25 g) were well above the GUD, and more foraging would be predicted even under the threat of predation risk. Discussion Colonization and occupancy patterns in heterogeneous landscapes may be proportional to resource availability (Fretwell and Lucas 1970; Morris 1987;
Morris et al. 2004), but mobile foragers often underutilize productive habitats (e.g., Kennedy and Gray 1993; Ranta et al. 1999; Polivka 2005) because of spatial detection limitations (Spencer et al. 1995, 1996; Tyler and Hargrove 1997), competition (Polivka 2005), and the attendant predation risk (e.g., Lima and Dill 1990; Grand and Dill 1999; Brown and Kotler 2004). Detecting the cost of predation in field studies is facilitated by approaches derived from foraging theory that can be useful at different scales. However, there are many study systems in which these approaches have not been tested, and techniques have not yet been developed for applying these conceptual models to other field studies. Here, I have shown that direct measurement of the cost of predation using the foraging behavior of benthic estuarine fishes effectively complements large-scale estimates of mortality risk. Opportunistic or seasonal use of estuaries (e.g. Kneib 1984; Limburg et al. 1997) by fishes can be limited by both lethal and nonlethal effects of predation risk. Predation risk from adults in subtidal zones restricted juvenile mummichogs Fundulus heteroclitus to the intertidal zone (Kneib 1987). Birds and piscivorous southern flounder Paralichthys lethostigma threatened juvenile spot Leiostomus xanthurus, but spot survival was primarily affected by southern flounder only (Crowder et al. 1997). In these cases, patch-scale examination of GUDs could quantify the relative cost of predation between habitat or predator types. In my study system, I adapted the GUD technique to show that predation risk, in addition to competition (Polivka 2005), mediates the estuarine distribution of at least coastrange sculpin. Here, I demonstrated that coastrange sculpin were apparently limited in tidal distribution and potentially suffered
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direct mortality that could be mediated by reduced resource intake on depletable food patches. Patch-scale behavioral responses to predation risk included reduction in foraging, but it is still difficult to estimate the relative role of behavior and mortality in the estuarine distribution of coastrange sculpin. Coastrange sculpin overlap frequently at a patch scale with the predatory Pacific staghorn sculpin, which suggests that predation risk could limit the distribution of coastrange sculpin and justifies experiments to examine the cost of predation in estuaries. I found co-occurrence between coastrange sculpin and Pacific staghorn sculpin in the upper intertidal zone, but coastrange sculpin generally avoided the lower intertidal habitats where Pacific staghorn sculpin were most abundant. High-tide movements of Pacific staghorn sculpin and other large marine predators occur regularly in this study system (Anderson and Chew 1972), and the residual presence of Pacific staghorn sculpin at low-tide censuses suggests that this species would probably pose the greatest threat to smaller Cottus. The absence of coastrange sculpin in the lower intertidal could be due to (1) predation risk, as suggested by the survivorship experiment; (2) the inability of coastrange sculpin to tolerate the more frequent exposure to higher salinity characteristic of this zone; or (3) both. However, transplantation of individuals between the upper and lower intertidal zone in predator-free enclosures showed that the avoidance of the lower intertidal by coastrange sculpin does not appear to be due to physiological constraints. Sample size was low in this assay, but the results are congruent with other assays and experiments (Polivka 2005; K.M.P., unpublished data). This assay did not address the physiological cost of movement to the estuary from completely fresh water and any associated adjustment period, which appears to be highly variable (K.M.P., unpublished data) and remains poorly understood in this system. The ‘‘minimize l/g fitness rule’’ can be used to estimate the expected survivorship in habitats where growth is countered by predation costs, specifically whether these costs balance growth benefits in estuarine habitats with respect to predator-free situations and upstream habitats. At the patch scale (small microhabitats occupied by one or a few fish), behavioral responses can be used to quantify the cost of predation in terms of lost foraging gains (e.g. Abrahams and Dill 1989; Kotler and Blaustein 1995). Relative densities of coastrange sculpin and Pacific staghorn sculpin in the upper estuary and the predictions of the l/g minimization rule (Werner and Gilliam 1984; Gilliam and Fraser 1987) were the basis
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for the survivorship experiment. Field enclosures have proven effective for short-term manipulative experiments, particularly involving juvenile cottids; high survivorship under most conditions and measurable growth rates suggest reasonable access to resources (e.g., Alofs and Polivka 2004; Polivka 2005). Previous assays and experiments showed that survivorship of coastrange sculpin in predator-free enclosures at ambient densities in both estuarine and upstream habitats is equal (Polivka 2005). Thus, the survivorship of coastrange sculpin at ambient density with no predators in the estuary can reasonably represent the predator-free survivorship in either habitat. I used the l/g minimization rule to calculate the expected mortality due to predation in the estuary, given the growth rate I reported previously (Polivka 2005). The rule predicts an equilibrium distribution where no habitat offers a lower ratio; thus, the coastrange sculpin mortality rate in the estuarine habitat should be two- to threefold greater when Pacific staghorn sculpin are present than in predator-free enclosures to balance the two- to threefold higher growth in the estuary (Polivka 2005). The observed reduction in coastrange sculpin survivorship was consistent (when variance was considered) with the predicted value obtained from the l/g minimization rule and from existing survivorship data for the freshwater reaches of the stream. Growth of surviving individuals is usually a tractable means of quantifying the risk of predation at the population level (e.g., Werner and Anholt 1993; Tollrian 1995; McPeek and Peckarsky 1998), but individual coastrange sculpin that survived in the presence of Pacific staghorn sculpin grew almost as rapidly as individuals in low-density control treatments. Low sample size limited statistical power of this comparison (Figure 2b), but I also found no significant effect of simply doubling coastrange sculpin density on fish growth. Although I previously found an effect of fish density (Polivka 2005), this result is still consistent with the conclusion that the estuary could potentially support twice the observed density of coastrange sculpin if costs, such as predation risk, were absent. My predation mortality estimate might be inflated by the enclosed nature of the experimental arenas because field situations might provide other possible refugia for coastrange sculpin. Alternatives include short-term movements to upstream areas, given the spatial and temporal variability in the distribution of Pacific staghorn sculpin and their absence above the mixohaline zone. However, Pacific staghorn sculpin did not completely eliminate all coastrange sculpin from the enclosures in the 4-week experimental period, suggesting foraging costs for predators not addressed by the experiments (Armstrong et al. 1995; Barry et al. 1996)
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or limitations on the capacity of 65–85-mm Pacific staghorn sculpin to consume small fishes (sensu Abrams 1989; Schmitz 1995). This size-class is most abundant during the early juvenile stages of estuarine habitat use by coastrange sculpin and is capable of piscivory (Alofs and Polivka 2004). In the field, predation rates by Pacific staghorn sculpin of any size-class might be limited if these predators also experience predation risk (Abrams 1991; Abrams and Schmitz 1999), have state-dependent foraging strategies (e.g., Mangel and Clark 1988; Clark 1994; Lima and Bednekoff 1999; Krivan and Vrkoc 2000), or induce behavioral responses by prey species. Whether or not a distributional equilibrium is achieved according to the l/g minimization rule in this system, it is apparent that both food availability and predation risk have complementary effects on fitness in the estuary. Actual measurement of the cost of predation is possible when foragers quit harvesting depletable food patches in favor of alternate behaviors, such as vigilance (e.g., Lima 1988; Brown 1999), but usually assumes that the giving-up behavior includes actually leaving the patch (e.g., Brown 1988). In this case, an in situ experiment in the estuary required individuals to be enclosed so that the behaviors estimated by the GUDs are relative levels of resource consumption. My experimental design limited the suite of behavioral refugia from predation to those, such as vigilance (Brown 1999), that can occur within the patch. The fact that cottids are cryptic suggests that inactivity is the most common means of predator avoidance, an outcome consistent with the GUD experiments in this study. Migration between upstream and estuarine habitats might also be an effective counterpredatory measure because Pacific staghorn sculpin were not observed above the mixohaline zone in this system (e.g., Polivka 2005), but coastrange sculpin movement patterns based on mark–recapture data neither support nor refute this hypothesis (K.M.P., unpublished data). In the absence of predation risk, the GUD for juvenile and adult coastrange sculpin was 0.080–0.100 g/tray; for juveniles, 0.02 g more amphipod biomass was required for foraging under the risk of predation. In the 2001 experiment, however, GUDs were not significantly different for juveniles among treatments. During the juvenile GUD trials in 2001, the availability of food was frequently around 0.250 g, which is more than twice the GUD measured in 2000 for foraging under predation risk. Foraging theory predicts that food will have a marginal rate of substitution for safety from predation risk and that these two inputs into a forager’s survival will be complementary (Brown 1988). If food resources are well above the normal GUD, we would
expect that the cost of predation has been met and that foraging on these especially rich patches would be profitable even in the presence of predators. Indeed, I found that coastrange sculpin consumed more prey biomass on richer patches, possibly because the cost of predation was outweighed by the availability of food. Because the GUD in the 2000 experiment was not reached during the 7-d foraging period in the 2001 trials, it is possible that longer trials are needed for richer patches. Prey immigration and emigration can be a factor in these experiments as well, but because I was able to obtain measurable growth in the fish used as foragers in such a short period, it is assumed that measured prey biomass primarily reflects the GUD rather than prey dispersal patterns. Because GUDs for prickly sculpin were not measured in 2000, I was limited in my ability to make behavioral comparisons among species. Prickly sculpin showed slightly more depletion in the risky treatments, which—combined with their more frequent cooccurrence with predatory Pacific staghorn sculpin— is suggestive of more risk-prone behavior (e.g., Fraser and Huntingford 1986; Alofs and Polivka 2004): less vulnerability to predation or more efficient foraging. However, these two alternatives cannot be completely evaluated with the present data. Adult GUDs in both study years were measured under similar levels of food availability, and my results were consistent between years for adult coastrange sculpin. There was no significant species 3 predation interaction term in the overall ANOVA, but the fact that trials were independent replicates justified use of separate analyses for the two species. Adult prickly sculpin had slightly higher GUDs in the presence of predators, but because the comparison with the predator-free treatment was not significant, prickly sculpin appeared to either (1) have a lower cost of predation or (2) be more prone to risky behavior. Adult prickly sculpin co-occur readily in lower intertidal census stations (Polivka 2005), and juveniles in all parts of the estuary grow rapidly. Adults in the lower intertidal reach a size at which they can even be predatory on small conspecifics (Pfister 2003), making it unlikely that predation by Pacific staghorn sculpin limits foraging by adult prickly sculpin in this reach of the tidal creek. I expected that adult coastrange sculpin would also be less vulnerable to predation than juveniles; however, I still found a significant increase in adult GUDs when Pacific staghorn sculpin were present, which suggested a higher perceived cost of predation and may explain their infrequent appearance in lower intertidal census stations (Polivka 2005). Nonlethal foraging costs show that mortality may be a poor indicator of a predator’s effect. Many large
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predatory marine fishes make high-tide excursions into estuaries (Anderson and Chew 1972; Yoklavich et al. 1991), so short-term reductions in foraging effort might be optimal for adult Cottus; however, this does not explain the lack of a response in adult prickly sculpin. Differences in resource consumption by different size-classes of foraging fish may also complicate the measurement of foraging costs using GUDs. In this study, juvenile GUDs were more variable and E. confervicolus that remained on the trays were larger than those in adult GUDs. This difference in mean amphipod size initially suggested that large amphipods impose different handling costs on the foraging juveniles. Such costs contribute to the total cost of foraging due to reduced metabolic efficiency (e.g., Rovero et al. 2000) or to the forager’s predation costs via longer exposure time to predation risk (Sih 1993). However, electivity analysis enabled me to show that juvenile coastrange sculpin selected numbers of large amphipods that were comparable to selection by adults and that adults tended to avoid small amphipods, which constituted a very small percentage of the total available resource. Although the cost of predation for both adult and juvenile coastrange sculpin was detectable, strong species differences in foraging behavior that might facilitate coexistence between congeners were only apparent for adults. Predation risk and its interaction with the resources of competing species have been synthesized into an ‘‘ecology of fear’’ (Brown et al. 2001) in which vigilance, patch use, phenology, food preferences, and foraging efficiency all indicate tradeoffs that promote species coexistence (e.g., Werner and Hall 1988; Brown 1999; Brown et al. 1994; Grand 2002) and diversity in a wide range of taxa, including, for example, freshwater (Lewis 2001; Chase et al. 2001) and marine invertebrates (Wilson et al. 1999), ants (Albrecht and Gotelli 2001), and mammals (e.g. Brown 1988; Kotler et al. 1993; Ziv et al. 1993), and coexistence between birds and mammals (Brown et al. 1997; Kotler and Brown 1999). Despite the complications of applying foraging theory in the dynamic ecosystem presented by the freshwater–estuarine ecotone, these assays and experiments show that predation risk in the estuary creates a food versus safety trade-off across major habitats and between risky and safe patches within the estuary. The two Cottus spp. in this system are found in high densities in estuarine habitats, where individuals have the opportunity to enhance growth rates at early life stages (Polivka 2005) but where they may encounter the generalist predator, the Pacific staghorn sculpin. In estuarine systems, temporal and spatial variability in predation risk is implied by the effects of predators on
estuarine distributions of species (Kneib 1987; Sogard 1992; Crowder et al. 1997). This work emphasizes the importance of behavioral patterns at small spatial scales, which can facilitate variable co-occurrence of fish and their competitors or predators; such coexistence cannot always be explained by distributional data. The difference in GUDs for predator-present and predator-free treatments averaged about 0.02 g/tray, which is an estimate of the nonlethal cost of predation risk for juvenile and adult coastrange sculpin. This cost, combined with competitive effects of prickly sculpin, limits the benefit of estuarine habitat selection by coastrange sculpin. The fitness consequences of reduced energy intake may result in frequency-dependent behavior at the population level (e.g., Anholt and Werner 1995). The landscape of risk taking and resource availability can result in multiple strategies, some of which involve risk taking under low reserves, often resulting in mortality (Clark 1994; Sinclair and Arcese 1995). The actual level of risk assumed by foragers of varying individual condition might affect GUDs and subsequently population-level condition regulation; these possibilities are beyond the scope of this study. Identification of appropriate conceptual tools for consideration of the interaction between resources and risks (Gilliam and Fraser 1987; Brown 1992), such as the measurement of GUDs (e.g., Brown 1988), enables the quantification of the cost of predation in terms that can be applied to advancing studies of the broader consequences of foraging and habitat ecology in many systems. Acknowledgments Portions of this work received support from a Sigma Xi Grant-in-Aid of Research, a University of Chicago Committee on Evolutionary Biology Hinds Fund award, and personal funds. Additional support was provided by a Graduate Assistance in Areas of National Need training fellowship from the U.S. Department of Education. I thank K. Schmitt, D. Beauchamp, and G. George for the use of space and facilities at the Big Beef Creek Fish Research Station. This manuscript was submitted in partial fulfillment of the requirements for a Ph.D. in the Department of Ecology and Evolution at the University of Chicago. I thank C. Pfister, J. Brown, B. Chernoff, M. Leibold, and T. Wootton for helpful comments on the manuscript. This study also benefited from discussions with colleagues in the ecology group at the University of Chicago and the Aquatic and Land Interactions Team at the U.S. Department of Agriculture Forest Service’s Pacific Northwest Research Station laboratory in Wenatchee, Washington. Extremely valuable technical assistance was provided by R. Flint, L. Weis, K. Alofs, P. Tharp, R. Kordas, and K.
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Logan. Field censuses and studies of relative foraging effort were conducted with the permission of the University of Washington Institutional Animal Care and Use Committee (Protocol Number 3286-06). References Abrahams, M. V., and L. M. Dill. 1989. A determination of the energetic equivalence of the risk of predation. Ecology 70:999–1007. Abrams, P. A. 1989. Decreasing functional responses as a result of adaptive consumer behavior. Evolutionary Ecology 3:95–114. Abrams, P. A. 1991. Optimal traits when there are several costs: the interaction of mortality and energy costs in determining foraging behavior. Behavioral Ecology 4:246–253. Abrams, P. A., and O. J. Schmitz. 1999. The effect of risk of mortality on the foraging behaviour of animals faced with time and digestive capacity constraints. Evolutionary Ecology Research 1:285–301. Albrecht, M., and N. J. Gotelli. 2001. Spatial and temporal niche partitioning in grassland ants. Oecologia 126:134– 141. Alofs, K. M., and K. M. Polivka. 2004. Microhabitat-scale influences of resources and refuge on habitat selection by an estuarine-opportunist fish. Marine Ecology Progress Series 271:297–306. Anderson, R. D., and K. K. Chew. 1972. Preliminary study on the transient species of fish in Big Beef Harbor. Transactions of the American Fisheries Society 101:726–729. Anholt, B. R., and E. E. Werner. 1995. Interaction between food availability and predation mortality mediated by adaptive behavior. Ecology 76:2230–2234. Armstrong, J. L., D. A. Armstrong, and S. B. Mathews. 1995. Food habits of estuarine staghorn sculpin, Leptocottus armatus with focus on consumption of juvenile Dungeness crab, Cancer magister. U.S. National Marine Fisheries Service Fishery Bulletin 93:456–470. Barry, J. P., M. M. Yoklavich, G. M. Calliet, D. A. Ambrose, and B. S. Antrim. 1996. Trophic ecology of the dominant fishes in Elkhorn Slough, California. Estuaries 19:115– 138. Bayer, R. D. 1985. Shiner perch and Pacific staghorn sculpins in Yaquina Estuary, Oregon. Northwest Science 59:230– 240. Brown, J. S. 1988. Patch use as an indicator of habitat preference, predation risk and competition. Behavioral Ecology and Sociobiology 22:37–47. Brown, J. S. 1992. Patch use under predation risk: I. Models and predictions. Annales Zoologici Fennici 29:301–309. Brown, J. S. 1999. Vigilance, patch use and habitat selection: foraging under predation risk. Evolutionary Ecology Research 1:49–71. Brown, J. S. 2000. Foraging ecology of animals in response to heterogeneous environments. Pages 181–215 in M. J. Hutchings, E. A. John, and A. J. A. Stewart, editors. The ecological consequences of environmental heterogeneity. Blackwell Science, Oxford, UK. Brown, J. S., and B. P. Kotler. 2004. Hazardous duty pay and the foraging cost of predation. Ecology Letters 7:999– 1014.
Brown, J. S., B. P. Kotler, and A. Bouskila. 2001. Ecology of fear: foraging games between predators and prey with pulsed resources. Annales Zoologici Fennici 38:71–87. Brown, J. S., B. P. Kotler, and W. A. Mitchell. 1994. Foraging theory, patch use and the structure of a Negev Desert granivore community. Ecology 75:2286–2300. Brown, J. S., B. P. Kotler, and W. A. Mitchell. 1997. Competition between birds and mammals: a comparison of giving-up densities between crested larks and gerbils. Evolutionary Ecology 11:757–771. Chase, J. M., P. L. Abrams, J. P. Grover, S. Diehl, P. Chesson, R. D. Holt, S. A. Richards, R. M. Nisbet, and T. J. Case. 2002. The interaction between predation and competition: a review and synthesis. Ecology Letters 5:302–315. Chase, J. M., W. G. Wilson, and S. A. Richards. 2001. Foraging trade-offs and resource patchiness: theory and experiments with a freshwater snail community. Ecology Letters 4:304–312 Clark, C. W. 1994. Antipredator behavior and the assetprotection principle. Behavioral Ecology 5:159–170. Crowder, L. B., D. D. Squires, and J. A. Rice. 1997. Nonadditive effects of terrestrial and aquatic predators on juvenile estuarine fish. Ecology 78:1796–1804. Fernandez, M., O. Iribarne, and D. Armstrong. 1993. Habitat selection by young-of-the-year Dungeness crab Cancer magister and predation risk in intertidal habitats. Marine Ecology Progress Series 92:171–177. Fraser, D. F., and F. A. Huntingford. 1986. Feeding and avoiding predation hazard: the behavioral response of the prey. Ethology 73:56–68. Fretwell, S. D. 1972. Populations in a seasonal environment. Princeton University Press, Princeton, New Jersey. Fretwell, S. D., and H. L. Lucas. 1970. On territorial behavior and other factors influencing habitat distribution in birds. Acta Biotheoretica 19:16–36. Gilliam, J. F., and D. F. Fraser. 1987. Habitat selection under predation hazard: test of a model with foraging minnows. Ecology 68:1856–1862 Grand, T. C. 2002. Foraging–predation risk trade-offs, habitat selection, and the coexistence of competitors. American Naturalist 159:106–112. Grand, T. C., and L. M. Dill. 1999. Predation risk, unequal competitors and the ideal free distribution. Evolutionary Ecology Research 1:389–409. Gurevitch, J. J., J. A. Morrison, and L. V. Hedges. 2000. The interaction between competition and predation: a metaanalysis of field experiments. American Naturalist 155:435–453. Kennedy, M., and R. D. Gray. 1993. Can ecological theory predict the distribution of foraging animals? A critical analysis of experiments on the ideal free distribution. Oikos 68:158–166. Kneib, R. T. 1984. Patterns in the utilization of the intertidal salt marsh by larvae and juveniles of Fundulus heteroclitus (Linnaeus) and Fundulus luciae (Baird). Journal of Experimental Marine Biology and Ecology 83:41–51. Kneib, R. T. 1987. Predation risk and use of intertidal habitats by young fishes and shrimp. Ecology 68:379–386. Kneib, R. T. 1993. Growth and mortality in successive cohorts of fish larvae within an estuarine nursery. Marine Ecology Progress Series 94:115–127. Kotler, B. P., and L. Blaustein. 1995. Titrating food and safety
PREDATION RISK FOR BENTHIC FISHES
in a heterogeneous environment: when are the risky and safe patches of equal value? Oikos 74:251–258. Kotler, B. P., and J. S. Brown. 1988. Environmental heterogeneity and the coexistence of desert rodents. Annual Review of Ecology and Systematics 19:281–307. Kotler, B. P., and J. S. Brown. 1999. Mechanisms of coexistence of optimal foragers as determinants of local abundances and distributions of desert granivores. Journal of Mammalogy 80:361–374. Kotler, B. P., J. S. Brown, A. Oldfield, J. Thorson, and D. Cohen. 2001. Foraging substrate and escape substrate: patch use by three species of gerbils. Ecology 82:1781– 1790. Kotler, B. P., J. S. Brown, and A. Subach. 1993. Mechanisms of species coexistence of optimal foragers: temporal partitioning by two species of sand dune gerbils. Oikos 67:548–556. Krivan, V., and I. Vrkoc. 2000. Patch choice under predation hazard. Theoretical Population Biology 58:329–340. Lee, D. S., C. R. Gilbert, C. H. Hocutt, R. E. Jenkins, D. E. McAllister, and J. R. Stauffer, Jr. 1980. Atlas of North American freshwater fishes. North Carolina State Museum of Natural History, Raleigh. Lewis, D. B. 2001. Trade-offs between growth and survival: responses of freshwater snails to predaceous crayfish. Ecology 82:758–765. Lima, S. L. 1988. Vigilance and diet selection: the classical diet model reconsidered. Journal of Theoretical Biology 132:127–143. Lima, S. L., and P. A. Bednekoff. 1999. Temporal variation in danger drives antipredator behavior: the predation risk allocation hypothesis. American Naturalist 153:649–659. Lima, S. L., and L. M. Dill. 1990. Behavioral decisions made under the risk of predation: a review and prospectus. Canadian Journal of Zoology 68:619–640. Limburg, K. E., M. L. Pace, and D. Fischer. 1997. Consumption, selectivity, and use of zooplankton by larval striped bass and white perch in a seasonally pulsed estuary. Transactions of the American Fisheries Society 126:607–621. MacArthur, R. H., and E. Pianka. 1966. On optimal use of a patchy environment. American Naturalist 100:603–609. Mace, P. M. 1983. Predator–prey functional responses and predation by staghorn sculpins (Leptocottus armatus) on chum salmon fry (Oncorhynchus keta). Doctoral dissertation. University of British Columbia, Vancouver. Mangel, M., and C. W. Clark. 1988. Dynamic modeling in behavioral ecology. Princeton University Press, Princeton, New Jersey. McPeek, M. A., and B. L. Peckarsky. 1998. Life histories and the strengths of species interactions: combining mortality, growth, and fecundity effects. Ecology 79:867–879. Mitchell, W. A., and W. P. Porter. 2001. Foraging games and species diversity. Annales Zoologici Fennici 38:89–98. Morris, D. W. 1987. Tests of density dependent habitat selection in a patchy environment. Ecological Monographs 57:269–281. Morris, D. W., and D. L. Davidson. 2000. Optimally foraging mice match patch use with habitat differences in fitness. Ecology 81:2061–2066. Morris, D. W., J. E. Diffendorfer, and P. Lundberg. 2004. Dispersal among habitats varying in fitness: reciprocating
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migration through ideal habitat selection. Oikos 107:559–575. Moyle, P. B. 1976. Inland fishes of California. University of California Press, Berkeley. Pfister, C. A. 2003. Some consequences of size variability in juvenile prickly sculpin, Cottus asper. Environmental Biology of Fishes 66:383–390. Polivka, K. M. 2005. Resource-matching across habitats is limited by competition at patch scales in an estuarineopportunist fish. Canadian Journal of Fisheries and Aquatic Sciences 62:913–924. Posey, M. H. 1986. Predation on a burrowing shrimp: distribution and community consequences. Journal of Experimental Marine Biology and Ecology 103:143– 161. Ranta, E., P. Lundberg, and K. Viejo. 1999. Resource matching with limited knowledge. Oikos 86:383–385. Ringstad, N. R., and D. W. Narver. 1973. Some aspects of the ecology of two species of sculpin (Cottus) in a west coast Vancouver Island stream. Fisheries Research Board of Canada Manuscript Report Series 1267. Rovero, F., R. N. Hughes, and G. Chelazzi. 2000. When time is of the essence: choosing a currency for prey-handling costs. Journal of Animal Ecology 69:683–689. Schmitz, O. J. 1995. Functional responses of optimal consumers and the implication for regulation of resource populations. Wildlife Research 22:101–111. Sih, A. 1993. Effects of ecological interactions on forager diets: competition, predation risk parasitism and prey behaviour. Pages 182–211 in R. N. Hughes, editor. Diet selection: an interdisciplinary approach to foraging behaviour. Blackwell Scientific Publications, Oxford, UK. Sinclair, A. R. E., and P. Arcese. 1995. Population consequences of predation-sensitive foraging: the Serengeti wildebeest. Ecology 76:882–891. Skalski, G. T., and J. F. Gilliam. 2002. Feeding under predation hazard: testing models of adaptive behavior with stream fish. American Naturalist 160:158–172. Sogard, S. M. 1992. Variability in growth rates of juvenile fishes in different estuarine habitats. Marine Ecology Progress Series 85:35–53. Spencer, H., M. Kennedy, and R. D. Gray. 1995. Patch choice with competitive asymmetries and perceptual limits: the importance of history. Animal Behaviour 50:497–508. Spencer, H., M. Kennedy, and R. D. Gray. 1996. Perceptual constraints on optimal foraging: the effects of variation among foragers. Evolutionary Ecology 10:331–339. Stephens, D. W., and J. R. Krebs. 1986. Foraging theory. Princeton University Press, Princeton, New Jersey. Tilman, D. 1982. Resource competition and community structure. Princeton University Press, Princeton, New Jersey. Tollrian, R. 1995. Predator-induced morphological defenses: costs, life history shifts, and maternal effects in Daphnia pulex. Ecology 76:1691–1705. Tyler, J. A., and W. W. Hargrove. 1997. Predicting spatial distribution of foragers over large resource landscapes: a modeling analysis of the ideal free distribution. Oikos 79:388–393. Werner, E. E., and B. R. Anholt. 1993. Ecological consequences of the trade-off between growth and mortality
1790
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rates mediated by foraging activity. American Naturalist 142:242–272. Werner, E. E., and J. F. Gilliam. 1984. The ontogenetic niche and species interactions in size-structured populations. Annual Review of Ecology and Systematics 15:393–425. Werner, E. E., and D. J. Hall. 1988. Ontogenetic habitat shifts in bluegill: the foraging rate–predation risk tradeoff. Ecology 69:1352–1366. Wilson, W. G., C. W. Osenberg, R. J. Schmitt, and R. M.
Nisbet. 1999. Complementary foraging behaviors allow coexistence of two consumers. Ecology 80:2358–2372. Yoklavich, M. M., G. M. Cailliet, J. P. Barry, D. A. Ambrose, and B. S. Antrim. 1991. Temporal and spatial patterns in abundance and diversity of fish assemblages in Elkhorn Slough, California. Estuaries 14:465–480. Ziv, Y., Z. Abramsky, B. P. Kotler, and A. Subach. 1993. Interference competition and temporal and habitat partitioning in two gerbil species. Oikos 66:237–246.
