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Oecologia ISSN 0029-8549 OecologiaDOI 10.1007/s00442-014-2922-x

Predator interference alters foragingbehavior of a generalist predatoryarthropod

Jason M. Schmidt, Thomas O. Crist,Kerri Wrinn & Ann L. Rypstra

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OecologiaDOI 10.1007/s00442-014-2922-x

BehavIOral ecOlOgy - OrIgInal research

Predator interference alters foraging behavior of a generalist predatory arthropod

Jason M. Schmidt · Thomas O. Crist · Kerri Wrinn · Ann L. Rypstra

received: 24 July 2013 / accepted: 5 March 2014 © springer-verlag Berlin heidelberg 2014

containing elevated predator abundance. Functional response parameter estimation revealed significant levels of interference among predators leading to lower feeding rates even when the area allocated for each predator was kept constant. These results suggest that feeding rates determine patch movement dynamics, where interference induces predators to search for foraging sites that balance the fre-quency of agonistic interactions with prey encounter rates.

Keywords environmental heterogeneity · Flexible foraging · Patch quality · ratio dependent · space use

Introduction

ecologists increasingly recognize that foraging behavior of predators and prey is integral to characterizing the func-tioning of ecological communities (Krivan and schmitz 2003; abrams 2010; arditi and ginzburg 2012). Within this framework, the behavior of individuals within populations and communities influences the dynamics of food webs. Foragers are predicted to remain in patches containing high resource levels and choose patches of the highest quality (charnov et al. 1976; abrams 2007; stephens et al. 2007). While it is recognized that both biotic and abiotic factors influence the quality of a patch by altering interactions between animals, and by moderating environmental condi-tions (sih 1984; Perry and Pianka 1997; Fryxell et al. 1999; laundre et al. 2001; langellotto and Denno 2004; schmidt and rypstra 2010), there is growing recognition and accept-ance that predator–prey dynamics are influenced by com-petitive interactions between predators that alter foraging behavior (skalski and gilliam 2001; Jensen and ginzburg 2005; stephens et al. 2007; anderson 2010; Delong and vasseur 2011; arditi and ginzburg 2012; Fryxell 2013).

Abstract Interactions between predators foraging in the same patch may strongly influence patch use and functional response. In particular, there is continued interest in how the magnitude of mutual interference shapes predator–prey interactions. studies commonly focus on either patch use or the functional response without attempting to link these important components of the foraging puzzle. Predictions from both theoretical frameworks suggest that predators should modify foraging efforts in response to changes in feeding rate, but this prediction has received little empiri-cal attention. We study the linkage between patch departure rates and food consumption by the hunting spider, Pardosa milvina, using field enclosures in which prey and predator densities were manipulated. additionally, the most appro-priate functional response model was identified by fitting alternative functional response models to laboratory forag-ing data. Our results show that although prey availability was the most important determinant of patch departure rates, a greater proportion of predators left enclosures

communicated by Thomas s. hoffmeister.

Electronic supplementary material The online version of this article (doi:10.1007/s00442-014-2922-x) contains supplementary material, which is available to authorized users.

J. M. schmidt · T. O. crist · K. Wrinn Department of Zoology, Miami University, Oxford, Oh 45056, Usa

J. M. schmidt (*) s-225 agricultural science center north, lexington, Ky 40546-0091, Usae-mail: jason.schmidt@uky.edu

a. l. rypstra Department of Zoology, Miami University, hamilton, Oh 45011, Usa

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Predators are expected to move between patches to select foraging sites containing high prey abundance so that they can maximize their feeding rate (Ford 1978; Iwasa et al. 1981; Brown 1988; abrams 2007). classically, prey density alone was assumed to influence the feeding rate of predators, and attack frequency and efficiency assumed to increase with prey abundance until some maximum forag-ing rate is achieved (holling 1961; charnov et al. 1976). In this context, the high feeding rate should be an indication of a quality foraging site where the predator gains the high-est possible benefits (charnov et al. 1976). however, when predators aggregate in areas of high prey abundance, pred-ator–predator encounters are likely to influence the number of prey that can be captured and consumed. Because of this, predator-dependent forms of the functional response have emerged to incorporate the effects of predator abundance in addition to prey density on feeding rates (hassell and var-ley 1969; Beddington 1975; Deangelis et al. 1975; arditi and ginzburg 1989; crowley and Martin 1989; arditi and akcakaya 1990).

Distribution patterns of predators and prey over the landscape are commonly used to understand the effects of spatial configuration on predator–prey interactions. Within this spatially explicit context, predators are predicted to assess conditions and make patch choice decisions based on feeding rate or risk (van der Meer and ens 1997; Fryx-ell et al. 1999). Incorporating predator-dependence leads to the prediction that increases in interference levels lower patch quality by reducing feeding rate on prey. To medi-ate such interactions, predators must spatially or temporally segregate, which even at high prey abundance may lead to changes in the use of these prey-rich patches by foraging predators (sutherland 1992; lopez-Bao et al. 2011). While modeling and laboratory studies of the functional response can provide the mechanism for the distribution of animals, it is necessary to link the functional form to the behavioral shifts that foragers make in order to reduce the magnitude of interference in real field populations.

We test the hypothesis that resource availability and predator interference interactively determine predator for-aging success and patch occupancy. In a field study we assessed the degree to which predator density and prey availability affects the propensity of the forager to leave a patch. In a laboratory experiment, we compared predator functional responses across various levels of prey and pred-ator abundances to identify the best form of the functional response and the importance of interference for a model predator. Our approach was to hold individual predator foraging area constant over a range of predator and prey abundances so as not to confound density with abundance. By using this combined set of experiments, we are able to explicitly link the functional form to the behavior of ani-mals in the field.

Materials and methods

study system and location

all spiders used in experiments were adult female Pardosa milvina (wolf spider), a small ground-dwelling spider, col-lected from the ecology research center (erc), Butler county, Ohio. spiders were maintained within separate cylindrical containers (8 cm diameter × 5 cm high) in an environmental chamber (13 h light: 11 dark, 60 % relative humidity, 25 °c). This wolf spider is one of the numerically dominant predators in riparian and agroecosystems in east-ern north america (Dondale and redner 1990; young and edwards 1990). P. milvina reach highly variable densities in soybean fields, ranging from 5 to 50 m−2 (Marshall et al. 2002). Their variable densities are likely a result of their sit-and-pursue foraging strategy, where they move between quality foraging sites (nyffeler et al. 1994; samu et al. 2003). current evidence shows that high-quality foraging sites are characterized by a combination of prey availabil-ity (Marshall et al. 2000), landscape pattern (Marshall et al. 2006), habitat complexity (schmidt and rypstra 2010), and lower predation risk (rypstra et al. 2007). While for-aging, the rate at which a single individual captures prey in isolation is characterized by a holling type II functional response (Walker and rypstra 2002).

Patch departure and prey consumption experiment

We tested for the influence of prey availability and preda-tor abundance on patch departure rates of the wolf spider P. milvina from structurally complex patches. emigration was measured from enclosures established in the soybean fields at the erc. enclosures were constructed of sheet metal 30 cm in height to form a 0.75-m2 circular area with 10 cm buried in the ground. To prevent escape, the top of each enclosure was covered with 50-mm mesh, and the inside wall of each enclosure was cleaned and coated with a silicone spray. each enclosure had four 0.64-cm holes drilled into the sides (opposing sides, evenly spaced) at the soil surface level. Pitfall traps, plastic cups (0.47 l), with the same sized holes drilled 5 cm below the lid of the cup, were attached to the side of the enclosure so that spiders leaving the enclosures were captured in the cups. each cup contained a small piece of crumbled up paper towel (i.e., structure) as a means to provide refuge from the sun and prevent cannibalism. each plastic pitfall cup also had a lid to prevent escape. This design allows introduced spi-ders the choice to leave enclosures through the holes pro-vided (Buddle and rypstra 2003). enclosures were placed a minimum of 10 m apart in one of four 60 × 70-m soy-bean fields. Once enclosures were positioned in the field, we removed as many prey as possible by suction sampling

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the soil surface within enclosures multiple times using a ryobi garden vacuum (Techtronic Industries north amer-ica, anderson, sc) until no prey were detected. Following suction sampling, all enclosures received a 5-cm layer of wheat straw thatch on the soil surface to provide structural complexity.

eight replicates were used for each prey treatment (removed or enhanced) and predator treatment (low = 7 spiders and high = 28 spiders) combination. Prey availabil-ity was enhanced by adding seven suction samples to each prey-enhanced treatment (Online resource 1). suction samples were taken using the garden vacuum, fitted with an insect net to capture prey. We suction sampled within a 1-m2 metal ring for 20 s from randomly chosen locations in the grassy border adjacent to the field. each sample was emptied into a bucket, and all spiders and predators were removed by hand using forceps. Following sorting, each sample was immediately transferred to the respective enclosure and the enclosure was again covered with the 50-mm mesh. Prey were given a 30-min period of dispersal within the enclosure.

Predators, female P. milvina, were hand collected from the soybean fields at the erc. each spider was collected in a separate 10-ml plastic vial containing a moist paper towel (to keep them from drying out), and kept in the environ-mental chamber overnight without food. Two hours before releasing the spiders in field enclosures, we measured the cephalothorax and the abdomen width of seven spiders from each treatment group using a digital micrometer attached to a stereomicroscope (accuracy of ±0.01 mm). The abdomen width expands as a spider consumes prey and so changes reflect recent feeding history, while the cephalothorax width does not change except at molt and so provides a measure of absolute size (e.g., see references in rypstra et al. 2007).

To initiate the experiment, we opened the side of the mesh cover and carefully added the required spiders for each predator treatment. To reduce interactions between spiders, we deliberately released spiders individually in different locations within the enclosure. We returned to the enclosures 24 h later to collect spiders from the cups designed to catch any spiders leaving, and from within enclosures. We thoroughly inspected the straw and within any cracks in the soil surface for spiders remaining in the enclosures. To measure prey consumption during the 24-h period, we randomly selected from five to seven spiders from each treatment and measured their abdomen width (i.e., to calculate consumption as change in abdomen over the 24-h period).

Feeding rates and interference experiment

To test for the effects of prey and predator abundance on the feeding rate of female P. milvina, we conducted a

functional response experiment in the laboratory. In a facto-rial design, we crossed four abundance levels of P. milvina (1, 2, 4, 8) with three levels of prey abundance (40, 80, 160)—crickets (Acheta domesticus) 0.32 cm in size—for a total of 12 treatment combinations, each replicated eight times. Female P. milvina were used because the feeding rate of males is not influenced by prey abundance (Walker and rypstra 2002). To standardize the diet of the spiders, we fed each spider two 0.32-cm crickets, twice per week for a minimum of 3 weeks prior to the experiment. Before use, spiders were held without food for 1 week to standardized hunger levels. spiders and crickets were allowed to interact within laboratory foraging arenas, circular plastic contain-ers containing 2 cm moist soil on the floor of the arena and a 3-cm layer of thatch on the surface. arenas were designed to hold the search area for each predator constant for all abundance levels (Online resource 1), while manipulating the number of prey in each arena. To initiate trials, crick-ets were released into the arenas and allowed to disperse within the arena for 15 min before introduction of the spi-ders. Individual spiders were carefully released into arenas in different locations to minimize initial interactions. all containers were placed back in the environmental chamber for a 24-h period. spiders were then removed, and the num-ber of crickets remaining counted. no spiders were reused, and arenas were cleaned with soap, alcohol and water before reuse.

Models

We fit multiple published functional forms to the labora-tory data and selected the best-fitting model (Table 1; see Online resource 2). The models fit represent a gradient of complexity and multiple types of predator-depend-ent forms (Table 1). each model provides estimates of

Table 1 summary of functional response types compared in the analysis of laboratory feeding trials

The table is organized by increasing complexity of the forms com-pared

a encounter rate, b encounter rate multiplied by handling time, m magnitude of predator interference, N known initial prey density, P known initial predator density

Model Form of the functional response

lotka–volterra f(N, P) = aN

holling f (N , P) =aN

1+bN

hassell–varley f (N , P) =aNPm

arditi–ginzburg f (N , P) =aN

bN+P

arditi–akçakaya f (N , P) =aN

bN+Pm

Beddington–Deangelis f (N , P) =aN

(1+bN+m(P−1))

crowley–Martin f (N , P) =aN

(1+bN)(1+m(P−1))

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individual predation rate, where f(N, P) represents the number of prey captured per predator over a given amount of time. Because we did not replenish prey during the experiment, prey were depleted during the functional response experiment. each functional form was fit using numerical integration over the duration of the experiment to solve for the integrated per capita feeding rate (skalski and gilliam 2001). In the equations fit to the laboratory feeding trial data (Table 2), N is the initial prey abundance treatment, P is the predator abundance treatment, f(N, P) is the instantaneous feeding rate on prey, or total number of prey killed over the 1 day. The parameter a is the encoun-ter rate, b is the encounter rate multiplied by handling time, and m represents the magnitude of predator interfer-ence (Table 2). In the simplest case, feeding rate is deter-mined only by prey abundance [i.e., lotka–volterra (lotka 1925)], or by the handling time of prey by individual pred-ators (i.e., holling type II). In the case of predators forag-ing in the same area, there is the likelihood that predators interfere with the foraging of others. We fit five different forms of these predator-dependent functional responses (Table 1). The hassell and varley (1969) model equa-tion is similar to the holling type II, but this model lacks a saturating coefficient for handling time, and increases in predator density, P, may influence interference, which is estimated with the additional parameter m, the mutual interference coefficient. The classic ratio-dependent model (arditi and ginzburg 1989) does not contain an interfer-ence constant, and suggests that feeding rate is driven by the ratio of prey to predators. The arditi–akçakaya (1990) model is a holling type II form with an additional term (P) and interference constant (m) where feeding rate is influenced by saturation of predators to prey and predator dependence. The special case of ratio-dependent is real-ized when m equals 1. The crowley and Martin (1989) model equation is parameterized similarly to the Bed-dington–Deangelis model equation (Beddington 1975;

Deangelis et al. 1975) where interference (m) influences feeding rate, but predator interference is predicted to have a minimal effect on feeding rate at high prey densities. similar to the arditi–akçakaya form, both the Bedding-ton–Deangelis and the crowley–Martin reduce to holling type II when m = 0 (see below and Online resource 2 for further details).

statistical analyses

analyses of field and laboratory data were conducted using r version 3.0.0 (r core Team 2013). We tested for the effects of prey and predator abundance on proportion of spiders leaving the field enclosures with a logistic regres-sion model using the general linear model {stats} function with over-dispersion (hastie and Pregibon 1992). To exam-ine differences in consumption as measured by change in abdomen width (difference in before–after rypstra et al. 2007, and references therein), we used the linear mixed effects (lme) {non-linear lme} function with restricted maximum likelihood to estimate variance components (Pinheiro and Bates 2000). This allowed for partitioning the variability of the fixed effects (prey availability and preda-tor abundance treatments) and the random effect (enclo-sure). as a control for size and condition, we assessed the initial size (carapace width) and body condition [analysis of covariance (ancOva) of abdomen width and carapace width] to ensure that initial sizes and hunger levels were similar between treatments. To determine if the frequency of cannibalism differed between the treatment groups, we used a log-linear test of homogeneity.

We fit competing functional response models (Table 1) to the laboratory data to compare models differing in complexity and to estimate the magnitude of interference related to predator abundance (Online resource 2). We did not assume a priori that one functional form or another would be more appropriate for the given data because the

Table 2 comparison of competing functional response models used to estimate interference of the predators Pardosa milvina

Parameters were estimated using maximum likelihood (±95 % confidence interval) (skalski and gilliam 2001), and all were significantly differ-ent from zero, P < 0.0001

AIC akaike’s information criteria, ΔAIC compares alternative models to the model containing the lowest aIc; for other abbreviations, see Table 1

Model a b m aIc ΔaIc

arditi–akçakaya 0.085 ± 0.003 0.055 ± 0.002 1.175 ± 0.021 4,797 0

Beddington–Deangelis 0.091 ± 0.005 0.059 ± 0.003 1.515 ± 0.083 4,803 6

arditi–ginzburg 0.065 ± 0.001 0.040 ± 0.001 – 4,871 74

crowley–Martin 0.044 ± 0.001 0.023 ± 0.001 0.207 ± 0.004 5,988 1,191

holling type II 0.024 ± 0.001 0.016 ± 0.001 – 12,176 7,379

hassel–varley 0.018 ± 0.005 – 0.305 ± 0.005 12,462 7,665

lotka–volterra 0.008 ± 0.001 – – 16,497 11,700

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appropriate form varies between systems (skalski and gil-liam 2001). We fit competing models through numerical integration using the ordinary differential equation {des-olve} function to solve for N(t), the final prey abundance after predators were allowed to forage, while simultane-ously accounting for prey depletion (skalski and gil-liam 2001). We estimated parameters encounter rate (a(), encounter rate times handling time (b), and the interfer-ence parameter (m), in the competing models, by maximum likelihood using maximum likelihood estimation 2 (mle2) {Ben Bolker mle; bbmle} on the numerically integrated levels of prey depletion (skalski and gilliam 2001). To determine the appropriate predator-dependent functional form, we compared the fit of each model using akaike information criteria (aIc). confidence intervals were determined by asymptotic estimates of ses using mle2 {bbmle}. We displayed the best-fitting model using the per capita feeding rate (number of prey killed per predator per day) by dividing the overall feeding rate by the number of predators in a treatment.

Results

Patch departure and prey consumption

Prey availability and abundance of the spiders significantly affected the proportion of P. milvina leaving enclosures (Fig. 1a; Online resource 3). Prey availability had the most pronounced effect on patch leaving: when prey were removed from enclosures, the proportion of spiders leav-ing was nearly double that observed when prey were added to enclosures (Fig. 1a). however, when prey were added to the enclosures with high predator abundance, spiders also emigrated at a higher rate (Fig. 1a; Online resource 3). Over the 24-h period, spiders in prey-addition treat-ments consumed more prey, with a 14 % increase in abdo-men width (F1, 23 = 13.22, P = 0.001), which was con-sistent across spider abundance treatments (F1, 23 = 0.01, P = 0.92; Fig. 1b; see Online resource 3). neither size dif-ferences or body condition between treatments can account for the leaving rates and consumption because the average size of the spiders (anOva carapace width, F3,28 = 0.47, P = 0.71) and condition (ancOva abdomen width, F3,28 = 0.72, P = 0.55) did not differ before the experi-ment (Online resource 3). lastly, there were low levels of cannibalism as indicated by few unaccounted for spiders at the end of the 24-h period as compared to those recovered (Online resource 3), and since the differences between observed frequencies and those expected by homogeneity of responses were small, the probability of spiders miss-ing at the end of the 24-h period was similar between treat-ments (X2

3 = 4.59, P = 0.20).

Feeding rates and interference

The competing functional response models (Table 1) con-sistently yielded a non-zero estimate of parameters for predator interference (Table 2). Thus, modeling P. milvina’s functional response was significantly improved by adding the extra parameter to account for interactions between these predators when foraging. although all of the mod-els converged on non-zero estimates of predator interfer-ence, the arditi–akçakaya model provided the best fit to these data (Table 2). For all predator abundances, the inte-grated feeding rate (number of prey per predator per day)

Fig. 1 Patch-leaving rate of Pardosa milvina, proportion of spiders exiting 0.75-m2 field enclosures over a 24-h period (a), and con-sumption of prey measured as mean change (±1se) in the distensi-ble abdomen width (b). a, b Bars represent mean responses (±1se error bars) to spider abundance treatments [low = 7 (hatched bars); high = 28 (open bars)]. The prey treatments on the abscissa refer to whether prey were added to enclosures or removed from enclosures prior to introduction of the spiders

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increased at low prey levels and then leveled off at the asymptote (Fig. 2). The level of the asymptote decreased as spider number increased (Fig. 2). The interference param-eter m estimated was significantly greater than 1.0, which provides evidence of strong interference in the laboratory (Table 1). at low predator abundance, the predators were saturated with prey and were limited by prey handling time. Increasing predator abundance resulted in similar or lower asymptotic feeding rates as compared to the low-est predator abundance treatment (Fig. 2). The mean size of the spiders (anOva carapace width, F11, 71 = 0.68, P = 0.75) and condition (ancOva abdomen width, F3,

71 = 1.01, P = 0.45) did not differ between treatments prior to the experiment. cannibalism was very low in the labora-tory experiment, which prevents a formal analysis. There were only five cannibalism events (one spider missing after 24 h) that occurred over all the replicates (two in the four spider/40 cricket treatment, two in the eight spider/40 cricket treatments, and one in the eight spider/80 cricket treatment).

Discussion

We found that both prey abundance and conspecific inter-ference are significant determinants of feeding ecology of a numerically dominant generalist predator. generalist

predators, such as spiders, have been thought of as self-limiting because of agonistic interactions and cannibal-ism (riechert and lockley 1984; Wise 2006). Therefore, it would be advantageous to respond to increasing density of conspecifics by modifying space use to mediate such negative interactions. The current study provides support for this hypothesis by documenting increased patch depar-ture rates in response to conspecific abundance. In addition, predator dependence was more severe than ratio depend-ence (where m = 1), which indicates that feeding rate was driven by a combination of prey and predator abundance. Taken together, these results suggest that the signal to leave patches was a lower foraging rate caused by low prey or interference among conspecifics. These results provide evi-dence of a predator-dependent feedback, and emphasize the importance of understanding space use patterns in relation to the characteristics of the foraging success of generalist predators.

We also emphasize that it is critical to use foraging data to evaluate a range of competing functional response mod-els and modern computational tools make it relatively easy to do so. It seems likely that the most appropriate form of the functional response is system specific. however, only more critical evaluation of empirical data from a variety of contexts will reveal if and when we can generalize any given relationship. In addition, it has recently been argued that ratio-dependent functional responses are common in

Fig. 2 results from the functional response experi-ment. Observed and predicted integrated feeding rates of P. milvina at four predator-abundance treatments: a one spider, b two spiders, c four spiders, and d eight spiders plotted against prey abundance. Open circles represent observed feeding rates and lines represent predicted feeding rates (number of crickets captured per predator per day) from the best-fitting model (see Table 1)

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many systems (Delong and vasseur 2011; arditi and gin-zburg 2012), but little is known about the interaction with space use (anderson 2010). This point is important since a large body of theory assumes that some form of the holling type II model is in operation when addressing questions of predator–prey dynamics (skalski and gilliam 2001; Kim-brell et al. 2007; abrams 2010) and these models inform larger ecological questions in areas ranging from biological control to conservation.

Our results indicate that when Pardosa milvina are in an area foraging on prey, interference remains high even when the personal space of each forager is held constant and prey densities are high. The form of functional response that best fit the feeding rate of P. milvina on cricket prey was the arditi and akcakaya (1990) model. The estimated interference parameter suggests that the interaction among conspecifics approximates ratio dependence. There are multiple mechanistic explanations for why interference arises (abrams and ginzburg 2000; Delong and vasseur 2013). For instance, predators may alter movement pat-terns, waste time engaging in aggressive behavior, and prey may be seeking refuge or increase their vigilance. In our experiments, we provided habitat structure that is attractive to P. milvina in the field and allows for high prey capture (schmidt and rypstra 2010). Thus, the predators would normally reach high densities and prey would be unlikely to be able to hide in this habitat. P. milvina have been characterized as disturbance-adapted predators that use a sit-and-move foraging strategy (Marshall et al. 2002; samu et al. 2003). These data are consistent with that ste-reotype in that they likely explore the available habitat in search of high harvest rates of prey and relocate whenever conspecific interference or prey availability reduce intake rates.

In nature, cannibalism and intraguild predation poten-tially influence spider abundance, foraging success and site selection (Wise 2006). however, these pressures are size dependent and, in particular, predation among wolf spiders requires a greater size differential than foraging on insects (rypstra and samu 2005). since we controlled for size dif-ferences among our experimental animals (Online resource 3), cannibalism was low in both experiments. This situa-tion is likely to be true in natural populations because prior studies reveal that the animals that colonize habitat patches in the field tend to be similar in size but differ in density and body condition depending on the prey availability and structural complexity of the patch (Marshall et al. 2000; schmidt and rypstra 2010). Furthermore, the low levels of cannibalism among adult P. milvina (Buddle and rypstra 2003; rypstra and samu 2005; schmidt and rypstra 2010), suggest that it does not strongly regulate populations of this species. Thus, this species seems to be engaged in dynamic flow in and out of various habitat patches that is influenced

by the presence of other predators (including conspecifics) as well as the availability and capture ability of prey.

The ability of this predator to adjust its foraging in response to environmental conditions (i.e., encounter rates, time lost, risk, chemicals) is evidence of flexible forag-ing, which is predicted to influence the dynamics of food webs (abrams 2010). resource availability as compared to interference potentially exerts effects on predators in differ-ent ways. The effects of availability may be more directly assessed by predators as the amount of energy or nutrients available, and risk or interference are indirect effects that reduce time spent securing resources (stephens et al. 2007). Our study suggests that resource abundance has a strong effect on the ability of these predators to exert top-down control on prey, and interference competition weakens the link between prey and predators. at a local scale, increased predator abundance will result in inference, but in open systems where predator foraging behavior is less restricted, interference levels influence giving-up time where foraging behavior shifts from feeding to searching for a new patch.

Acknowledgments We thank sam evans and other undergraduate research assistants for help with the set-up of experiments and animal care. Michael sitvarin kindly contributed comments on an early draft of the manuscript. This research was funded by the Department of Zoology (both hamilton and Oxford, Ohio campuses), and we thank the rodney Kolb for helping with field management at the ecology research center at Miami University.

References

abrams Pa (2007) habitat choice in predator-prey systems: spa-tial instability due to interacting adaptive movements. am nat 169:581–594. doi:10.1086/512688

abrams Pa (2010) Implications of flexible foraging for interspecific interactions: lessons from simple models. Funct ecol 24:7–17. doi:10.1111/j.1365-2435.2009.01621.x

abrams Pa, ginzburg lr (2000) The nature of predation: prey dependent, ratio dependent or neither? Trends ecol evol 15:337–341. doi:10.1016/s0169-5347(00)01908-x

anderson JJ (2010) ratio- and predator-dependent functional forms for predators optimally foraging in patches. am nat 175:240–249. doi:10.1086/649606

arditi r, akcakaya hr (1990) Underestimation of mutual interfer-ence of predators. Oecologia 83:358–361

arditi r, ginzburg lr (1989) coupling in predator prey dynamics-ratio-dependence. J Theor Biol 139:311–326. doi:10.1016/s0022-5193(89)80211-5

arditi r, ginzburg lr (2012) how species interact: altering the stand-ard view of trophic ecology. Oxford University Press, new york

Beddington Jr (1975) Mutual interference between parasites or pred-ators and its effect on searching efficiency. J anim ecol 44:331–340. doi:10.2307/3866

Brown Js (1988) Patch use as an indicator of habitat preference, predation risk, and competition. Behav ecol sociobiol 22:37–47. doi:10.1007/bf00395696

Buddle cn, rypstra al (2003) Factors initiating emigration of two wolf spider species (araneae: lycosidae) in an agroecosystem. environ entomol 32:88–95. doi:10.1603/0046-225x-32.1.88

Author's personal copy

Oecologia

1 3

charnov el, Orians gh, hyatt K (1976) ecological implications of resource depression. am nat 110:247–259. doi:10.1086/283062

crowley Ph, Martin eK (1989) Functional-responses and interfer-ence within and between year classes of a dragonfly population. J n am Benthol soc 8:211–221. doi:10.2307/1467324

Deangelis Dl, goldstein ra, Oneill rv (1975) Model for trophic interaction. ecology 56:881–892. doi:10.2307/1936298

Delong JP, vasseur Da (2011) Mutual interference is common and mostly intermediate in magnitude. BMc ecol 11:1

Delong JP, vasseur Da (2013) linked exploitation and interference competition drives the variable behavior of a classic predator-prey system. Oikos 122:1393–1400

Dondale cD, redner Jh (1990) The insects and arachnids of canada. Part 17. The wolf spiders, nurseryweb spiders, and lynx spiders of canada and alaska. agriculture canada, Ottawa

Ford MJ (1978) locomotory activity and the predation strategy of the wolf spider Pardosa amentata (clerck) (lycosidae). anim Behav 26:31–35. doi:10.1016/0003-3472(78)90005-2

Fryxell JM (2013) The great predator-prey debate. ecology 94:1206–1207

Fryxell JM, Falls JB, Falls ea, Brooks rJ, Dix l, strickland Ma (1999) Density dependence, prey dependence, and popula-tion dynamics of martens in Ontario. ecology 80:1311–1321. doi:10.1890/0012-9658(1999)080[1311:ddpdap]2.0.co;2

hassell MP, varley gc (1969) new inductive population model for insect parasites and its bearing on biological control. nature 223:1133–2000. doi:10.1038/2231133a0

hastie TJ, Pregibon D (1992) generalized linear models. Wadsworth and Brooks/cole, california

holling cs (1961) Principles of insect predation. annu rev entomol 6:163–200. doi:10.1146/annurev.en06.010161.001115

Iwasa y, higashi M, yamamura n (1981) Prey distribution as a fac-tor determining the choice of optimal foraging strategy. am nat 117:710–723. doi:10.1086/283754

Jensen cXJ, ginzburg lr (2005) Paradoxes or theoreti-cal failures? The jury is still out. ecol Model 188:3–14. doi:10.1016/j.ecolmodel.2005.05.001

Kimbrell T, holt rD, lundberg P (2007) The influence of vigi-lance on intraguild predation. J Theor Biol 249:218–234. doi:10.1016/j.jtbi.2007.07.031

Krivan v, schmitz OJ (2003) adaptive foraging and flexible food web topology. evol ecol res 5:623–652

langellotto ga, Denno rF (2004) responses of invertebrate natural enemies to complex-structured habitats: a meta-analytical synthe-sis. Oecologia 139:1–10. doi:10.1007/s00442-004-1497-3

laundre JW, hernandez l, altendorf KB (2001) Wolves, elk, and bison: reestablishing the “landscape of fear” in yellowstone national Park, Usa. can J Zool-rev can Zool 79:1401–1409. doi:10.1139/cjz-79-8-1401

lopez-Bao Jv, Palomares F, rodriguez a, Ferreras P (2011) Intraspe-cific interference influences the use of prey hotspots. Oikos 120:1489–1496. doi:10.1111/j.1600-0706.2011.19194.x

lotka aJ (1925) elements of physical biology. Williams and Wilkins, Baltimore

Marshall sD, Walker se, rypstra al (2000) a test for a differential colonization and competitive ability in two generalist predators. ecology 81:3341–3349. doi:10.1890/0012-9658(2000)081[3341: atfadc]2.0.co;2

Marshall sD, Pavuk DM, rypstra al (2002) a comparative study of phenology and daily activity patterns in the wolf spiders Pardosa

milvina and Hogna helluo in soybean agroecosystems in south-western Ohio (araneae, lycosidae). J arachnol 30:503–510. doi:10.1636/0161-8202(2002)030[0503:acsopa]2.0.co;2

Marshall sD, Walker se, rypstra al (2006) Two ecolog-ically-divergent generalist predators have different responses to landscape fragmentation. Oikos 114:241–248. doi:10.1111/j.2006.0030-1299.14115.x

nyffeler M, sterling Wl, Dean Da (1994) how spiders make a liv-ing. environ entomol 23:1357–1367

Perry g, Pianka er (1997) animal foraging: past, present and future. Trends ecol evol 12:360–364. doi:10.1016/s0169-5347(97)01097-5

Pinheiro Jc, Bates DM (2000) Mixed-effects models in s and s-PlUs. springer, new york Berlin heidelberg

r core Team (2013) r: a language and environment for statistical computing. r Foundation for statistical computing, vienna

riechert se, lockley T (1984) spiders as biological-control agents. annu rev entomol 29:299–320. doi:10.1146/annurev.ento.29.1.299

rypstra al, samu F (2005) size dependent intraguild predation and cannibalism in coexisting wolf spiders (araneae, lycosidae). J arachnol 33:390–397. doi:10.1636/ct05-10.1

rypstra al, schmidt JM, reif BD, Devito J, Persons Mh (2007) Tradeoffs involved in site selection and foraging in a wolf spider: effects of substrate structure and predation risk. Oikos 116:853–863. doi:10.1111/j.2007.0030-1299.15622.x

samu F, sziranyi a, Kiss B (2003) Foraging in agricultural fields: local ‘sit-and-move’ strategy scales up to risk-averse habitat use in a wolf spider. anim Behav 66:939–947. doi:10.1006/anbe.2003.2265

schmidt JM, rypstra al (2010) Opportunistic predator prefers habi-tat complexity that exposes prey while reducing cannibalism and intraguild encounters. Oecologia 164:899–910. doi:10.1007/s00442-010-1785-z

sih a (1984) The behavioral response race between predator and prey. am nat 123:143–150. doi:10.1086/284193

skalski gT, gilliam JF (2001) Functional responses with predator interference: viable alternatives to the holling type II model. ecol-ogy 82:3083–3092. doi:10.1890/0012-9658(2001)082[3083:frwpiv]2.0.co;2

stephens DW, Brown Js, ydenberg rc (2007) Foraging: behevior and ecology. University of chicago Press, chicago

sutherland WJ (1992) game-theory models of functional and aggregative responses. Oecologia 90:150–152. doi:10.1007/bf00317820

van der Meer J, ens BJ (1997) Models of interference and their con-sequences for the spatial distribution of ideal and free predators. J anim ecol 66:846–858

Walker se, rypstra al (2002) sexual dimorphism in trophic mor-phology and feeding behavior of wolf spiders (araneae: lycosi-dae) as a result of differences in reproductive roles. can J Zool 80:679–688. doi:10.1139/z02-037

Wise Dh (2006) cannibalism food limitation intraspecific competi-tion and the regulation of spider populations. annu rev entomol 51:441–465

young OP, edwards gB (1990) spiders in United states field crops and their potential effect on crop pests. J arachnol 18:1–27

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