Solutions for functional response experiments

Okuyama, Toshinori; Ruyle, Robert L.

doi:10.1016/j.actao.2011.07.002

Cited by 18 publications

(16 citation statements)

References 29 publications

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“…3) models, as the Arditi-Akçakaya model allows for partial ratio dependence (2) ( 3) where P is the predator density, and m relates the attack rate to predator density such that a value of 0 indicates pure prey dependence and a value of 1 indicates ratio dependence. Prey were not replaced as they were killed, and we account for depletion of prey over time by using the formulations of these models provided by Okuyama and Ruyle (2011). These formulations also allowed us to examine the fit of ratio-dependent models where θ = 1 (i.e., hyperbolic), θ = 2 (i.e., sigmoidal), or where θ was estimated from the data.…”

Section: R Eportsmentioning

confidence: 99%

Spatial arrangement of prey affects the shape of ratio-dependent functional response in strongly antagonistic predators

Hossie

Murray

2016

Ecology

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Abstract. Predators play a key role in shaping natural ecosystems, and understanding the factors that influence a predator's kill rate is central to predicting predator-prey dynamics. While prey density has a well-established effect on predation, it is increasingly apparent that predator density also can critically influence predator kill rates. The effects of both prey and predator density on the functional response will, however, be determined in part by their distribution on the landscape. To examine this complex relationship we experimentally manipulated prey density, predator density, and prey distribution using a tadpole (prey)-dragonfly nymph (predator) system. Predation was strongly ratio-dependent irrespective of prey distribution, but the shape of the functional response changed from hyperbolic to sigmoidal when prey were clumped in space. This sigmoidal functional response reflected a relatively strong negative effect of predator interference on kill rates at low prey: predator ratios when prey were clumped. Prey aggregation also appeared to promote stabilizing density-dependent intraguild predation in our system. We conclude that systems with highly antagonistic predators and patchily distributed prey are more likely to experience stable dynamics, and that our understanding of the functional response will be improved by research that examines directly the mechanisms generating interference.

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Section: R Eportsmentioning

confidence: 99%

Spatial arrangement of prey affects the shape of ratio-dependent functional response in strongly antagonistic predators

Hossie

Murray

2016

Ecology

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“…Recently, more functional response studies began to test the importance of the predator density (Kratina et al. ; Okuyama and Ruyle ; Okuyama ). Nevertheless, as discussed above, those data usually do not have the needed resolution because the standard protocol of these experiments is to count the number of prey consumed at the end of an experimental trial.…”

Section: Discussionmentioning

confidence: 99%

“…Although many functional response studies have characterized how prey density influences the average predation success, we know little about how the variance in predation success changes with the prey density because data are not analyzed in such a way. Recently, more functional response studies began to test the importance of the predator density (Kratina et al 2009;Okuyama and Ruyle 2011;Okuyama 2012). Nevertheless, as discussed above, those data usually do not have the needed resolution because the standard protocol of these experiments is to count the number of prey consumed at the end of an experimental trial.…”

Section: Discussionmentioning

confidence: 99%

Consequences of variation in foraging success among predators on numerical response

Okuyama

2013

Ecology and Evolution

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The relationship between foraging success and reproduction is commonly assumed to be linear in theoretical investigations. Although the exact relationship (e.g., linear or nonlinear) does not influence qualitative conclusions of models under some assumptions, an inclusion of individual behavioral variation can make it otherwise due to Jensen's inequality. In particular, a mechanism that stabilizes food web dynamics is generated when two conditions are satisfied: (1) the reproduction of predators experiences diminishing returns from foraging success (i.e., concave down relationship between foraging success and reproduction) and (2) foraging success variation among predator individuals increases with the predator density. However, empirical results that confirm these conditions are scarce. This study describes the mechanism as a hypothesis for stability and discusses some important considerations for empirical verifications of the mechanism.

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“…where a and h are the attack rate and the handling time, respectively, of the predator. Although the Lambert W function is used for convenience (Bolker, 2008;Okuyama & Ruyle, 2011), the same solution can be obtained using the random predator equation (Rogers, 1972).…”

Section: The Population Modelmentioning

confidence: 99%

“…The predominant experimental approach is to place one predator and a variable number of prey (because prey density is the main factor that influences the functional response) in the same environment and count the number of prey eaten. Then, various functional response models are fit to the data (Okuyama & Ruyle, ). When the functional response f is independent of the predator density P (e.g., Holling, ), studies typically do not consider testing the assumption that fP describes the predation rate when there is more than one predator ( P > 1), after characterizing f when P = 1 (i.e., one predator in an experimental arena).…”

Section: Introductionmentioning

confidence: 99%

Variation in foraging success among predators and its implications for population dynamics

Okuyama

2016

Ecology and Evolution

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The effects of the expected predation rate on population dynamics have been studied intensively, but little is known about the effects of predation rate variability (i.e., predator individuals having variable foraging success) on population dynamics. In this study, variation in foraging success among predators was quantified by observing the predation of the wolf spider Pardosa pseudoannulata on the cricket Gryllus bimaculatus in the laboratory. A population model was then developed, and the effect of foraging variability on predator–prey dynamics was examined by incorporating levels of variation comparable to those quantified in the experiment. The variability in the foraging success among spiders was greater than would be expected by chance (i.e., the random allocation of prey to predators). The foraging variation was density‐dependent; it became higher as the predator density increased. A population model that incorporates foraging variation shows that the variation influences population dynamics by affecting the numerical response of predators. In particular, the variation induces negative density‐dependent effects among predators and stabilizes predator–prey dynamics.

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Solutions for functional response experiments

Cited by 18 publications

References 29 publications

Spatial arrangement of prey affects the shape of ratio-dependent functional response in strongly antagonistic predators

Spatial arrangement of prey affects the shape of ratio-dependent functional response in strongly antagonistic predators

Consequences of variation in foraging success among predators on numerical response

Variation in foraging success among predators and its implications for population dynamics

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