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

Toshinori Okuyama

doi:10.1002/ece3.2633

Abstract

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.

Highlights

Functional and numerical responses are important building blocks of population dynamics and are usually defined on a per capita basis
When the functional response f is independent of the predator density P (e.g., Holling, 1959), 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
DP = (f)P − mP, dt whether β is linear (e.g., β(f) = bf) or nonlinear (e.g., β(f) = bf/(q + f)), the predator isoclines are vertical, and predator density does not influence the sign of dP/dt, provided that there is no individual variation among predators and that f is independent of predators

Summary

| INTRODUCTION

Functional and numerical responses are important building blocks of population dynamics and are usually defined on a per capita basis. In studies that consider predator-dependent functional responses, multiple levels of predator densities are tested by assuming that fP (in which f is a predator-dependent functional response) describes the predation rate of a predator population (e.g., Elliott, 2003; Hossie & Murray, 2016), but potential variation among predators is neglected. The relationship between the numerical response β and the functional response f can have important effects when we consider variation in the foraging success among predators (Okuyama, 2013). The On the other hand, per capita-based modeling will predict β(f)P, where f is the average of fi These two quantities are the same only when fi is the same for all i (no individual variation) or when the relationship between β and foraging success is linear. A population model incorporating variable predators is developed and explored to examine the effects of the variation on population dynamics

| MATERIALS AND METHODS

| DISCUSSION