Foraging arena theory

Abstract

Introduction 42Basic models of foraging arena theory 43Mechanisms that cause prey population partitioning and vulnerability exchange processes 44 Arena structure caused by restricted spatial distribution of predators relative to prey 45Restricted predator distribution in response to predation risk caused by its predators 45Restricted predator distribution caused by limited predator mobility or habitat requirements 45Restricted prey distribution and/or activity 47Time allocation to safe/resting sites 47 AbstractThere is a critical need for quantitative models that can help evaluate trade-off decisions related to the impacts of harvesting and protection of aquatic ecosystems within an ecosystem context. Ecosystem models used to evaluate such trade-offs need to have the capability of capturing the dynamic stability that can arise when predator-prey interactions are restricted to spatial and temporal arenas. Foraging arenas appear common in aquatic systems and are created by a wide range of mechanisms, ranging from restrictions of predator distributions in response to predation risk caused by their own predators, to risk-sensitive foraging behaviour by their prey. Foraging arenas partition the prey in each predator-prey interaction in a food web into vulnerable and invulnerable states, with exchange between these states potentially limiting overall trophic flow. Inclusion of vulnerability exchange processes in models for recruitment processes and food web responses to disturbances like harvesting leads to very different predictions about dynamic stability, trophic cascades and maintenance of ecological diversity than do models based on large-scale mass action (random mixing) interactions between prey and predators. Although a number of methods to estimate these critical exchange rates are presented, none are considered fully satisfactory. The most important challenge for the practical application of models that incorporate foraging arena theory today is not only developing new or improved methods for measuring exchange rates but also evaluating how such rates vary in responses to major fishery-induced changes in abundances of predators.

Uncertainties in a Baltic Sea Food-Web Model Reveal Challenges for Future Projections

“…The description of trophic interactions between functional groups is based on a foraging arena theory according to which each prey population is split into a component that is vulnerable and a component that is invulnerable to predation (Walters et al 1997;Ahrens et al 2012). The rate at which the prey can move between these two components determines the predation rates on a particular prey population and is in Ecosim determined by a vulnerability (v) parameter.…”

Evolution of boldness and life history in response to selective harvesting

“…Behaviour is represented by a parameter ߬ ∈ ሾ0: 1ሿ, which conceptually is the fraction of time the 214 individual spends foraging. While foraging in risky foraging arenas outside refuges (Ahrens et al 2012), the individual encounters food, but exposes itself to predation as it 216 typically observed (Lima & Dill 1990;Biro et al 2005) and described by optimal foraging theory (McNamara et al 2001). Given this trade-off, the behavioral process in our 218 model is best described by boldness as personality trait, which is defined in modern behavioural ecology as risk-taking during foraging (Réale et al 2007).…”

Use of food resources by small fish species in Neotropical rivers: responses to spatial and temporal variations

“…Thus the use of resources by fish may be related to resource accessibility in the environment, and the active choices and feeding preferences of each species according to their trophic niches or foraging areas (WINEMILLER & JEPSEN 1998, AHRENS et al 2012. These mechanisms, coupled with food availability, can reduce dietary overlap, which can also vary spatially and temporally (ZARET & RAND 1971, ESTEVES & GALETTI 1995.…”