4.5 Article

State dependent behavior and the Marginal Value Theorem

期刊

BEHAVIORAL ECOLOGY
卷 12, 期 1, 页码 71-83

出版社

OXFORD UNIV PRESS INC
DOI: 10.1093/oxfordjournals.beheco.a000381

关键词

marginal value theorem; predation risk; foraging; patch use; stochastic dynamic programming; state-dependent behavior

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The Marginal Value Theorem (MVT) is the dominant paradigm in predicting patch use and numerous tests support its qualitative predictions. Quantitative tests under complex foraging situations could be expected to be more variable in their support because the MVT assumes behavior maximizes only net energy-intake rate. However across a survey of 26 studies, foragers rather consistently erred in staying too long in patches. Such a consistent direction to the errors suggests that the simplifying assumptions of the MVT introduce a systematic bias rather than just imprecision. Therefore, I simulated patch use as a state-dependent response to physiological state, travel cost, predation risk, prey densities, and fitness currencies other than net-rate maximization (e.g., maximizing survival, reproductive investment, or mating opportunities). State-dependent behavior consistently results in longer patch residence times than predicted by the MVT or another foraging model, the minimize mu /g rule, and these rules fail to closely approximate the best behavioral strategy over a wide range of conditions. Because patch residence times increase with state-dependent behavior, this also predicts mass regulation below maximum energy capacities without direct mass-specific costs. Finally, qualitative behavioral predictions from the MVT about giving-up densities in patches and the effects of travel costs are often inconsistent with state-dependent behavior. Thus in order to accurately predict patch exploitation patterns, the model highlights the need to: (1) consider predator behavior (sit-and-wait versus actively foraging); (2) identify activities that can occur simultaneously to foraging (i.e., mate search or parental care); and (3) specify the range of nutritional states likely in foraging animals. Future predictive models of patch use should explicitly consider these parameters.

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