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Title: Stochasticity in foraging theory : risk and information
Author: Stephens, David William
ISNI:       0000 0004 2742 919X
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 1982
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This thesis considers the importance of adding stochasticity to models of optimal foraging behaviour. The problem is divided into two elements, risk and information, which are treated separately. Part One: Risk. The theoretical and empirical results concerning animal preferences in risky situations are reviewed. Animals are known to show both risk-averse and risk-prone preferences over food reward. It is shown, theoretically, that a simple optimality model mimimizing the probability of death due to starvation accounts for at least some of the observed patterns of preference. The model is generalized to consider preference from arbitrary combinations of mean and variance. Three limitations of the model are treated in detail, that is the importance of starvation by "ruin", mind-changing about risk preferences, and energetic carry-over are discussed. The implications and limitations of these models are outlined. Part Two: Information. The theoretical literature is reviewed, and the problem of information is divided into three elements. A simple model of environmental tracking is studied. The model suggests that there is a trade-off between sensitivity to change and the costs of sampling. The model is tested using great tits (Parus major) foraging in an aviary. The trend in sampling was as predicted, but the birds were less sensitive to change than predicted. The problem of patch sampling is critically discussed. The value of sampling is defined, and this definition is used to compare the assumptions of previous models. Three such problems are treated: the importance of variance in the mixing distribution of patch sub-types; the importance of alternative and unambiguous patch types; and the importance of patch depression. It is concluded that previous models have often over-valued sampling. A simple and natural model of partial patch recognition is considered, and is shown to have empirical support. Implications and limitations of these models of information are discussed.
Supervisor: Krebs, John; Houston, Alasdair Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Zoological sciences ; stochasticity ; optimal foraging behaviour ; environmental tracking