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Many organisms, from bacteria to primates, use stochastic movement patterns to find food. These movement patterns, known as search strategies, have recently be- come a focus of ecologists interested in identifying universal properties of optimal foraging behavior. In this dissertation, I describe three contributions to this field. First, I propose a way to extend Charnov's Marginal Value Theorem to the spatially explicit framework of stochastic search strategies. Next, I describe simulations that compare the efficiencies of sensory and memory-based composite search strategies, which involve switching between different behavioral modes. Finally, I explain a new behavioral analysis protocol for identifying the factors that influence pollinator for- aging. The utility of this protocol is demonstrated using data gathered on sweat bees (Agapostemon) in Western Nebraska.
Advisers: J. David Logan & Chad E. Brassil
Behavior and Ethology Commons, Numerical Analysis and Computation Commons, Other Applied Mathematics Commons, Other Ecology and Evolutionary Biology Commons, Other Mathematics Commons, Probability Commons