Search

© 2018 The Authors A theoretical and applied literature has suggested that foragers search using Lévy flights, since Lévy flights can maximize the efficiency of search in the absence of information on the location of randomly distributed prey. Foragers, however, often have available to them at least some information about the distribution of prey, gained either through evolved mechanisms, experience and memory, or social transmission of information. As such, we might expect selection for heuristics that make use of such information to further improve the efficiency of random search. Here we present a general model of random search behavior that includes as special cases: area-restricted search, correlated random walks, Brownian search, and Lévy flights. This generative model allows foragers to adjust search parameters based on encounter-conditional and other heuristics. Using a simulation model, we demonstrate the efficiency gains of these search heuristics, and illustrate the resulting differences in the distributions of step-size and heading angle change they imply, relative to Lévy flights. We conclude by presenting a statistical model that can be fit to empirical data and a set of testable, quantitative predictions that contrast our model of adaptive search with the Lévy flight foraging hypothesis.

Drawing on Skellam׳s (1958) work on sampling animal populations using transects, we derive a behavioral ecological model of the choice between sit-and-wait and active-search hunting. Using simple, biologically based assumptions about the characteristics of predator and prey, we show how an empirically definable parameter space favoring active-search hunting expands as: (1) the average rate of movement of prey decreases, or (2) the energetic costs of hunter locomotion decline. The same parameter space narrows as: (3) prey skittishness increases as a function of a hunter׳s velocity, or (4) prey become less detectable as a function of a hunter׳s velocity. Under either search tactic, encounter rate increases as a function of increasing prey velocity and increasing detection zone radius. Additionally, we investigate the roles of habitat heterogeneity and spatial auto-correlation or grouping of prey on the optimal search mode of a hunter, finding that habitat heterogeneity has the potential to complicate application of the model to some empirical examples, while the effects of prey grouping lead to relatively similar model outcomes. As predicted by the model, the introduction of the horse to the Great Plains and the introduction of the snowmobile to Arctic foraging communities decreased the metabolic costs of active-search and led to a change in normative hunting strategies that favored active-search in place of sit-and-wait hunting.