Meeting Abstract
Fat-tailed foraging strategies have been hailed as optimal for patchy environments. Diverse organisms have been documented performing Lévy walks, which are fat-tailed foraging strategies with step lengths drawn from power-law distributions with exponents near -2. But like other fat-tailed strategies, Lévy walks entail relatively high probabilities of very long steps, and therefore involve trade-offs between energy gained through food consumption and energy lost during travel. Under what environmental conditions are these strategies energetically favorable? To explore this question, we constructed an agent-based model that simulated a single forager searching for food in a 2-dimensional world. During each time step, the forager looked for food within its range of perception. If it could perceive food, it moved to the food and consumed it. Otherwise, it drew a step length from a power-law distribution. We ran simulations on 21 worlds, which contained 0.5-15% food cover arranged in randomly distributed, non-overlapping patches, and varied the forager’s power-law exponent (α), range of perception, and whether that range of perception was anteriorly biased. For each simulation, we measured the number of times the forager consumed food, and calculated the cost-benefit ratio. We found that the four-way interaction between % food cover, power-law exponent, range of perception and anterior bias was significant for all three response variables. But in general, a fat-tailed foraging strategy (α=-1) resulted in significantly more food consumed than a thin-tailed strategy (α=-3). However, the beneficial effect of the power-law exponent was almost completely eliminated when considering cost-benefit ratios.
