title: Patch exploitation in two dimensions: from Daphnia to simulated foragers.
abstract: We explore the variability that animals display in their movement choices as they forage in a finite-sized food patch with a uniform food distribution, and present a framework for how these choices may be adjusted to optimize foraging efficiency. Inspired by experimental studies of the zooplankton Daphnia, we model foraging animals as "agents" moving in two dimensions in repeated and successive sequences of hops, pauses, and turns. For Daphnia and other species, critical movement parameters such as hop lengths, pause times, and turning angles are typically reported as probability density functions. Similarly, the agents in our simulations choose their movement parameters at random from such distributions. Each distribution is defined by a characteristic width, which we interpret as a "noise width," available to be tuned for increased foraging efficiency. We investigate the sensitivity of the system by measuring the food gathered by the agents as the turning angle and hop length noise widths are varied. In all cases, we find a maximum in food gathered at some particular value of the noise width in question, suggesting that these results can be considered robust examples of natural stochastic resonance.
authors.affiliation: Department of Physics and Astronomy, Center for Neurodynamics, University of Missouri at St. Louis, 503J Benton Hall, One University Boulevard, St. Louis, MO 63121, USA. clara.prats@upc.edu
authors.forename: Nathan D
authors.initials: ND
authors.lastname: Dees
authors.forename: Sonya
authors.initials: S
authors.lastname: Bahar
authors.forename: Ricardo
authors.initials: R
authors.lastname: Garcia
authors.forename: Frank
authors.initials: F
authors.lastname: Moss
mesh_terms: D000818:Animals; D001070:Appetitive Behavior / Q000502:physiology*; D003621:Daphnia / Q000502:physiology*; D017753:Ecosystem; D005247:Feeding Behavior / Q000502:physiology; D008954:Models, Biological; D009043:Motor Activity / Q000502:physiology; D013269:Stochastic Processes