The role of stochastic resonance and physical constraints in the evolution of foraging strategy
type: CreativeWork
description: "This work represents a detailed study of the optimization of this process: foraging within a single, finite food patch for a limited amount of time. The work is an example of the computational algorithms of statistical physics being applied to the ecological field of foraging behavior. The analysis begins with an examination of the probability distributions observed in the movement parameters of the zooplankton, Daphnia. While foraging, these small aquatic organisms stochastically choose movement parameters with particular levels of variation, or noise, which are similar across several species. Here, related simulations consistently show that these noise levels may be adjusted to maximize foraging efficiency, regardless of the physical constraints imposed in the models. The results are presented as an example of natural stochastic resonance, in which some function of noise (in this case, the variability in parameter choices), when adapted to a biological process (e.g., the gathering of food), can optimize that process. The architect of this optimization is suggested to be natural selection, a hypothesis further explored with a novel evolutionary algorithm which transforms uniform and uncorrelated parameter distributions into "optimal" forms over thousands of generations of competition amongst foraging agents. The results of the algorithm support the implication that the noise levels are evolved quantities, and also reinforce the hypothesis that stochastic resonance may have a role in their evolution. And lastly, the evolutionary algorithm was extended to larger aquatic organisms feeding in patches through the addition of the Reynolds number as a physical constraint. The results of the modified algorithm clearly differentiate between the trajectories predicted for smaller and larger animals, and match very well with the experimental data reported here for both the Daphnia, and also for a larger fish species, the paddlefish. Since both organisms filter-feed inside fi…
abstract: "This work represents a detailed study of the optimization of this process: foraging within a single, finite food patch for a limited amount of time. The work is an example of the computational algorithms of statistical physics being applied to the ecological field of foraging behavior. The analysis begins with an examination of the probability distributions observed in the movement parameters of the zooplankton, Daphnia. While foraging, these small aquatic organisms stochastically choose movement parameters with particular levels of variation, or noise, which are similar across several species. Here, related simulations consistently show that these noise levels may be adjusted to maximize foraging efficiency, regardless of the physical constraints imposed in the models. The results are presented as an example of natural stochastic resonance, in which some function of noise (in this case, the variability in parameter choices), when adapted to a biological process (e.g., the gathering of food), can optimize that process. The architect of this optimization is suggested to be natural selection, a hypothesis further explored with a novel evolutionary algorithm which transforms uniform and uncorrelated parameter distributions into "optimal" forms over thousands of generations of competition amongst foraging agents. The results of the algorithm support the implication that the noise levels are evolved quantities, and also reinforce the hypothesis that stochastic resonance may have a role in their evolution. And lastly, the evolutionary algorithm was extended to larger aquatic organisms feeding in patches through the addition of the Reynolds number as a physical constraint. The results of the modified algorithm clearly differentiate between the trajectories predicted for smaller and larger animals, and match very well with the experimental data reported here for both the Daphnia, and also for a larger fish species, the paddlefish. Since both organisms filter-feed inside fi…
author: Dees, Nathan Daniel
keywords: Optimal foraging theory, Physics
date published: 2016-02-10T08:00:00Z
date modified: 2026-07-24T03:18:57Z
provider: Missouri University of Science and Technology
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Missouri University of Science and Technology