Doctoral Dissertations

Keywords and Phrases

Optimal foraging theory

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 finite patches of food, albeit on different scales, the results clearly show the degree to which the physical constraints imposed upon an animal can dictate the evolution of their behavior"--Abstract, page iii.

Advisor(s)

Bahar, Sonya

Committee Member(s)

Yamilov, Alexey
Larson-Prior, Linda
Waddill, George Daniel
Flores, Ricardo

Department(s)

Physics

Degree Name

Ph. D. in Physics

Sponsor(s)

Dr. Sonya Bahar's Startup Funds
National Science Foundation (U.S.)

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2009

Pagination

viii, 85 pages

Note about bibliography

Includes bibliographical references.

Rights

© 2009 Nathan Daniel Dees, All rights reserved.

Document Type

Dissertation - Restricted Access

File Type

text

Language

English

Library of Congress Subject Headings

Decision making -- Mathematical models
Multiple criteria decision making -- Mathematical models
Stochastic analysis
Subsistence hunting -- Decision making -- Analysis

Thesis Number

T 9636

Print OCLC #

748670161

Electronic OCLC #

905621478

Link to Catalog Record

Electronic access to the full-text of this document is restricted to Missouri S&T users. Otherwise, request this publication directly from Missouri S&T Library or contact your local library.

http://laurel.lso.missouri.edu/record=b8342476~S5

Comments

Funded by NSF Career grant No. PHY-0547647

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