
University of Colorado
1.
Krishnan, Nikhil.
Foraging in Stochastic Environments.
Degree: MS, Applied Mathematics, 2019, University of Colorado
URL: https://scholar.colorado.edu/appm_gradetds/145
For many organisms, foraging for food and resources is integral to survival. Mathematical models of foraging can provide insight into the benefits and drawbacks of different foraging strategies. We begin by considering the movement of a memoryless starving forager on a one-dimensional periodic lattice, where each location contains one unit of food. As the forager lands on sites with food, it consumes the food leaving the sites empty. If the forager lands consecutively on a certain number of empty sites, then it starves. The forager has two modes of movement: it can either diffuse by moving with equal probability to adjacent lattice sites, or it can jump uniformly randomly amongst the lattice sites. The lifetime of the forager can be approximated in either paradigm by the sum of the cover time plus the number of empty sites it can visit before starving. The lifetime of the forager varies nonmontonically according to the probability of jumping. The tradeoff between jumps and diffusion is explored using simpler systems as well as numerical simulation, and we demonstrate that the best strategy is one that incorporates both jumps and diffusion. When long range jumps are time-penalized, counterintuitively, this shifts the optimal strategy to pure jumping. We next consider optimal strategies for a group of foragers to search for a target (such as food in an environment where it is sparsely located). There is a single target in one of several patches, with a greater penalty if the foragers decide to switch their positions among the patches. Both in the case of a single searcher, and in the case of a group of searchers, efficient deterministic strategies can be found to locate the target.
Advisors/Committee Members: Zachary Kilpatrick, Nancy Rodriguez, Juan Restrepo.
Subjects/Keywords: Foraging; Dynamic Systems
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APA (6th Edition):
Krishnan, N. (2019). Foraging in Stochastic Environments. (Masters Thesis). University of Colorado. Retrieved from https://scholar.colorado.edu/appm_gradetds/145
Chicago Manual of Style (16th Edition):
Krishnan, Nikhil. “Foraging in Stochastic Environments.” 2019. Masters Thesis, University of Colorado. Accessed January 24, 2021.
https://scholar.colorado.edu/appm_gradetds/145.
MLA Handbook (7th Edition):
Krishnan, Nikhil. “Foraging in Stochastic Environments.” 2019. Web. 24 Jan 2021.
Vancouver:
Krishnan N. Foraging in Stochastic Environments. [Internet] [Masters thesis]. University of Colorado; 2019. [cited 2021 Jan 24].
Available from: https://scholar.colorado.edu/appm_gradetds/145.
Council of Science Editors:
Krishnan N. Foraging in Stochastic Environments. [Masters Thesis]. University of Colorado; 2019. Available from: https://scholar.colorado.edu/appm_gradetds/145

University of Colorado
2.
Krishnan, Nikhil.
Foraging in Stochastic Environments.
Degree: MS, 2019, University of Colorado
URL: https://scholar.colorado.edu/appm_gradetds/150
For many organisms, foraging for food and resources is integral to survival. Mathematical models of foraging can provide insight into the benefits and drawbacks of different foraging strategies. We begin by considering the movement of a memoryless starving forager on a one-dimensional periodic lattice, where each location contains one unit of food. As the forager lands on sites with food, it consumes the food leaving the sites empty. If the forager lands consecutively on a certain number of empty sites, then it starves. The forager has two modes of movement: it can either diffuse by moving with equal probability to adjacent lattice sites, or it can jump uniformly randomly amongst the lattice sites. The lifetime of the forager can be approximated in either paradigm by the sum of the cover time plus the number of empty sites it can visit before starving. The lifetime of the forager varies nonmontonically according to the probability of jumping. The tradeoff between jumps and diffusion is explored using simpler systems as well as numerical simulation, and we demonstrate that the best strategy is one that incorporates both jumps and diffusion. When long range jumps are time-penalized, counterintuitively, this shifts the optimal strategy to pure jumping. We next consider optimal strategies for a group of foragers to search for a target (such as food in an environment where it is sparsely located). There is a single target in one of several patches, with a greater penalty if the foragers decide to switch their positions among the patches. Both in the case of a single searcher, and in the case of a group of searchers, efficient deterministic strategies can be found to locate the target.
Advisors/Committee Members: Zachary P. Kilpatrick, Nancy Rodriguez, Juan G. Restrepo.
Subjects/Keywords: foraging; probability; survival; strategy; Applied Mathematics; Statistics and Probability
Record Details
Similar Records
Cite
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Record Details
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Cite
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Krishnan, N. (2019). Foraging in Stochastic Environments. (Masters Thesis). University of Colorado. Retrieved from https://scholar.colorado.edu/appm_gradetds/150
Chicago Manual of Style (16th Edition):
Krishnan, Nikhil. “Foraging in Stochastic Environments.” 2019. Masters Thesis, University of Colorado. Accessed January 24, 2021.
https://scholar.colorado.edu/appm_gradetds/150.
MLA Handbook (7th Edition):
Krishnan, Nikhil. “Foraging in Stochastic Environments.” 2019. Web. 24 Jan 2021.
Vancouver:
Krishnan N. Foraging in Stochastic Environments. [Internet] [Masters thesis]. University of Colorado; 2019. [cited 2021 Jan 24].
Available from: https://scholar.colorado.edu/appm_gradetds/150.
Council of Science Editors:
Krishnan N. Foraging in Stochastic Environments. [Masters Thesis]. University of Colorado; 2019. Available from: https://scholar.colorado.edu/appm_gradetds/150