Agent-based models for collective animal movement: Proximity-induced state switching

Journal of Agricultural, Biological and Environmental Statistics
By: , and 

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Abstract

Animal movement is a complex phenomenon where individual movement patterns can be influenced by a variety of factors including the animal’s current activity, available terrain and habitat, and locations of other animals. Motivated by modeling grizzly bear movement in the Greater Yellowstone Ecosystem, this article presents an agent-based model represented in a state-space framework for collective animal movement. The novel contribution of this work is a collective animal movement model that captures interactions between animals that can trigger changes in movement patterns, such as when a dominant grizzly bear may cause another subordinate bear to temporarily leave an area. The modeling framework enables learning different movement patterns through a state-space representation with particle-MCMC methods for fully Bayesian model fitting and the prediction of future animal movement behaviors.

Publication type Article
Publication Subtype Journal Article
Title Agent-based models for collective animal movement: Proximity-induced state switching
Series title Journal of Agricultural, Biological and Environmental Statistics
DOI 10.1007/s13253-021-00456-0
Edition Online First
Year Published 2021
Language English
Publisher Springer
Contributing office(s) Northern Rocky Mountain Science Center
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