Document Type
Article
Publication Date
6-1-2015
Description
In this paper, we discuss methods for developing a stochastic model which incorporates behavior differences in the predation movements of Anelosimus studiosus (a subsocial spider). Stochastic models for animal movement and, in particular, spider predation movement have been developed previously; however, this paper focuses on the development and implementation of the necessary mathematical and statistical methods required to expand such a model in order to capture a variety of distinct behaviors. A least squares optimization algorithm is used for parameter estimation to fit a single stochastic model to an individual spider during predation resulting in unique parameter values for each spider. Similarities and variations between parameter values across the spiders are analyzed and used to estimate probability distributions for the variable parameter values. An aggregate stochastic model is then created which incorporates the individual dynamics. The comparison between the optimal individual models to the aggregate model indicate the methodology and algorithm developed in this paper are appropriate for simulating a range of individualistic behaviors.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Citation Information
Quijano, Alex John; Joyner, Michele L.; Seier, Edith; Hancock, Nathaniel; Largent, Michael; and Jones, Thomas C.. 2015. An Aggregate Stochastic Model Incorporating Individual Dynamics for Predation Movements of Anelosimus Studiosus. Mathematical Biosciences and Engineering. Vol.12(3). 585-607. https://doi.org/10.3934/mbe.2015.12.585 PMID: 25811547 ISSN: 1547-1063
Copyright Statement
2015 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)