Models and measures of animal aggregation and dispersal

• Published in: Journal of theoretical biology Vol. 484; p. 110002
• Main Authors: Broom, Mark, Erovenko, Igor V., Rowell, Jonathan T., Rychtář, Jan
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 07.01.2020
• Subjects: Animal movement; Group movement coordination; Habitat choice; Ideal free distribution; Patch selection; Urn models; Urn models; Animal movement; Ideal free distribution; Habitat choice; Patch selection; Group movement coordination; Ideal Free Distribution
• ISSN: 0022-5193; 1095-8541
• DOI: 10.1016/j.jtbi.2019.110002

•We provide a unified model framework for animal aggregation and dispersal.•We provide several measures of group movement coordination.•We fit classical models, such as the Ideal Free Distribution into our framework.•We show how to generate models of movement with specific desirable characteristics. The dispersal of individuals within an animal population will depend upon local properties intrinsic to the environment that differentiate superior from inferior regions as well as properties of the population. Competing concerns can either draw conspecifics together in aggregation, such as collective defence against predators, or promote dispersal that minimizes local densities, for instance to reduce competition for food. In this paper we consider a range of models of non-independent movement. We include established models, such as the ideal free distribution, but also develop novel models, such as the wheel. We also develop several ways to combine different models to create a flexible model of addressing a variety of dispersal mechanisms. We further devise novel measures of movement coordination and show how to generate a population movement that achieves appropriate values of the measure specified. We find the value of these measures for each of the core models described, as well as discuss their use, and potential limitations, in discerning the underlying movement mechanisms. The movement framework that we develop is both of interest as a stand-alone process to explore movement, but also able to generate a variety of movement patterns that can be embedded into wider evolutionary models where movement is not the only consideration.