Details

Autor(en) / Beteiligte

• Ellis, John R.
• Petrovskaya, Natalia B.

Titel

A computational study of density-dependent individual movement and the formation of population clusters in two-dimensional spatial domains

Ist Teil von

• Journal of theoretical biology, 2020-11, Vol.505, p.110421-110421, Article 110421

Ort / Verlag

England: Elsevier Ltd

Erscheinungsjahr

2020

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• •Individual-based model of 2-D density-dependent animal movement is suggested.•The model predicts formation of spatial density clusters.•Cluster properties are investigated subject to parameters of the model.•Spatial metrics alone cannot identify density-dependent movement type correctly. The patterns of collective behaviour in a population emerging from individual animal movement have long been of interest to ecologists, as has the emergence of heterogeneous patterns among a population. In this paper we will consider these phenomena by using an individual-based modelling approach to simulate a population whose individuals undergo density-dependent movement in 2D spatial domains. We first show that the introduction of density-dependent movement in the form of two parameters, a perception radius and a probability of directed movement, leads to the formation of clusters. We then show that the properties of the clusters and their stability over time are different between populations of Brownian and non-Brownian walkers and are also dependent on the choice of parameters. Finally, we consider the effect of the probability of directed movement on the temporal stability of clusters and show that while clusters formed by Brownian and non-Brownian walkers may have similar properties with certain parameter sets, the spatio-temporal dynamics remain different.