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International Conference on Complex Systems (ICCS2006)

Effect of space on a multi-species community model with individual-based dynamics

Elise Filotas
Complex Systems Laboratory, Department of Geography, Univers

Lael Parrott
Complex Systems Laboratory, Department of Geography, Université de Montréal, Canada

Martin Grant
Department of Physics, McGill University, Canada

     Full text: Not available
     Last modified: February 1, 2006

Abstract
We investigate the dynamics of a community of multiple interacting species in a spatial environment using an individual-based model. The model is inspired from recent non-spatial models of biological coevolution such as the Tangled Nature model. Each species is represented by a genome in the form of a finite vector of bits and evolves via asexual reproduction. Interactions between species are defined through a fixed matrix of randomly distributed elements. The addition of spatial degrees of freedom to models of population dynamics is known to generate new phenomena not defined at the scale of individual interactions. In this perspective, our objective was to verify if the outcomes of a non-spatial coevolution model still hold when space is made explicit. Hence, our model is characterized by the distribution of the biological community over space. The community is spread on a grid and every individual in a cell interacts with other members located in the same cell. A species reproduction probability is a function of how well it interacts locally with other species and is a function of their population sizes. We call this probability the species fitness. Therefore the fitness is spatially dependent. Motion through space (dispersal) occurs for individuals with fitnesses lower than a specified threshold pm. This rule allows unfit individuals to move to neighboring cells in hope of finding a more suitable habitat. We discuss the dynamics of the spatial community as a function of the threshold pm. As individuals reproduce and move through space, self-organized spatial patterns and temporal population dynamics emerge that are markedly different form the non-spatial model.




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