Evolution of dispersal in explicitly spatial metacommunities

Rachata Muneepeerakul, Sandro Azaele, Simon A. Levin, Andrea Rinaldo, I. Rodriguez-Iturbe Ignacio

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

We apply an evolutionary game theoretic approach to the evolution of dispersal in explicitly spatial metacommunities, using a flexible parametric class of dispersal kernels, namely 2Dt kernels, and study the resulting evolutionary dynamics and outcomes. We observe strong selective pressure on mean dispersal distance (i.e., the first moment), and weaker, but significant, one on the shape of dispersal kernel (i.e., higher moments). We investigate the effects of landscape topology and spatial heterogeneity on the resulting 'optimal' dispersal kernels. The shape-importantly the tail structure-and stability of evolutionarily optimal dispersal strategies are strongly affected by landscape topology or connectivity. Specifically, the results suggest that the optimal dispersal kernels in the river network topology have heavier tails and are stable, while those in the direct topology, where organisms are allowed to travel directly from one location to another, have relatively thin tails and may be unstable. We also find that habitat spatial heterogeneity enables coexistence and controls spatial distribution of distinct groups of dispersal strategies and that alteration in topology alone may not be sufficient to change such coexistence. This work provides a tool to translate environmental changes such as global climate change and human intervention into changes in dispersal behavior, which in turn may lead to important alterations of biodiversity and biological invasion patterns.

Original languageEnglish (US)
Pages (from-to)256-265
Number of pages10
JournalJournal of Theoretical Biology
Volume269
Issue number1
DOIs
StatePublished - Jan 21 2011
Externally publishedYes

Keywords

  • Dispersal
  • Evolutionary game
  • Metacommunity
  • Spatial
  • Topology

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • General Biochemistry, Genetics and Molecular Biology
  • General Immunology and Microbiology
  • General Agricultural and Biological Sciences
  • Applied Mathematics

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