Evolution of dispersal in a spatially heterogeneous population with finite patch sizes

Parvinen, K. ORCID: https://orcid.org/0000-0001-9125-6041, Ohtsuki, H., & Wakano, J.Y. (2020). Evolution of dispersal in a spatially heterogeneous population with finite patch sizes. Proceedings of the National Academy of Sciences 117 (13) e201915881. 10.1073/pnas.1915881117.

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Abstract

Dispersal is one of the fundamental life-history strategies of organisms, so understanding the selective forces shaping the dispersal traits is important. In the Wright’s island model, dispersal evolves due to kin competition even when dispersal is costly, and it has traditionally been assumed that the living conditions are the same everywhere. To study the effect of spatial heterogeneity, we extend the model so that patches may receive different amounts of immigrants, foster different numbers of individuals, and give different reproduction efficiency to individuals therein. We obtain an analytical expression for the fitness gradient, which shows that directional selection consists of three components: As in the homogeneous case, the direct cost of dispersal selects against dispersal and kin competition promotes dispersal. The additional component, spatial heterogeneity, more precisely the variance of so-called relative reproductive potential, tends to select against dispersal. We also obtain an expression for the second derivative of fitness, which can be used to determine whether there is disruptive selection: Unlike the homogeneous case, we found that divergence of traits through evolutionary branching is possible in the heterogeneous case. Our numerical explorations suggest that evolutionary branching is promoted more by differences in patch size than by reproduction efficiency. Our results show the importance of the existing spatial heterogeneity in the real world as a key determinant in dispersal evolution.

Item Type: Article
Uncontrolled Keywords: dispersal; evolutionarily stable strategy; evolutionary branching; metapopulation model
Research Programs: Evolution and Ecology (EEP)
Depositing User: Luke Kirwan
Date Deposited: 20 Mar 2020 11:40
Last Modified: 27 Aug 2021 17:32
URI: https://pure.iiasa.ac.at/16363

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