Spatial social dilemmas promote diversity.

Christoph Hauert, Michael Doebeli
Author Information
  1. Christoph Hauert: Department of Mathematics, University of British Columbia, Vancouver, BC V6T 1Z2, Canada; hauert@math.ubc.ca. ORCID
  2. Michael Doebeli: Department of Mathematics, University of British Columbia, Vancouver, BC V6T 1Z2, Canada.

Abstract

Cooperative investments in social dilemmas can spontaneously diversify into stably coexisting high and low contributors in well-mixed populations. Here we extend the analysis to emerging diversity in (spatially) structured populations. Using pair approximation, we derive analytical expressions for the invasion fitness of rare mutants in structured populations, which then yields a spatial adaptive dynamics framework. This allows us to predict changes arising from population structures in terms of existence and location of singular strategies, as well as their convergence and evolutionary stability as compared to well-mixed populations. Based on spatial adaptive dynamics and extensive individual-based simulations, we find that spatial structure has significant and varied impacts on evolutionary diversification in continuous social dilemmas. More specifically, spatial adaptive dynamics suggests that spontaneous diversification through evolutionary branching is suppressed, but simulations show that spatial dimensions offer new modes of diversification that are driven by an interplay of finite-size mutations and population structures. Even though spatial adaptive dynamics is unable to capture these new modes, they can still be understood based on an invasion analysis. In particular, population structures alter invasion fitness and can open up new regions in trait space where mutants can invade, but that may not be accessible to small mutational steps. Instead, stochastically appearing larger mutations or sequences of smaller mutations in a particular direction are required to bridge regions of unfavorable traits. The net effect is that spatial structure tends to promote diversification, especially when selection is strong.

Keywords

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MeSH Term

Biodiversity
Biological Evolution
Models, Genetic
Mutation
Prisoner Dilemma

Word Cloud

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