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Social evolution under demographic stochasticity

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  • David V McLeod
  • Troy Day

Abstract

How social traits such as altruism and spite evolve remains an open question in evolutionary biology. One factor thought to be potentially important is demographic stochasticity. Here we provide a general theoretical analysis of the role of demographic stochasticity in social evolution. We show that the evolutionary impact of stochasticity depends on how the social action alters the recipient’s life cycle. If the action alters the recipient’s death rate, then demographic stochasticity always favours altruism and disfavours spite. On the other hand, if the action alters the recipient’s birth rate, then stochasticity can either favour or disfavour both altruism and spite depending on the ratio of the rate of population turnover to the population size. Finally, we also show that this ratio is critical to determining if demographic stochasticity can reverse the direction of selection upon social traits. Our analysis thus provides a general understanding of the role of demographic stochasticity in social evolution.Author summary: Explaining the evolution of social traits such as altruism and spite remains a key outstanding problem in evolutionary biology. Here we develop a simple theory for the effect of demographic stochasticity (random variation in an individual’s birth and death rates) on the evolution of social traits. Our results provide a clear set of predictions: whether a social trait is favoured or disfavoured is determined by how the social action alters the recipient’s life cycle. If the social action alters the recipient’s death rate, then altruism is favoured and spite disfavoured. If instead the social action alters the recipient’s birth rate, then both altruism and spite can be either favoured or disfavoured—the precise outcome depends upon the ratio of the population turnover rate to the population size.

Suggested Citation

  • David V McLeod & Troy Day, 2019. "Social evolution under demographic stochasticity," PLOS Computational Biology, Public Library of Science, vol. 15(2), pages 1-13, February.
  • Handle: RePEc:plo:pcbi00:1006739
    DOI: 10.1371/journal.pcbi.1006739
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