Can natural selection favour altruism between species?

G. A. K. Wyatt*, S. A. West, Andy Gardner

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Darwin suggested that the discovery of altruism between species would annihilate his theory of natural selection. However, it has not been formally shown whether between-species altruism can evolve by natural selection, or why this could never happen. Here, we develop a spatial population genetic model of two interacting species, showing that indiscriminate between species helping can be favoured by natural selection. We then ask if this helping behaviour constitutes altruism between species, using a linear-regression analysis to separate the total action of natural selection into its direct and indirect (kin selected) components. We show that our model can be interpreted in two ways, as either altruism within species, or altruism between species. This ambiguity arises depending on whether or not we treat genes in the other species as predictors of an individual's fitness, which is equivalent to treating these individuals as agents (actors or recipients). Our formal analysis, which focuses upon evolutionary dynamics rather than agents and their agendas, cannot resolve which is the better approach. Nonetheless, because a within-species altruism interpretation is always possible, our analysis supports Darwin's suggestion that natural selection does not favour traits that provide benefits exclusively to individuals of other species.

Original languageEnglish
Pages (from-to)1854-1865
Number of pages12
JournalJournal of Evolutionary Biology
Volume26
Issue number9
DOIs
Publication statusPublished - Sept 2013

Keywords

  • evolutionary graph theory
  • Hamilton's rule
  • inclusive fitness
  • kin selection
  • mutualism
  • relatedness
  • INCLUSIVE FITNESS
  • KIN SELECTION
  • STRONG RECIPROCITY
  • PRICE EQUATION
  • GENERAL-MODEL
  • EVOLUTION
  • MUTUALISM
  • COOPERATION
  • OPTIMIZATION
  • POPULATIONS

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