Survivor's dilemma: The evolution of cooperation in volatile environments

Kirk Kayser, Adam Lampert

Research output: Contribution to journalArticlepeer-review

Abstract

The volatility of an environment significantly impacts cooperative behavior. In environments where viability-threatening events occur on a shorter timescale than reproduction, it is reasonable to measure the costs and benefits of cooperation in terms of their direct effect on survival probability. Then, the number of offspring increases with lifespan. With such a model, is it possible for cooperation to be evolutionarily stable, and how does cooperation depend on the benefit and cost of such interactions, and the volatility of the environment? In this paper, we develop an N-player survivor's dilemma in which prisoner's dilemma payoffs in an iteration are survival rates, and expected lifespan is the measure of reproductive fitness. We investigate cost, benefit, and volatility parameter ranges where various cooperative behaviors may occur. We observe that free-riding results in indirect punishment as the cheated partner's early death leaves the defector vulnerable. For 2- and 3-player versions of the game, we identify parameter regions where the repeated game becomes equivalent to a Harmony, Stag Hunt, or Prisoner's Dilemma static game and discuss evolutionary stability. We find that with two individuals, the initial fraction of cooperators necessary for cooperation to be selected for decreases as the benefit to cost ratio increases and as environmental volatility decreases. With the presence of a third individual, there also exists a parameter region where cooperation can invade an initially all-defecting population.

Original languageEnglish (US)
Article number110603
JournalJournal of Theoretical Biology
Volume516
DOIs
StatePublished - May 7 2021

Keywords

  • Density-dependent cooperation
  • Evolutionarily stable strategies
  • Evolutionary game theory
  • Prisoner's dilemma

ASJC Scopus subject areas

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

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