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Public goods games in populations with fluctuating size

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  • McAvoy, Alex
  • Fraiman, Nicolas
  • Hauert, Christoph
  • Wakeley, John
  • Nowak, Martin A.

Abstract

Many mathematical frameworks of evolutionary game dynamics assume that the total population size is constant and that selection affects only the relative frequency of strategies. Here, we consider evolutionary game dynamics in an extended Wright–Fisher process with variable population size. In such a scenario, it is possible that the entire population becomes extinct. Survival of the population may depend on which strategy prevails in the game dynamics. Studying cooperative dilemmas, it is a natural feature of such a model that cooperators enable survival, while defectors drive extinction. Although defectors are favored for any mixed population, random drift could lead to their elimination and the resulting pure-cooperator population could survive. On the other hand, if the defectors remain, then the population will quickly go extinct because the frequency of cooperators steadily declines and defectors alone cannot survive. In a mutation–selection model, we find that (i) a steady supply of cooperators can enable long-term population survival, provided selection is sufficiently strong, and (ii) selection can increase the abundance of cooperators but reduce their relative frequency. Thus, evolutionary game dynamics in populations with variable size generate a multifaceted notion of what constitutes a trait’s long-term success.

Suggested Citation

  • McAvoy, Alex & Fraiman, Nicolas & Hauert, Christoph & Wakeley, John & Nowak, Martin A., 2018. "Public goods games in populations with fluctuating size," Theoretical Population Biology, Elsevier, vol. 121(C), pages 72-84.
    • Handle: RePEc:eee:thpobi:v:121:y:2018:i:c:p:72-84
    DOI: 10.1016/j.tpb.2018.01.004
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    References listed on IDEAS

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    1. Jennifer Jacquet & Kristin Hagel & Christoph Hauert & Jochem Marotzke & Torsten Röhl & Manfred Milinski, 2013. "Intra- and intergenerational discounting in the climate game," Nature Climate Change, Nature, vol. 3(12), pages 1025-1028, December.
    2. Veller, Carl & Hayward, Laura K., 2016. "Finite-population evolution with rare mutations in asymmetric games," Journal of Economic Theory, Elsevier, vol. 162(C), pages 93-113.
    3. Bin Wu & Julián García & Christoph Hauert & Arne Traulsen, 2013. "Extrapolating Weak Selection in Evolutionary Games," PLOS Computational Biology, Public Library of Science, vol. 9(12), pages 1-7, December.
    4. Hisashi Ohtsuki & Christoph Hauert & Erez Lieberman & Martin A. Nowak, 2006. "A simple rule for the evolution of cooperation on graphs and social networks," Nature, Nature, vol. 441(7092), pages 502-505, May.
    5. Martin A. Nowak & Akira Sasaki & Christine Taylor & Drew Fudenberg, 2004. "Emergence of cooperation and evolutionary stability in finite populations," Nature, Nature, vol. 428(6983), pages 646-650, April.
    6. Benjamin Allen & Gabor Lippner & Yu-Ting Chen & Babak Fotouhi & Naghmeh Momeni & Shing-Tung Yau & Martin A. Nowak, 2017. "Evolutionary dynamics on any population structure," Nature, Nature, vol. 544(7649), pages 227-230, April.
    7. Erez Lieberman & Christoph Hauert & Martin A. Nowak, 2005. "Evolutionary dynamics on graphs," Nature, Nature, vol. 433(7023), pages 312-316, January.
    8. Bao, Ming & Wild, Geoff, 2012. "Reproductive skew can provide a net advantage in both conditional and unconditional social interactions," Theoretical Population Biology, Elsevier, vol. 82(3), pages 200-208.
    9. Xiaojie Chen & Yongkui Liu & Yonghui Zhou & Long Wang & Matjaž Perc, 2012. "Adaptive and Bounded Investment Returns Promote Cooperation in Spatial Public Goods Games," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-8, May.
    10. Peter D. Taylor & Troy Day & Geoff Wild, 2007. "Evolution of cooperation in a finite homogeneous graph," Nature, Nature, vol. 447(7143), pages 469-472, May.
    11. Mathieu Faure & Sebastian Schreiber, 2014. "Quasi-stationary distributions for randomly perturbed dynamical systems," Post-Print hal-01474257, HAL.
    12. F. Débarre & C. Hauert & M. Doebeli, 2014. "Social evolution in structured populations," Nature Communications, Nature, vol. 5(1), pages 1-7, May.
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