Altruism in a volatile world

  • Nature volume 555, pages 359362 (15 March 2018)
  • doi:10.1038/nature25965
  • Download Citation


The evolution of altruism—costly self-sacrifice in the service of others—has puzzled biologists1 since The Origin of Species. For half a century, attempts to understand altruism have developed around the concept that altruists may help relatives to have extra offspring in order to spread shared genes2. This theory—known as inclusive fitness—is founded on a simple inequality termed Hamilton’s rule2. However, explanations of altruism have typically not considered the stochasticity of natural environments, which will not necessarily favour genotypes that produce the greatest average reproductive success3,4. Moreover, empirical data across many taxa reveal associations between altruism and environmental stochasticity5,6,7,8, a pattern not predicted by standard interpretations of Hamilton’s rule. Here we derive Hamilton’s rule with explicit stochasticity, leading to new predictions about the evolution of altruism. We show that altruists can increase the long-term success of their genotype by reducing the temporal variability in the number of offspring produced by their relatives. Consequently, costly altruism can evolve even if it has a net negative effect on the average reproductive success of related recipients. The selective pressure on volatility-suppressing altruism is proportional to the coefficient of variation in population fitness, and is therefore diminished by its own success. Our results formalize the hitherto elusive link between bet-hedging and altruism4,9,10,11, and reveal missing fitness effects in the evolution of animal societies.

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We thank A. Gardner for discussions in the early stages of this work, and P.K. thanks the Behaviour Discussion Group at the Smithsonian Tropical Research Institute in Panama for the opportunity to present and discuss these ideas. We thank S. Schindler, S. Okasha, B. Autzen, J. McNamara and M. Bentley for comments on the project. P.K. was supported by the National Geographic Society (GEF-NE 145-15) and a University of Bristol Research Studentship, A.D.H. by the Natural Environment Research Council (NE/L011921/1), A.N.R. by a European Research Council Consolidator Grant (award no. 682253) and S.S. by the Natural Environment Research Council (NE/M012913/2).

Author information


  1. School of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol BS8 1TQ, UK

    • Patrick Kennedy
    •  & Andrew N. Radford
  2. Centre for Research in Animal Behaviour, College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4QG, UK

    • Andrew D. Higginson
  3. Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, UK

    • Seirian Sumner


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P.K. conceived the idea, P.K. and A.D.H. performed the modelling, A.N.R. and S.S. supervised the project. All authors discussed the ideas and wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Patrick Kennedy.

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Extended data

Supplementary information

PDF files

  1. 1.

    Life Sciences Reporting Summary

  2. 2.

    Supplementary Information

    This file contains Supplementary Information Appendices A-C. Appendix A contains derivations of the main text equations. Appendix B contains information on obtaining benefits and costs and Appendix C provides illustrative examples. These three appendices are merged into a single .pdf file.

Text files

  1. 1.

    Supplementary Data

    This file contains Supplementary Appendix D1, the MATLAB code for simulation detailed in Appendix B.

  2. 2.

    Supplementary Data

    This file contains Supplementary Appendix D2, the MATLAB code for simulation detailed in Appendix C.


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