IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v129y2019icp126-132.html
   My bibliography  Save this article

Mutual altruism and long-term optimization of the inclusive fitness in multilocus genetic systems

Author

Listed:
  • Eshel, Ilan

Abstract

The dynamics of long-term evolution in a complex genetically-structured population with a flux of random mutations is employed here to study the evolution of mutual altruism between relatives that are encountered repeatedly, where the level of altruism is measured by the risk one is willing to accept in order to save the life of one’s relative. It is shown that regardless of the number of loci involved, of the rates of recombination among them, and of the intensity of the selection forces, the long-term dynamics can phenotypically converge only to a level of altruism that maximizes the individual inclusive fitness as it has previously defined by students of the individual approach to evolution. Except for the widely studied case of weak selection, however, the convergence to such a level of altruism is not necessarily generation-to-next monotone. It is further shown that, unlike the case of the one-shot encounter, repeated encounters between relatives allow for more than one level of altruism which may maximize the inclusive fitness, in which case not all such levels of altruism are evolutionarily accessible.

Suggested Citation

  • Eshel, Ilan, 2019. "Mutual altruism and long-term optimization of the inclusive fitness in multilocus genetic systems," Theoretical Population Biology, Elsevier, vol. 129(C), pages 126-132.
  • Handle: RePEc:eee:thpobi:v:129:y:2019:i:c:p:126-132
    DOI: 10.1016/j.tpb.2018.10.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580918301187
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tpb.2018.10.005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:thpobi:v:129:y:2019:i:c:p:126-132. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.