Literature DB >> 24758351

Pathways to social evolution: reciprocity, relatedness, and synergy.

Jeremy Van Cleve1, Erol Akçay.   

Abstract

Many organisms live in populations structured by space and by class, exhibit plastic responses to their social partners, and are subject to nonadditive ecological and fitness effects. Social evolution theory has long recognized that all of these factors can lead to different selection pressures but has only recently attempted to synthesize how these factors interact. Using models for both discrete and continuous phenotypes, we show that analyzing these factors in a consistent framework reveals that they interact with one another in ways previously overlooked. Specifically, behavioral responses (reciprocity), genetic relatedness, and synergy interact in nontrivial ways that cannot be easily captured by simple summary indices of assortment. We demonstrate the importance of these interactions by showing how they have been neglected in previous synthetic models of social behavior both within and between species. These interactions also affect the level of behavioral responses that can evolve in the long run; proximate biological mechanisms are evolutionarily stable when they generate enough responsiveness relative to the level of responsiveness that exactly balances the ecological costs and benefits. Given the richness of social behavior across taxa, these interactions should be a boon for empirical research as they are likely crucial for describing the complex relationship linking ecology, demography, and social behavior.
© 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Entities:  

Keywords:  Behavioral responses; class structure; cooperation; genetic assortment; nonadditive fitness

Mesh:

Year:  2014        PMID: 24758351     DOI: 10.1111/evo.12438

Source DB:  PubMed          Journal:  Evolution        ISSN: 0014-3820            Impact factor:   3.694


  15 in total

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9.  Social animal models for quantifying plasticity, assortment, and selection on interacting phenotypes.

Authors:  Jordan S Martin; Adrian V Jaeggi
Journal:  J Evol Biol       Date:  2021-07-22       Impact factor: 2.516

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