Abstract

In the context of social evolution, the ecological drivers of selection are the phenotypes of other individuals. The social environment can thus evolve, potentially changing the adaptive value for different social strategies. Different branches of evolutionary biology have traditionally focused on different aspects of these feedbacks. Here, we synthesize behavioral ecology theory concerning evolutionarily stable strategies when fitness is frequency dependent with quantitative genetic models providing statistical descriptions of evolutionary responses to social selection. Using path analyses, we review how social interactions influence the strength of selection and how social responsiveness, social impact, and non-random social assortment affect responses to social selection. We then detail how the frequency-dependent nature of social interactions fits into this framework and how it imposes selection on traits mediating social responsiveness, social impact, and social assortment, further affecting evolutionary dynamics. Throughout, we discuss the parameters in quantitative genetics models of social evolution from a behavioral ecology perspective and identify their statistical counterparts in empirical studies. This integration of behavioral ecology and quantitative genetic perspectives should lead to greater clarity in the generation of hypotheses and more focused empirical research regarding evolutionary pathways and feedbacks inherent in specific social interactions.

Document Type

Review

Publication Date

9-2020

Notes/Citation Information

Published in Evolution, v. 74, issue 9.

© 2020 The Authors

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Digital Object Identifier (DOI)

https://doi.org/10.1111/evo.14054

Funding Information

This work was also partly supported by the U.S. National Science Foundation and the Research Council of Norway through its Centres of Excellence funding scheme (SFF-III 223257/F50) and the research grant spatdif (274930).

Related Content

The code to generate the data that supports the findings of this study is available on https://github.com/YimenAraya-Ajoy/SocialEvolutionPathways.

evo14054-sup-0001-suppmat.docx (455 kB)
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