@article{McDonald2017-11Assor-40822,
  year={2017},
  doi={10.1111/evo.13365},
  title={Assortment and the analysis of natural selection on social traits},
  number={11},
  volume={71},
  issn={0014-3820},
  journal={Evolution : international journal of organic evolution},
  pages={2693--2702},
  author={McDonald, Grant C. and Farine, Damien R. and Foster, Kevin R. and Biernaskie, Jay M.}
}

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    <dc:creator>McDonald, Grant C.</dc:creator>
    <dc:contributor>Foster, Kevin R.</dc:contributor>
    <dc:language>eng</dc:language>
    <dcterms:title>Assortment and the analysis of natural selection on social traits</dcterms:title>
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    <dc:creator>Farine, Damien R.</dc:creator>
    <dc:creator>Biernaskie, Jay M.</dc:creator>
    <dc:contributor>Farine, Damien R.</dc:contributor>
    <dc:contributor>Biernaskie, Jay M.</dc:contributor>
    <dc:creator>Foster, Kevin R.</dc:creator>
    <dcterms:abstract xml:lang="eng">A central problem in evolutionary biology is to determine whether and how social interactions contribute to natural selection. A key method for phenotypic data is social selection analysis, in which fitness effects from social partners contribute to selection only when there is a correlation between the traits of individuals and their social partners (nonrandom phenotypic assortment). However, there are inconsistencies in the use of social selection that center around the measurement of phenotypic assortment. Here, we use data analysis and simulations to resolve these inconsistencies, showing that: (i) not all measures of assortment are suitable for social selection analysis; and (ii) the interpretation of assortment, and how to detect nonrandom assortment, will depend on the scale at which it is measured. We discuss links to kin selection theory and provide a practical guide for the social selection approach.</dcterms:abstract>
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    <dc:contributor>McDonald, Grant C.</dc:contributor>
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