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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
Indirect genetics effects and evolutionary constraint: An analysis of social dominance in red deer, Cervus elaphus
Journal of Evolutionary Biology, Volume 24, No. 4, Year 2011
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Description
By determining access to limited resources, social dominance is often an important determinant of fitness. Thus, if heritable, standard theory predicts mean dominance should evolve. However, dominance is usually inferred from the tendency to win contests, and given one winner and one loser in any dyadic contest, the mean proportion won will always equal 0.5. Here, we argue that the apparent conflict between quantitative genetic theory and common sense is resolved by recognition of indirect genetic effects (IGEs). We estimate selection on, and genetic (co)variance structures for, social dominance, in a wild population of red deer Cervus elaphus, on the Scottish island of Rum. While dominance is heritable and positively correlated with lifetime fitness, contest outcomes depend as much on the genes carried by an opponent as on the genotype of a focal individual. We show how this dependency imposes an absolute evolutionary constraint on the phenotypic mean, thus reconciling theoretical predictions with common sense. More generally, we argue that IGEs likely provide a widespread but poorly recognized source of evolutionary constraint for traits influenced by competition. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.
Authors & Co-Authors
Morrissey, Michael B.
United Kingdom, Edinburgh
The University of Edinburgh
Adams, Mark James
United Kingdom, Edinburgh
The University of Edinburgh
Walling, Craig A.
United Kingdom, Edinburgh
The University of Edinburgh
Pemberton, Josephine M.
United Kingdom, Edinburgh
The University of Edinburgh
Clutton-Brock, Tim H.
United Kingdom, Cambridge
University of Cambridge
Kruuk, Loeske E.B.
United Kingdom, Edinburgh
The University of Edinburgh
Statistics
Citations: 127
Authors: 6
Affiliations: 2
Identifiers
Doi:
10.1111/j.1420-9101.2010.02212.x
ISSN:
14209101
Research Areas
Genetics And Genomics
Health System And Policy
Study Design
Cross Sectional Study
Study Approach
Quantitative