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THE PREDICTION OF ADAPTIVE EVOLUTION: EMPIRICAL APPLICATION OF THE SECONDARY THEOREM OF SELECTION AND COMPARISON TO THE BREEDER’S EQUATION
Author(s) -
Morrissey Michael B.,
Parker Darren J.,
Korsten Peter,
Pemberton Josephine M.,
Kruuk Loeske E.B.,
Wilson Alastair J.
Publication year - 2012
Publication title -
evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.84
H-Index - 199
eISSN - 1558-5646
pISSN - 0014-3820
DOI - 10.1111/j.1558-5646.2012.01632.x
Subject(s) - biology , trait , selection (genetic algorithm) , univariate , natural selection , disruptive selection , evolutionary biology , multivariate statistics , covariance , quantitative genetics , statistics , genetic variation , genetics , mathematics , artificial intelligence , computer science , gene , programming language
Adaptive evolution occurs when fitness covaries with genetic merit for a trait (or traits). The breeder’s equation (BE), in both its univariate and multivariate forms, allows us to predict this process by combining estimates of selection on phenotype with estimates of genetic (co)variation. However, predictions are only valid if all factors causal for trait‐fitness covariance are measured. Although this requirement will rarely (if ever) be met in practice, it can be avoided by applying Robertson’s secondary theorem of selection (STS). The STS predicts evolution by directly estimating the genetic basis of trait‐fitness covariation without any explicit model of selection. Here we apply the BE and STS to four morphological traits measured in Soay sheep ( Ovis aries ) from St. Kilda. Despite apparently positive selection on heritable size traits, sheep are not getting larger. However, although the BE predicts increasing size, the STS does not, which is a discrepancy that suggests unmeasured factors are upwardly biasing our estimates of selection on phenotype. We suggest this is likely to be a general issue, and that wider application of the STS could offer at least a partial resolution to the common discrepancy between naive expectations and observed trait dynamics in natural populations.