ArticleNature ecology & evolution2022
Decomposing phenotypic skew and its effects on the predicted response to strong selection.
Article in Nature ecology & evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Genetic Parameter Estimation of White Spot Traits in the Carapace of Swimming CrabAnimals : an open access journal from MDPI · 2026Article
- New approaches to meta-analyze differences in skewness, kurtosis, and correlation.PLoS biology · 2026Article
- Estimating (Non)Linear Selection on Reaction Norms: A General Framework for Labile Traits.Ecology and evolution · 2025Article
- Dynamical BLUP modeling of reaction norm evolution, accommodating changing environments, overlapping generations, and multivariate data.Ecology and evolution · 2023Article
- Weaklings make trouble.Nature ecology & evolution · 2022Article
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Authors and funding
4 authors.
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Abstract
The major frameworks for predicting evolutionary change assume that a phenotype's underlying genetic and environmental components are normally distributed. However, the predictions of these frameworks may no longer hold if distributions are skewed. Despite this, phenotypic skew has never been decomposed, meaning the fundamental assumptions of quantitative genetics remain untested. Here we demonstrate that the substantial phenotypic skew in the body size of juvenile blue tits (Cyanistes caeruleus) is driven by environmental factors. Although skew had little impact on our predictions of selection response in this case, our results highlight the impact of skew on the estimation of inheritance and selection. Specifically, the nonlinear parent-offspring regressions induced by skew, alongside selective disappearance, can strongly bias estimates of heritability. The ubiquity of skew and strong directional selection on juvenile body size imply that heritability is commonly overestimated, which may in part explain the discrepancy between predicted and observed trait evolution.
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