Reducing environmental bias when measuring natural selection.

Published

Journal Article

Crucial to understanding the process of natural selection is characterizing phenotypic selection. Measures of phenotypic selection can be biased by environmental variation among individuals that causes a spurious correlation between a trait and fitness. One solution is analyzing genotypic data, rather than phenotypic data. Genotypic data, however, are difficult to gather, can be gathered from few species, and typically have low statistical power. Environmental correlations may act through traits other than through fitness itself. A path analytic framework, which includes measures of such traits, may reduce environmental bias in estimates of selection coefficients. We tested the efficacy of path analysis to reduce bias by re-analyzing three experiments where both phenotypic and genotypic data were available. All three consisted of plant species (Impatiens capensis, Arabidopsis thaliana, and Raphanus sativus) grown in experimental plots or the greenhouse. We found that selection coefficients estimated by path analysis using phenotypic data were highly correlated with those based on genotypic data with little systematic bias in estimating the strength of selection. Although not a panacea, using path analysis can substantially reduce environmental biases in estimates of selection coefficients. Such confidence in phenotypic selection estimates is critical for progress in the study of natural selection.

Full Text

Duke Authors

Cited Authors

  • Scheiner, SM; Donohue, K; Dorn, LA; Mazer, SJ; Wolfe, LM

Published Date

  • November 2002

Published In

Volume / Issue

  • 56 / 11

Start / End Page

  • 2156 - 2167

PubMed ID

  • 12487346

Pubmed Central ID

  • 12487346

Electronic International Standard Serial Number (EISSN)

  • 1558-5646

International Standard Serial Number (ISSN)

  • 0014-3820

Digital Object Identifier (DOI)

  • 10.1111/j.0014-3820.2002.tb00140.x

Language

  • eng