Testing for environmentally induced bias in phenotypic estimates of natural selection: theory and practice.

Published

Journal Article

Measuring natural selection has been a fundamental goal of evolutionary biology for more than a century, and techniques developed in the last 20 yr have provided relatively simple means for biologists to do so. Many of these techniques, however, share a common limitation: when applied to phenotypic data, environmentally induced covariances between traits and fitness can lead to biased estimates of selection and misleading predictions about evolutionary change. Utilizing estimates of breeding values instead of phenotypic data with these methods can eliminate environmentally induced bias, although this approach is more difficult to implement. Despite this potential limitation to phenotypic methods and the availability of a potential solution, little empirical evidence exists on the extent of environmentally induced bias in phenotypic estimates of selection. In this article, we present a method for detecting bias in phenotypic estimates of selection and demonstrate its use with three independent data sets. Nearly 25% of the phenotypic selection gradients estimated from our data are biased by environmental covariances. We find that bias caused by environmental covariances appears mainly to affect quantitative estimates of the strength of selection based on phenotypic data and that the magnitude of these biases is large. As our estimates of selection are based on data from spatially replicated field experiments, we suggest that our findings on the prevalence of bias caused by environmental covariances are likely to be conservative.

Full Text

Duke Authors

Cited Authors

  • Stinchcombe, JR; Rutter, MT; Burdick, DS; Tiffin, P; Rausher, MD; Mauricio, R

Published Date

  • October 2002

Published In

Volume / Issue

  • 160 / 4

Start / End Page

  • 511 - 523

PubMed ID

  • 18707526

Pubmed Central ID

  • 18707526

Electronic International Standard Serial Number (EISSN)

  • 1537-5323

International Standard Serial Number (ISSN)

  • 0003-0147

Digital Object Identifier (DOI)

  • 10.1086/342069

Language

  • eng