Literature DB >> 18707526

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

John R Stinchcombe1, Matthew T Rutter, Donald S Burdick, Peter Tiffin, Mark D Rausher, Rodney Mauricio.   

Abstract

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.

Year:  2002        PMID: 18707526     DOI: 10.1086/342069

Source DB:  PubMed          Journal:  Am Nat        ISSN: 0003-0147            Impact factor:   3.926


  35 in total

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2.  Natural selection on light response curve parameters in the herbaceous annual, Impatiens capensis.

Authors:  M Shane Heschel; John R Stinchcombe; Kent E Holsinger; Johanna Schmitt
Journal:  Oecologia       Date:  2004-04-09       Impact factor: 3.225

3.  Viability selection prior to trait expression is an essential component of natural selection.

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Journal:  Proc Biol Sci       Date:  2010-05-12       Impact factor: 5.349

4.  Estimating evolutionary parameters when viability selection is operating.

Authors:  Jarrod D Hadfield
Journal:  Proc Biol Sci       Date:  2008-03-22       Impact factor: 5.349

5.  Polymorphic genes of major effect: consequences for variation, selection and evolution in Arabidopsis thaliana.

Authors:  John R Stinchcombe; Cynthia Weinig; Katy D Heath; Marcus T Brock; Johanna Schmitt
Journal:  Genetics       Date:  2009-05-04       Impact factor: 4.562

6.  How much do genetic covariances alter the rate of adaptation?

Authors:  Aneil F Agrawal; John R Stinchcombe
Journal:  Proc Biol Sci       Date:  2009-03-22       Impact factor: 5.349

7.  Evolutionary optimum for male sexual traits characterized using the multivariate Robertson-Price Identity.

Authors:  Matthieu Delcourt; Mark W Blows; J David Aguirre; Howard D Rundle
Journal:  Proc Natl Acad Sci U S A       Date:  2012-05-21       Impact factor: 11.205

8.  Dominance genetic variance for traits under directional selection in Drosophila serrata.

Authors:  Jacqueline L Sztepanacz; Mark W Blows
Journal:  Genetics       Date:  2015-03-16       Impact factor: 4.562

9.  Evolution caused by extreme events.

Authors:  Peter R Grant; B Rosemary Grant; Raymond B Huey; Marc T J Johnson; Andrew H Knoll; Johanna Schmitt
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-06-19       Impact factor: 6.237

10.  Non-additive effects of genotypic diversity increase floral abundance and abundance of floral visitors.

Authors:  Mark A Genung; Jean-Philippe Lessard; Claire B Brown; Windy A Bunn; Melissa A Cregger; W M Nicholas Reynolds; Emmi Felker-Quinn; Mary L Stevenson; Amanda S Hartley; Gregory M Crutsinger; Jennifer A Schweitzer; Joseph K Bailey
Journal:  PLoS One       Date:  2010-01-14       Impact factor: 3.240

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