Literature DB >> 28564514

VISUALIZING MULTIVARIATE SELECTION.

Patrick C Phillips1, Stevan J Arnold1.   

Abstract

Recent developments in quantitative-genetic theory have shown that natural selection can be viewed as the multivariate relationship between fitness and phenotype. This relationship can be described by a multidimensional surface depicting fitness as a function of phenotypic traits. We examine the connection between this surface and the coefficients of phenotypic selection that can be estimated by multiple regression and show how the interpretation of multivariate selection can be facilitated through the use of the method of canonical analysis. The results from this analysis can be used to visualize the surface implied by a set of selection coefficients. Such a visualization provides a compact summary of selection coefficients, can aid in the comparison of selection surfaces, and can help generate testable hypotheses as to the adaptive significance of the traits under study. Further, we discuss traditional definitions of directional, stabilizing, and disruptive selection and conclude that selection may be more usefully classified into two general modes, directional and nonlinear selection, with stabilizing and disruptive selection as special cases of nonlinear selection. © 1989 The Society for the Study of Evolution.

Entities:  

Year:  1989        PMID: 28564514     DOI: 10.1111/j.1558-5646.1989.tb02569.x

Source DB:  PubMed          Journal:  Evolution        ISSN: 0014-3820            Impact factor:   3.694


  39 in total

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4.  MIPoD: a hypothesis-testing framework for microevolutionary inference from patterns of divergence.

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7.  The onset of ecological diversification 50 years after colonization of a crater lake by haplochromine cichlid fishes.

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9.  Individual fitness and phenotypic selection in age-structured populations with constant growth rates.

Authors:  Jacob A Moorad
Journal:  Ecology       Date:  2014-04       Impact factor: 5.499

10.  Selection gradients, the opportunity for selection, and the coefficient of determination.

Authors:  Jacob A Moorad; Michael J Wade
Journal:  Am Nat       Date:  2013-01-28       Impact factor: 3.926

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