Loading…

A robust new metric of phenotypic distance to estimate and compare multiple trait differences among populations

Whereas a rich literature exists for estimating population genetic divergence, metrics of phenotypic trait divergence are lacking, particularly for comparing multiple traits among three or more populations. Here, we review and analyze via simula- tion Hedges' g, a widely used parametric estimate of...

Full description

Saved in:
Bibliographic Details
Published in:Current zoology 2012-06, Vol.58 (3), p.426-439
Main Authors: Safran, Rebecca, Flaxman, Samuel, Kopp, Michael, Irwin, Darren E., Briggs, Derek, Evans, Matthew R., Funk, W. Chris, Gray, David A., Hebets, Eileen A., Seddon, Nathalie, Scordato, Elizabeth, Symes, Laurel B., Tobias, Joseph A., Toews, David P. L., Uy, J. Albert C.
Format: Article
Language:English
Subjects:
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Whereas a rich literature exists for estimating population genetic divergence, metrics of phenotypic trait divergence are lacking, particularly for comparing multiple traits among three or more populations. Here, we review and analyze via simula- tion Hedges' g, a widely used parametric estimate of effect size. Our analyses indicate that g is sensitive to a combination of unequal trait variances and unequal sample sizes among populations and to changes in the scale of measurement. We then go on to derive and explain a new, non-parametric distance measure, 'Aft', which is caiculated based upon a joint cumulative distribution function (CDF) from all populations under study. More precisely, distances are measured in terms of the percentiles in this CDF at which each population's median lies. Ap combines many desirable features of other distance metrics into a single metric; namely, compared to other metrics, p is relatively insensitive to unequal variances and sample sizes among the populations sam- pied. Furthermore, a key feature of Ap--and our main motivation for developing it--is that it easily accommodates simultaneous comparisons of any number of traits across any number of populations. To exemplify its utility, we employ Ap to address a ques- tion related to the role of sexual selection in speciation: are sexual signals more divergent than ecological traits in closely related taxa? Using traits of known function in closely related populations, we show that traits predictive of reproductive performance are indeed, more divergent and more sexually dimorphic than traits related to ecological adaptation [Current Zoology 58 (3): 426-439 2012].
ISSN:1674-5507
2396-9814
DOI:10.1093/czoolo/58.3.426