AuthorsSiepielski, Adam M.
Gotanda, Kiyoko M.
Morrissey, Michael B.
Diamond, Sarah E.
Carlson, Stephanie Marie
KAUST DepartmentRed Sea Research Center (RSRC)
Online Publication Date2013-09-12
Print Publication Date2013-11
Permanent link to this recordhttp://hdl.handle.net/10754/566044
MetadataShow full item record
AbstractLocal adaptation, adaptive population divergence and speciation are often expected to result from populations evolving in response to spatial variation in selection. Yet, we lack a comprehensive understanding of the major features that characterise the spatial patterns of selection, namely the extent of variation among populations in the strength and direction of selection. Here, we analyse a data set of spatially replicated studies of directional phenotypic selection from natural populations. The data set includes 60 studies, consisting of 3937 estimates of selection across an average of five populations. We performed meta-analyses to explore features characterising spatial variation in directional selection. We found that selection tends to vary mainly in strength and less in direction among populations. Although differences in the direction of selection occur among populations they do so where selection is often weakest, which may limit the potential for ongoing adaptive population divergence. Overall, we also found that spatial variation in selection appears comparable to temporal (annual) variation in selection within populations; however, several deficiencies in available data currently complicate this comparison. We discuss future research needs to further advance our understanding of spatial variation in selection. © 2013 John Wiley & Sons Ltd/CNRS.
CitationSiepielski, A. M., Gotanda, K. M., Morrissey, M. B., Diamond, S. E., DiBattista, J. D., & Carlson, S. M. (2013). The spatial patterns of directional phenotypic selection. Ecology Letters, 16(11), 1382–1392. doi:10.1111/ele.12174
SponsorsWe thank C. Benkman and M. McPeek for enlightening discussion on the nature of selection as well as comments on an earlier version of this manuscript. We also appreciate the insightful and helpful comments by three anonymous reviewers that improved the work presented here. AMS was supported by NSF (DEB-1255318). KMG was funded by a Vanier Canada Graduate Scholarship from NSERC and a doctoral scholarship from FQRNT. SMC was supported in part by NSF (DBI-0630626).
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