Performance of individual vs. group sampling for inferring dispersal under isolation-by-distance.

Details

Serval ID
serval:BIB_B0BC81B064B5
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Performance of individual vs. group sampling for inferring dispersal under isolation-by-distance.
Journal
Molecular Ecology Resources
Author(s)
Luximon N., Petit E.J., Broquet T.
ISSN
1755-0998 (Electronic)
ISSN-L
1755-098X
Publication state
Published
Issued date
2014
Peer-reviewed
Oui
Volume
14
Number
4
Pages
745-752
Language
english
Notes
Publication types: Comparative Study ; Evaluation Studies ; Journal Article ; Research Support, Non-U.S. Gov'tPublication Status: ppublish
Abstract
Models of isolation-by-distance formalize the effects of genetic drift and gene flow in a spatial context where gene dispersal is spatially limited. These models have been used to show that, at an appropriate spatial scale, dispersal parameters can be inferred from the regression of genetic differentiation against geographic distance between sampling locations. This approach is compelling because it is relatively simple and robust and has rather low sampling requirements. In continuous populations, dispersal can be inferred from isolation-by-distance patterns using either individuals or groups as sampling units. Intrigued by empirical findings where individual samples seemed to provide more power, we used simulations to compare the performances of the two methods in a range of situations with different dispersal distributions. We found that sampling individuals provide more power in a range of dispersal conditions that is narrow but fits many realistic situations. These situations were characterized not only by the general steepness of isolation-by-distance but also by the intrinsic shape of the dispersal kernel. The performances of the two approaches are otherwise similar, suggesting that the choice of a sampling unit is globally less important than other settings such as a study's spatial scale.
Keywords
Demography, Genetic Variation, Genetics, Population/methods, Sampling Studies
Pubmed
Web of science
Create date
18/10/2016 16:08
Last modification date
20/08/2019 15:19
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