Cargando…
Consequences of population topology for studying gene flow using link‐based landscape genetic methods
Many landscape genetic studies aim to determine the effect of landscape on gene flow between populations. These studies frequently employ link‐based methods that relate pairwise measures of historical gene flow to measures of the landscape and the geographical distance between populations. However,...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5528204/ https://www.ncbi.nlm.nih.gov/pubmed/28770047 http://dx.doi.org/10.1002/ece3.3075 |
_version_ | 1783253022346838016 |
---|---|
author | van Strien, Maarten J. |
author_facet | van Strien, Maarten J. |
author_sort | van Strien, Maarten J. |
collection | PubMed |
description | Many landscape genetic studies aim to determine the effect of landscape on gene flow between populations. These studies frequently employ link‐based methods that relate pairwise measures of historical gene flow to measures of the landscape and the geographical distance between populations. However, apart from landscape and distance, there is a third important factor that can influence historical gene flow, that is, population topology (i.e., the arrangement of populations throughout a landscape). As the population topology is determined in part by the landscape configuration, I argue that it should play a more prominent role in landscape genetics. Making use of existing literature and theoretical examples, I discuss how population topology can influence results in landscape genetic studies and how it can be taken into account to improve the accuracy of these results. In support of my arguments, I have performed a literature review of landscape genetic studies published during the first half of 2015 as well as several computer simulations of gene flow between populations. First, I argue why one should carefully consider which population pairs should be included in link‐based analyses. Second, I discuss several ways in which the population topology can be incorporated in response and explanatory variables. Third, I outline why it is important to sample populations in such a way that a good representation of the population topology is obtained. Fourth, I discuss how statistical testing for link‐based approaches could be influenced by the population topology. I conclude the article with six recommendations geared toward better incorporating population topology in link‐based landscape genetic studies. |
format | Online Article Text |
id | pubmed-5528204 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-55282042017-08-02 Consequences of population topology for studying gene flow using link‐based landscape genetic methods van Strien, Maarten J. Ecol Evol Hypotheses Many landscape genetic studies aim to determine the effect of landscape on gene flow between populations. These studies frequently employ link‐based methods that relate pairwise measures of historical gene flow to measures of the landscape and the geographical distance between populations. However, apart from landscape and distance, there is a third important factor that can influence historical gene flow, that is, population topology (i.e., the arrangement of populations throughout a landscape). As the population topology is determined in part by the landscape configuration, I argue that it should play a more prominent role in landscape genetics. Making use of existing literature and theoretical examples, I discuss how population topology can influence results in landscape genetic studies and how it can be taken into account to improve the accuracy of these results. In support of my arguments, I have performed a literature review of landscape genetic studies published during the first half of 2015 as well as several computer simulations of gene flow between populations. First, I argue why one should carefully consider which population pairs should be included in link‐based analyses. Second, I discuss several ways in which the population topology can be incorporated in response and explanatory variables. Third, I outline why it is important to sample populations in such a way that a good representation of the population topology is obtained. Fourth, I discuss how statistical testing for link‐based approaches could be influenced by the population topology. I conclude the article with six recommendations geared toward better incorporating population topology in link‐based landscape genetic studies. John Wiley and Sons Inc. 2017-06-02 /pmc/articles/PMC5528204/ /pubmed/28770047 http://dx.doi.org/10.1002/ece3.3075 Text en © 2017 The Author. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Hypotheses van Strien, Maarten J. Consequences of population topology for studying gene flow using link‐based landscape genetic methods |
title | Consequences of population topology for studying gene flow using link‐based landscape genetic methods |
title_full | Consequences of population topology for studying gene flow using link‐based landscape genetic methods |
title_fullStr | Consequences of population topology for studying gene flow using link‐based landscape genetic methods |
title_full_unstemmed | Consequences of population topology for studying gene flow using link‐based landscape genetic methods |
title_short | Consequences of population topology for studying gene flow using link‐based landscape genetic methods |
title_sort | consequences of population topology for studying gene flow using link‐based landscape genetic methods |
topic | Hypotheses |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5528204/ https://www.ncbi.nlm.nih.gov/pubmed/28770047 http://dx.doi.org/10.1002/ece3.3075 |
work_keys_str_mv | AT vanstrienmaartenj consequencesofpopulationtopologyforstudyinggeneflowusinglinkbasedlandscapegeneticmethods |