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Detalle de: Assessing population structure in the face of isolation by distance: Are we neglecting the problem?

Title Assessing population structure in the face of isolation by distance: Are we neglecting the problem?
Abstract

Aim To investigate how the potential bias from isolation by distance ( IBD ) in inferences of population structure has been addressed, in studies aiming biodiversity conservation. Location Global. Methods We reviewed the literature on the impact of IBD on the performance of the widely used software structure . We also performed a literature survey in the Web of Knowledge to assess how data have been analysed in biodiversity conservation studies when IBD is detected. Results By reviewing the literature on structure performance in IBD data sets, we found a high number of studies showing that structure outputs are extremely affected by IBD . This misleading inference results principally in the detection of artificial genetic clusters. The literature survey showed that IBD was present in most data sets (60.56%) and that a substantial number of the articles only tested IBD by Mantel tests (82.21%). The most concerning result is that several articles have been using structure even after detecting IBD (57.99%), and a substantial number of them are drawing formal conservation strategies, notwithstanding the potentially biased results (51.49%). Main conclusions Our results are of great concern, as conservation strategies may be distinct under different population structure, and its success can be affected by the incorrect identification of populations. We recommend possible stages to be considered in the presence of IBD , which can help conservation investigators before the proposition of explicit conservation strategies.

Apa Reference Perez, M.F., Franco, F.F., Bombonato, J.R., Bonatelli, I.A.S., Khan, G., Romeiro‐Brito, M., Fegies, A.C., Ribeiro, P.M., Silva, G.A.R. & Moraes, E.M. (2018). Assessing population structure in the face of isolation by distance: Are we neglecting the problem?. Diversity and Distributions, 24(12), 1883-1889. 10.1111/ddi.12816
Doi 10.1111/ddi.12816
Publication Date 18 Jul 2018
Publication Type Article
Researcher Manolo Perez
Ontology Bioinformatics Software and Tools, Population genomics
Research Groups
Tools

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