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dc.contributor.authorLeroy, G.
dc.contributor.authorCarroll, E. L.
dc.contributor.authorBruford, M. W.
dc.contributor.authorDeWoody, J. A.
dc.contributor.authorStrand, A.
dc.contributor.authorWaits, L.
dc.contributor.authorWang, J.
dc.date.accessioned2017-11-23T16:30:09Z
dc.date.available2017-11-23T16:30:09Z
dc.date.issued2018-08
dc.identifier.citationLeroy , G , Carroll , E L , Bruford , M W , DeWoody , J A , Strand , A , Waits , L & Wang , J 2018 , ' Next-generation metrics for monitoring genetic erosion within populations of conservation concern ' , Evolutionary Applications , vol. 11 , no. 7 , pp. 1066-1083 . https://doi.org/10.1111/eva.12564en
dc.identifier.issn1752-4571
dc.identifier.otherPURE: 251451798
dc.identifier.otherPURE UUID: ad49093f-3c44-4825-b605-74b7f685bd2f
dc.identifier.otherRIS: urn:14E6CE8513649ED2048665E06477330C
dc.identifier.otherRIS: urn:14E6CE8513649ED2048665E06477330C
dc.identifier.otherScopus: 85034744287
dc.identifier.otherWOS: 000439505200004
dc.identifier.urihttps://hdl.handle.net/10023/12161
dc.descriptionThis work was conducted as a part of the Next-generation Genetic Monitoring Working Group at the National Institute for Mathematical and Biological Synthesis, sponsored by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Emma Carrol was supported by a Marie Slodowska Curie Fellowship, (Behaviour-Connect) funded by the EU Horizon2020 program. MWB was supported by a Royal Society Wolfson research merit award. LW was supported by the University of Idaho. This research was supported in part by NSF awards 1355106 and 1357386 to AES.en
dc.description.abstractGenetic erosion is a major threat to biodiversity because it can reduce fitness and ultimately contribute to the extinction of populations. Here, we explore the use of quantitative metrics to detect and monitor genetic erosion. Monitoring systems should not only characterize the mechanisms and drivers of genetic erosion (inbreeding, genetic drift, demographic instability, population fragmentation, introgressive hybridization, selection) but also its consequences (inbreeding and outbreeding depression, emergence of large effect detrimental alleles, maladaptation and loss of adaptability). Technological advances in genomics now allow the production of data the can be measured by new metrics with improved precision, increased efficiency and the potential to discriminate between neutral diversity (shaped mainly by population size and gene-flow) and functional/adaptive diversity (shaped mainly by selection), allowing the assessment of management-relevant genetic markers. The requirements of such studies in terms of sample size and marker density largely depend on the kind of population monitored, the questions to be answered and the metrics employed. We discuss prospects for the integration of this new information and metrics into conservation monitoring programmes.
dc.format.extent18
dc.language.isoeng
dc.relation.ispartofEvolutionary Applicationsen
dc.rights© 2017 Food and Agriculture Organization of the United Nations. © 2017 Evolutionary Applications published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.en
dc.subjectConservationen
dc.subjectMonitoringen
dc.subjectGenomicsen
dc.subjectEffective population sizeen
dc.subjectInbreedingen
dc.subjectAdaptationen
dc.subjectSNPen
dc.subjectQH301 Biologyen
dc.subjectQL Zoologyen
dc.subject.lccQH301en
dc.subject.lccQLen
dc.titleNext-generation metrics for monitoring genetic erosion within populations of conservation concernen
dc.typeJournal itemen
dc.contributor.sponsorEuropean Commissionen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Sea Mammal Research Uniten
dc.identifier.doihttps://doi.org/10.1111/eva.12564
dc.description.statusPeer revieweden
dc.identifier.grantnumber656774en


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