2020
DOI: 10.1002/ece3.6942
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Evaluating wildlife translocations using genomics: A bighorn sheep case study

Abstract: 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.

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Cited by 22 publications
(27 citation statements)
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References 85 publications
(169 reference statements)
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“…Genetic structure among herds in this study clearly matched reintroduction history, as has been found in other studies (Gille et al 2019, Jahner et al 2019, Flesch et al 2020). Most reintroduced herds showed either pure California or Rocky Mountain ancestry, reflecting the efforts of separately managing these 2 lineages by reintroducing assumed pure California or Rocky Mountain sources to areas where they occurred historically in most cases.…”
Section: Discussionsupporting
confidence: 89%
See 1 more Smart Citation
“…Genetic structure among herds in this study clearly matched reintroduction history, as has been found in other studies (Gille et al 2019, Jahner et al 2019, Flesch et al 2020). Most reintroduced herds showed either pure California or Rocky Mountain ancestry, reflecting the efforts of separately managing these 2 lineages by reintroducing assumed pure California or Rocky Mountain sources to areas where they occurred historically in most cases.…”
Section: Discussionsupporting
confidence: 89%
“…S2, S3). This observed substructure might also reflect the association with different source populations, as has been seen across many other areas of the species' distribution (Epps et al 2005(Epps et al , 2018Castillo et al 2014;Gille et al 2019;Flesch et al 2020). We additionally identified some substructure within California and Rocky Mountain lineages for higher values of K using the program STRUCTURE, such as increased similarity between Tucannon and Black Butte in Washington, potentially as a result of gene flow between these herds (Fig.…”
Section: Discussionmentioning
confidence: 76%
“…We expected that native (indigenous/extant) origin, large population size, and greater gene flow via augmentations or natural dispersal would result in lower average pairwise kinship than reintroduced origin, small population size, and genetic isolation. We also predicted that the number of animals received in augmentations and origin would be the most important influences, due to observed effects of these variables on genomic similarity among populations (Flesch et al, 2020). This effort to evaluate how different influences on population size over time may affect average pairwise kinship in multiple free‐ranging populations can serve to assess the relative importance of these influences to enhance genetic management strategies, identify priorities for conservation of genetic diversity in different types of populations (e.g., native [indigenous/extant] vs. reintroduced), and improve the identification of populations of concern if genetic data are not available.…”
Section: Introductionmentioning
confidence: 99%
“…This study evaluates genomic consequences of post-reintroduction of Père David’s deer using the conservation genomics approach, and the results would contribute to inform future conservation management. There are many factors influencing species reintroduction success, among which genetic is the most important ( Flesch et al, 2020 ). The genetic diversity of an endangered species is one of the main parameters that can directly reflect the evolutionary potential.…”
Section: Conservation Implicationsmentioning
confidence: 99%
“…Genetic management plays an important role in improving the performance of reintroduction actions ( Theodorou and Couvet, 2010 ). Several studies have evaluated genetic consequences induced by reintroduction events for some ungulates using traditional molecular markers, for example, Przewalskii’s wild horse ( Equus ferus ; Liu et al, 2014 ), European bison ( Bison bonasus ; Olech and Perzanowski, 2002 ), and Arabian oryx ( Oryx leucoryx ; El Alqamy et al, 2012 ), but only very few studies use genomics data to evaluate post-reintroduction genetic consequences ( Flesch et al, 2020 ).…”
Section: Introductionmentioning
confidence: 99%