Complex problems need detailed solutions: Harnessing multiple data types to inform genetic management in the wild.
AlleleRetain
Tasmanian devil
genetic rescue
major histocompatibility complex
microsatellites
stochastic population modelling
translocation
Journal
Evolutionary applications
ISSN: 1752-4571
Titre abrégé: Evol Appl
Pays: England
ID NLM: 101461828
Informations de publication
Date de publication:
Feb 2019
Feb 2019
Historique:
received:
27
02
2018
revised:
15
08
2018
accepted:
04
09
2018
entrez:
31
1
2019
pubmed:
31
1
2019
medline:
31
1
2019
Statut:
epublish
Résumé
For bottlenecked populations of threatened species, supplementation often leads to improved population metrics (genetic rescue), provided that guidelines can be followed to avoid negative outcomes. In cases where no "ideal" source populations exist, or there are other complicating factors such as prevailing disease, the benefit of supplementation becomes uncertain. Bringing multiple data and analysis types together to plan genetic management activities can help. Here, we consider three populations of Tasmanian devil,
Identifiants
pubmed: 30697339
doi: 10.1111/eva.12715
pii: EVA12715
pmc: PMC6346650
doi:
Banques de données
Dryad
['10.5061/dryad.11ss226']
Types de publication
Journal Article
Langues
eng
Pagination
280-291Références
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