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Restoring species through reintroductions: strategies for source population selection
Author(s) -
Houde Aimee Lee S.,
Garner Shawn R.,
Neff Bryan D.
Publication year - 2015
Publication title -
restoration ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.214
H-Index - 100
eISSN - 1526-100X
pISSN - 1061-2971
DOI - 10.1111/rec.12280
Subject(s) - adaptation (eye) , selection (genetic algorithm) , population , adaptive strategies , local adaptation , matching (statistics) , computer science , biology , geography , machine learning , statistics , demography , mathematics , archaeology , neuroscience , sociology
Only a quarter of reintroduction programs succeed in restoring a self‐sustaining population of an extirpated species. Optimal source population selection for restoration efforts can increase the fitness of translocated individuals and improve reintroduction success. Here, we describe the support for two strategies for selecting source populations: pre‐existing adaptation and adaptive potential. The pre‐existing adaptation strategy focuses on source populations with a high frequency of genotypes that confer adaptations, and within this strategy we detail the ancestry matching approach and environment matching approach. The adaptive potential strategy focuses on source populations with high heritable genetic variation that confer the potential to adapt, and within this strategy we detail the single source population approach and multiple source population approach. We review empirical tests of the different approaches, and find stronger support for the pre‐existing adaptation strategy than the adaptive potential strategy. We provide a framework for source population selection based on the two strategies, highlighting the importance of gathering information on key environment features in the source and restoration locations, as well as detail the knowledge gaps. Filling these knowledge gaps is important for validating and potentially revising our proposed framework, and ultimately improving the success rate of restoring extirpated populations.