Guidelines for planning genomic assessment and monitoring of locally adaptive variation to inform species conservation. (2nd December 2017)

• Record Type: Journal Article
• Authors: Flanagan, Sarah P.; Forester, Brenna R.; Latch, Emily K.; Aitken, Sally N.; Hoban, Sean
• Is Part Of: Evolutionary applications. Volume 11:Number 7(2018)
• Page Start: 1035
• Page End: 1052
• Publication Date: 2017-12-02
• Subjects: adaptive management -- conservation genetics -- conservation planning -- local adaptation -- natural selection -- next‐generation sequencing -- outlier detection; Evolution (Biology) -- Periodicals; Genetics -- Periodicals; Natural selection -- Periodicals; Ecology -- Periodicals; 576.8
• DOI: 10.1111/eva.12569
• Languages: English
• ISSNs: 1752-4571

Abstract

Abstract: Identifying and monitoring locally adaptive genetic variation can have direct utility for conserving species at risk, especially when management may include actions such as translocations for restoration, genetic rescue, or assisted gene flow. However, genomic studies of local adaptation require careful planning to be successful, and in some cases may not be a worthwhile use of resources. Here, we offer an adaptive management framework to help conservation biologists and managers decide when genomics is likely to be effective in detecting local adaptation, and how to plan assessment and monitoring of adaptive variation to address conservation objectives. Studies of adaptive variation using genomic tools will inform conservation actions in many cases, including applications such as assisted gene flow and identifying conservation units. In others, assessing genetic diversity, inbreeding, and demographics using selectively neutral genetic markers may be most useful. And in some cases, local adaptation may be assessed more efficiently using alternative approaches such as common garden experiments. Here, we identify key considerations of genomics studies of locally adaptive variation, provide a road map for successful collaborations with genomics experts including key issues for study design and data analysis, and offer guidelines for interpreting and using results from genomic assessments to inform monitoring programs and conservation actions.