Evaluation of Genetic Structuring within GIS‐Derived Brook Trout Management Units. Issue 6 (1st October 2020)

• Record Type: Journal Article
• Authors: Nathan, Lucas R.; Kanno, Yoichiro; Letcher, Benjamin H.; Welsh, Amy B.; Whiteley, Andrew R.; Vokoun, Jason C.
• Is Part Of: Transactions of the American Fisheries Society. Volume 149:Issue 6(2020)
• Page Start: 681
• Page End: 694
• Publication Date: 2020-10-01
• Subjects: Fish culture -- Periodicals; Fishery management -- Periodicals; Pisciculture -- Périodiques; 639.2
• DOI: 10.1002/tafs.10260
• Languages: English
• ISSNs: 0002-8487

Abstract

Abstract: Delineation of management units across broad spatial scales can help to visualize population structuring and identify conservation opportunities. Geographical information system (GIS) approaches can be useful for developing broad‐scale management units, especially when paired with field data that can validate the GIS‐based delineations. Genetic data can be useful for evaluating whether management units accurately represent population structuring. The Eastern Brook Trout Joint Venture, a regionwide collaborative group, delineated patch‐based management units for Brook Trout Salvelinus fontinalis by using GIS approaches to inform conservation strategies across the eastern United States. The objectives of this research were to (1) evaluate how well the patches predicted Brook Trout genetic structuring in Connecticut, USA; (2) modify the patches as needed to represent contemporary genetic structuring; and (3) identify catchment‐ and patch‐scale riverscape characteristics that predict genetic diversity. Patches with dams and high levels of upstream impervious surfaces (>3%) had increased intrapatch genetic structuring, which we incorporated into our revised patch delineation algorithm. Patch area and catchment area were the best predictors of genetic diversity, suggesting the importance of maintaining connectivity and incorporating patch‐scale processes into conservation actions. The modified patch layer could be used as the basis for Brook Trout management units to help predict population structuring in the absence of watershed‐scale genetic data, allowing opportunities for Brook Trout conservation to be identified.