Development of Genetic Baseline Information to Support the Conservation and Management of Wild Brook Trout in North Carolina. (2nd April 2021)

• Record Type: Journal Article
• Authors: Kazyak, David C.; Lubinski, Barbara A.; Rash, Jacob M.; Johnson, Thomas C.; King, Timothy L.
• Is Part Of: North American journal of fisheries management. Volume 41:Number 3(2021)
• Page Start: 626
• Page End: 638
• Publication Date: 2021-04-02
• Subjects: Fishery management -- United States -- Periodicals; 333.956097305
• DOI: 10.1002/nafm.10569
• Languages: English
• ISSNs: 0275-5947

Abstract

Abstract: After centuries of declines, there is growing interest in conserving extant wild populations of Brook Trout Salvelinus fontinalis and reintroducing Brook Trout populations of native ancestry. A population genetic baseline can enhance conservation outcomes and promote restoration success. Consequently, it is important to document existing patterns of genetic variation across the landscape and translate these data into an approachable format for fisheries managers. We genotyped 9, 507 Brook Trout representing 467 wild collections at 12 microsatellite loci to establish a genetic baseline for North Carolina, USA. Rarefied allelic richness (mean = 3.12) and observed heterozygosity (mean = 0.42), which reflect within‐population diversity, were low to moderate relative to levels typically observed at higher latitudes. Effective population sizes ( Ne ) varied widely but were often very low (151 collections had an estimated Ne < 10). Despite decades of intensive stocking across the state, we found little to no evidence of hatchery introgression in most populations. Although genetic variation was significant at a variety of spatial scales (mean pairwise = F ST ′ 0.73), substantial genetic variation occurred between patches within individual watersheds. Analysis of molecular variance indicated that a substantial portion (28.5%) of the observed genetic variation was attributable to differences among populations, with additional genetic variation among hydrologic unit codes (HUCs; 16.0, 16.6, 12.1, and 9.4% of the overall variation among 12‐, 10‐, 8‐, and 6‐digit HUCs, respectively). We discuss a suite of potential applications for this type of genetic data to enhance management outcomes, such as conservation prioritization and selection of source stocks for reintroductions or genetic rescue.