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Population abundance in arctic grayling using genetics and close‐kin mark‐recapture
- Source :
- Ecology and Evolution, Vol 11, Iss 9, Pp 4763-4773 (2021)
- Publication Year :
- 2021
- Publisher :
- Wiley, 2021.
-
Abstract
- Abstract Arctic Grayling (Thymallus arcticus) are among the most widely distributed and abundant freshwater fish in the Yukon Territory of Canada, yet little information exists regarding their broad and fine‐scale population structures or the number and size of these populations. The estimation of population abundance is fundamental for robust management and conservation, yet estimating abundance in the wild is often difficult. Here, we estimated abundance of an Arctic Grayling population using multiple genetic markers and the close‐kin mark‐recapture (CKMR) method. A total of N = 1,104 Arctic Grayling collected from two systems in Yukon were genotyped at 38 sequenced microsatellites. We first identified structure and assessed genetic diversity (effective population size, N^e). Collections from one of the systems (Lubbock River) comprised adults and young‐of‐the‐year sampled independently allowing the identification of parent–offspring pairs (POPs), and thus, the estimation of abundance using CKMR. We used COLONY and CKMRsim to identify POPs and both provided similar results leading to indistinguishable estimates (95% CI) of census size, that is, N^c(COLONY) = 1858 (1259–2457) and N^c(CKMRsim)=1812 (1229–2389). The accuracy of the population abundance estimates can in the future be improved with temporal sampling and more precise age or size‐specific fecundity estimates for Arctic Grayling. Our study demonstrates that the method can be used to inform management and conservation policy for Arctic Grayling and likely also for other fish species for which the assumption of random and independent sampling of adults and offspring can be assured.
Details
- Language :
- English
- ISSN :
- 20457758
- Volume :
- 11
- Issue :
- 9
- Database :
- Directory of Open Access Journals
- Journal :
- Ecology and Evolution
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.71ce1f380f614fc3957063f55e2b393d
- Document Type :
- article
- Full Text :
- https://doi.org/10.1002/ece3.7378