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Estimating Proportional Contributions of Migratory Bull Trout from Hierarchical Populations to Mixed‐Stock Recreational Fisheries Using Genetic and Trapping Data
Author(s) -
Warnock Will G.,
Blackburn Jason K.,
Rasmussen Joseph B.
Publication year - 2011
Publication title -
transactions of the american fisheries society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.696
H-Index - 86
eISSN - 1548-8659
pISSN - 0002-8487
DOI - 10.1080/00028487.2011.567868
Subject(s) - stock (firearms) , fishery , tributary , recreational fishing , trout , recreation , geography , fisheries management , streams , range (aeronautics) , stock assessment , ecology , fishing , biology , fish <actinopterygii> , computer network , cartography , archaeology , computer science , materials science , composite material
Genetic assignment methods were used to assign 104 adult migrant bull trout Salvelinus confluentus from five recreational fisheries in the Oldman River drainage (Alberta, Canada) to a baseline of three coarse‐scale genetic stocks that had been previously identified with a model‐based Bayesian clustering method. Based on individual assignment and genetic stock identification, most fisheries were largely dominated by the stock with the most proximate spawning tributaries; however, assignment tests suggested variation among source stocks in the proportions of long‐range (>90 river kilometers) migrants relative to short‐range migrants (i.e., that used nearby river systems draining spawning streams). Migrants originating from a subset of the drainage were then subjected to a finer‐scale mixed‐stock analysis in which populations at near‐tributary scales were used as the baseline. These stock proportions were compared with estimates from direct observations and were found to yield similar values to stock proportions derived from 2 years of trapping in several spawning streams. These genetic assignment methods may be used to infer contributions of large and fine‐scale hierarchical populations to mixed‐stock recreational fisheries and are especially applicable for use by inland recreational fisheries managers, which have traditionally not taken advantage of spatial genetic analysis tools to the extent used by coastal commercial fisheries managers.