Use of a mark-recapture model to evaluate largemouth bass delayed tournament mortality

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2019-11-01
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Sylvia, Andrea
Weber, Michael
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Weber, Michael
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Natural Resource Ecology and Management
The Department of Natural Resource Ecology and Management is dedicated to the understanding, effective management, and sustainable use of our renewable natural resources through the land-grant missions of teaching, research, and extension.
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Estimating fishing mortality, including initial and delayed mortality, is necessary to assess potential effects of catch and release tournament fishing events. Previous studies retaining angler-caught fish are useful in understanding delayed mortality but have associated limitations. As an alternative to tournament mortality studies, we estimated daily apparent survival rates of largemouth bass Micropterus salmoidesusing a modified Cormack-Jolly-Seber model in Program MARK to test for the duration of delayed tournament mortality and to identify important covariates affecting survival. Multiple monotonic trends were evaluated to test acute (2, 3, 4, or 7 d) and chronic (15 or 30 d) delayed mortality hypotheses. The most supported models revealed an acute trend in survival following tournament capture but no support for chronic mortality. Largemouth bass survival decreased with increases in water temperature and the number of tournament capture events. Combined, these factors resulted in up to 90% cumulative mortality at temperatures of 18.8 °C for individuals captured at five tournament events. Our results confirm the potential for high delayed mortality associated with catch and release fishing tournaments. Using mark-recapture data to understand tournament fishing mortality can be a valuable tool in managing highly fished systems.

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This is a mansucript of an article published as Sylvia, Andrea, and Michael J. Weber. "Use of a mark-recapture model to evaluate largemouth bass delayed tournament mortality." Fisheries Research 219 (2019): 105335. doi: 10.1016/j.fishres.2019.105335. Posted with permission.

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Tue Jan 01 00:00:00 UTC 2019
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