Th-302A-15
Estimates of the Proportion of Hatchery-Origin Fish on Spawning Grounds Using Parentage-Based Tagging

Thursday, August 21, 2014: 3:40 PM
302A (Centre des congrès de Québec // Québec City Convention Centre)
Richard A. Hinrichsen , Hinrichsen Environmental, Seattle, WA
Craig A. Steele , Eagle Fish Genetics Lab, Pacific States Marine Fisheries Commission / Idaho Department of Fish and Game, Eagle, ID
Michael W. Ackerman , Eagle Fish Genetics Lab, Pacific States Marine Fisheries Commision, Eagle, ID
Matthew R. Campbell , Eagle Fish Genetics Lab, Idaho Department of Fish and Game, Eagle, ID
Shawn R. Narum , Fish Science, Columbia River Inter-Tribal Fish Commission, Hagerman, ID
Maureen A. Hess , Fish Science, Columbia River Inter-Tribal Fish Commission, Hagerman, ID
William Young , Department of Fisheries Resources Management, Nez Perce Tribe, McCall, ID
Barbara A. Shields , Bonneville Power Administration, Portland, OR
Brian Maschhoff , Salmonetics, Seattle, WA
For salmon populations in the Columbia River basin, estimates of the proportion of hatchery-origin adults in spawning areas (p) are needed to assess population status and potential for interbreeding with wild-origin adults. To identify hatchery-origin fish on spawning grounds, some hatchery releases are given visible marks, some are tagged with coded-wire tags (CWTs) or parentage based tags (PBTs), or all three. The PBT approach uses genotypes of hatchery broodstock and parentage assignments to identify the origin and brood year of their progeny. We derived a maximum likelihood estimator of p and applied it to the 2012 and 2013 carcass survey data for Spring Chinook salmon Oncorhynchus tshawytscha in the South Fork Salmon River, USA. We found that precision in the estimate of p increased with the expected number of tag recoveries, whether CWT or PBT. In the South Fork Salmon River study, PBT-based were more precise that CWT-base estimates because there were more PBT than CWT recoveries. To design a program for estimate p, one determines the expected number of tag recoveries that delivers the desired precision in p, and then selects the tagging fraction and sampling rate that achieves that number of tag recoveries in the least expensive way.