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A Time Density Model to Estimate Run Size and Entry Timing in a Salmon Fishery

1998; Wiley; Volume: 18; Issue: 2 Linguagem: Inglês

10.1577/1548-8675(1998)018 2.0.co;2

1548-8675

Robert Richard Springborn, Nickolas D. Lampsakis, Vincent F. Gallucci,

Water Quality and Resources Studies

North American Journal of Fisheries ManagementVolume 18, Issue 2 p. 391-405 Article A Time Density Model to Estimate Run Size and Entry Timing in a Salmon Fishery Robert Richard Springborn, Robert Richard Springborn Point No Point Treaty Council, 7999 Northeast Salish Lane, Kingston, Washington, 98346 USAPresent address: 701 Wawona Street, Apartment 265, San Francisco, California 94116, USA.Search for more papers by this authorNickolas D. Lampsakis, Nickolas D. Lampsakis Point No Point Treaty Council, 7999 Northeast Salish Lane, Kingston, Washington, 98346 USASearch for more papers by this authorVincent F. Gallucci, Vincent F. Gallucci School of Fisheries Center for Quantitative Science University of Washington, Box 357980, Seattle, Washington, 98195 USASearch for more papers by this author Robert Richard Springborn, Robert Richard Springborn Point No Point Treaty Council, 7999 Northeast Salish Lane, Kingston, Washington, 98346 USAPresent address: 701 Wawona Street, Apartment 265, San Francisco, California 94116, USA.Search for more papers by this authorNickolas D. Lampsakis, Nickolas D. Lampsakis Point No Point Treaty Council, 7999 Northeast Salish Lane, Kingston, Washington, 98346 USASearch for more papers by this authorVincent F. Gallucci, Vincent F. Gallucci School of Fisheries Center for Quantitative Science University of Washington, Box 357980, Seattle, Washington, 98195 USASearch for more papers by this author First published: 08 January 2011 https://doi.org/10.1577/1548-8675(1998)018 2.0.CO;2Citations: 4 Corresponding author. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract Managers need improved estimates of run size and entry timing for salmon migrating to their natal spawning grounds if they are to improve the biological and economic management of salmon fisheries. A time density model was derived from the inverted exponential model of Mathisen and Berg. During a fishery, this model provides three estimates of run size that are more accurate than the preseason forecast. The result is used to manage fisheries for chum salmon Oncorhynchus keta in the entire Hood Canal area and the Skokomish River of western Washington state. The model uses both daily catches per unit effort (CPUE) by drift gill nets and peak purse-seine catches from a northern Hood Canal fishery to estimate run size and entry timing. Run size and entry timing estimates are derived from a fitted cumulative time density of daily CPUE; historical data are used to correct for missing daily gill-net CPUE values. The result is estimates of run size with increased precision and decreased bias. A linear regression model, in which a peak 1-d purse-seine catch is an independent variable, is used to correct the time density run size estimate. This correction decreased the run size mean percent error from 18% to 5% and from 27% to 4% on two successive updates. The assumptions are that: (1) the timing and progression of a salmon migration are consistent; (2) there is continuous fish passage in one direction; (3) the gill nets sample passively; (4) estimates of daily CPUE from the fishery can be used to construct the time density; and (5) the cumulative daily CPUE for the season is directly proportional to run size. The accuracy of run size and entry timing estimates obtained during the fishery are likely to be affected by gear competition between the purse-seine fleet and the drift gill-net fleet, as well as by data misreporting and time delays in reporting daily drift gill-net CPUE. This model could be applied to most exploited animal populations where the abundance of individuals over time at a fixed geographic reference frame is approximately normally distributed. Citing Literature Volume18, Issue2May 1998Pages 391-405 RelatedInformation