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Use of Genetic Stock Identification Data for Comparison of the Ocean Spatial Distribution, Size at Age, and Fishery Exposure of an Untagged Stock and Its Indicator: California Coastal versus Klamath River Chinook Salmon
Author(s) -
Satterthwaite William H.,
Mohr Michael S.,
O'Farrell Michael R.,
Anderson Eric C.,
Banks Michael A.,
Bates Sarah J.,
Bellinger M. Renee,
Borgerson Lisa A.,
Crandall Eric D.,
Garza John Carlos,
Kormos Brett J.,
Lawson Peter W.,
PalmerZwahlen Melodie L.
Publication year - 2014
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 - 10.1080/00028487.2013.837096
Subject(s) - stock (firearms) , chinook wind , oncorhynchus , fishery , stock assessment , fish stock , environmental science , fisheries management , threatened species , geography , fishing , ecology , habitat , biology , fish <actinopterygii> , archaeology
Managing weak stocks in mixed‐stock fisheries often relies on proxies derived from data‐rich indicator stocks, although there have been limited tests of the appropriateness of such proxies. For example, full cohort reconstruction of tagged Klamath River fall‐run Chinook Salmon Oncorhynchus tshawytscha of northern California enables the use of detailed models to inform management. Information gained from this stock is also used in the management of the untagged, threatened California Coastal Chinook Salmon (CCC) stock, where it is assumed that a cap on Klamath harvest rates effectively constrains impacts on CCC to acceptable levels. To evaluate use of this proxy, we used a novel approach based on genetic stock identification (GSI) data to compare the two stocks’ size at age and ocean distribution (as inferred from spatial variation in CPUE), two key factors influencing fishery exposure. We developed broadly applicable methods to account for both sampling and genetic assignment uncertainty in estimating total stock‐specific catch from GSI data, and propagated this uncertainty into models quantifying variation in CPUE across space and time. We found that, in 2010, the stocks were similar in size at age early in the year (age 3 and age 4), but CCC fish were larger later in the year. The stocks appeared similarly distributed early in the year (2010) but more concentrated near their respective source rivers later in the year (2010 and 2011). If these results are representative, relative fishery impacts on the two stocks might scale similarly early in the year, but management changes later in the year could have differing impacts on the two stocks. This novel modeling approach is suited to evaluating the concordance between other data‐limited stocks and their proxies, and can be broadly applied to estimate stock‐specific harvest, and the uncertainty therein, using GSI in other systems.