|Document Type:||Journal Article|
|Title:||Use of genertic stock identification data for comparison of the ocean spatial distribution, size-at-age, and fishery exposure of Klamath River versus California Coastal Chinook salmon|
|Author:||William H. Satterthwaite, Michael S. Mohr, Michael R. O'Farrell, E. Andersen, Michael A. Banks, Sarah J. Bates, M. Renee Bellinger, Lisa A. Borgerson, Eric D. Crandall, John Carlos Garza, Brett J. Kormos, Peter W. Lawson, M. Palmer-Zwahlen|
|Journal:||Transactions of the American Fisheries Society|
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.
|Full Text URL:||http://dx.doi.org/10.1080/00028487.2013.837096|
|Theme:||Ecosystem Approach to Management for the California Current Large Marine Ecosystem|
Characterize ecological interactions (e.g. predation, competition, parasitism, disease, etc.) within and among species to support ecosystem approach to management.