A statistical model for in-season forecasts of sockeye salmon (Oncorhynchus nerka) returns to the Bristol Bay districts of Alaska

Canadian Journal of Fisheries and Aquatic Sciences

Volumn 62, Issue 7, 2005, Pages 1665-1680

  Hyun, Saang Yoon ^a,b   Hilborn, Ray ^a   Anderson, James J ^a   Ernst, Billy ^a,c  

^a UNIVERSITY OF WASHINGTON   (United States)

^b Box 355020 ^*  (United States)

^c UNIVERSITY OF CONCEPCIÓN   (Chile)

Author keywords

[No Author keywords available]

Indexed keywords

FORECASTING METHOD; RETURN MIGRATION; SALMONID; STATISTICAL ANALYSIS;

ALASKA; BRISTOL BAY; NORTH AMERICA; UNITED STATES; WESTERN HEMISPHERE; WORLD;

ONCORHYNCHUS; ONCORHYNCHUS NERKA;

EID: 26944437986     PISSN: 0706652X     EISSN: None     Source Type: Journal    
DOI: 10.1139/f05-071     Document Type: Article

References (23)

1. Brooks, S.P., and Roberts, G.O. 1998. Assessing convergence of Markov Chain Monte Carlo algorithms. Stat. Comput. 8: 319-335.
2. Burgner, R.L. 1980. Some feature of ocean migrations and timing of Pacific salmon. In Salmonid ecosystems of the North Pacific. Edited by W.J. McNeil and D.C. Himsworth. Oregon State University Press, Corvallis, Oreg. pp. 153-164.
3. Casella, G., and Berger, R.L. 1990. Statistical inference. Duxbury Press, Belmont, Calif.
4. Cowles, M.K., and Carlin, B.P. 1995. Markov Chain Monte Carlo diagnostics: a comparative review. J. Am. Stat. Soc. 91: 883-904.
5. Crone, P.R., and Sampson, D.B. 1998. Evaluation of assumed error structure in stock assessment models that use sample estimates of age composition. In Fishery stock assessment models. Edited by F. Funk, T.J. Quinn II, J. Heifetz, J.N. Ianelli, J.E. Powers, J.F. Schweigen, P.J. Sullivan, and C.-I. Zhang. University of Alaska Fairbanks Press, Fairbanks, Alaska. pp. 355-370.
6. Flynn, L., and Hilborn, R. 2004. Test fishery indices for sockeye salmon (Oncorhynchus nerka) as affected by age composition and environmental variables. Can. J. Fish. Aquat. Sci. 61: 80-92.
7. Fournier, D.A. 2000. An introduction to AD Model Builder version 4: for use in nonlinear modeling and statistics. Otter Research Ltd., Sidney, B.C.
8. Fournier, D., and Archibald, C.P. 1982. A general theory for analyzing catch at age data. Can. J. Fish. Aquat. Sci. 39: 1195-1207.
9. Fried, S.M., and Hilborn, R. 1988. In-season forecasting of Bristol Bay, Alaska, sockeye salmon (Oncorhynchus nerka) abundance using Bayesian probability theory. Can. J. Fish. Aquat. Sci. 45: 850-855.
10. Gamerman, D. 1997. Markov Chain Monte Carlo: stochastic simulation for Bayesian inference. Chapman and Hall, London, UK.
11. Gelman, A., Carlin, J.B., Stern, H.S., and Rubin, D.B. 1995. Bayesian data analysis. Chapman and Hall, London, UK.
12. Helton, D.R. 1991. An analysis of the Port Moller offshore test fishing forecast of sockeye and chum salmon runs to Bristol Bay, Alaska. M.S. thesis, University of Washington, Seattle, Wash.
13. Hilborn, R. 2003. The state of the art in stock assessment: where we are and where we are going. Sci. Mar. 67(Suppl. 1): 15-20.
14. Hyun, S. 2002a. In-season forecasts of sockeye salmon returns to the Bristol Bay districts of Alaska. Ph.D. thesis, University of Washington, Seattle, Wash.
15. Hyun, S. 2002b. In-season forecast of sockeye salmon return timing to Bristol Bay, Alaska. J. Korean Soc. Fish. Res. 5: 41-51.
16. Minard, R.E., and Meacham, C.P. 1987. Sockeye salmon (Oncorhynchus nerka) management in Bristol Bay, Alaska. In Sockeye salmon (Oncorhynchus nerka) population biology and future management. Edited by H.D. Smith, L. Margolis, and C.C. Wood. Can. Spec. Publ. Fish. Aquat. Sci. No. 96. pp. 336-342.
17. Mundy, P.R. 1979. A quantitative measure of migratory timing illustrated by application to the management of commercial salmon fisheries. Ph.D. thesis, University of Washington, Seattle, Wash.
18. Patterson, K.R. 1999. Evaluating uncertainty in harvest control law catches using Bayesian Markov chain Monte Carlo virtual population analysis with adaptive rejection sampling and including structural uncertainty. Can. J. Fish. Aquat. Sci. 56: 208-221.
19. Quinn, T.J., and Deriso, R.B. 1999. Quantitative fish dynamics. Oxford University Press, Oxford, UK.
20. Raftery, A.E., and Lewis, S. 1992. How many iterations in the Gibbs sampler? In Bayesian statistics 4. Edited by J.M. Bernardo, J. Berger, A.P. Dawid, and A.F.M. Smith. Oxford University Press, Oxford, UK. pp. 763-773.
21. Raftery, A.E., and Lewis, S. 1996. Implementing MCMC. In Markov Chain Monte Carlo in practice. Edited by W.R. Gilks, S. Richardson, and D.J. Spielgehalter. Chapman and Hall, London, UK. pp. 115-127.
22. Rogers, D.E. 1994. Forecasts of the 1995 sockeye salmon runs to Bristol Bay. University of Washington School of Fisheries, Seattle, Wash., FRI-UW 9417.
23. Rogers, D.E., and Steen, R.P. 2000. A Bristol Bay almanac for 2000. University of Washington School of Fisheries, Seattle, Wash., SOF-UW-2005.