Deriving acceptable biological catch from the overfishing limit: Implications for assessment models

North American Journal of Fisheries Management

Volumn 30, Issue 1, 2010, Pages 289-294

  Prager, Michael H ^a   Shertzer, Kyle W ^a  

^a SOUTHEAST FISHERIES SCIENCE CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 79956040008     PISSN: 02755947     EISSN: 15488675     Source Type: Journal    
DOI: 10.1577/M09-105.1     Document Type: Article

References (19)

1. Caddy, J. F., and R. McGarvey. 1996. Targets or limits for management of fisheries? North American Journal of Fisheries Management 16:479-487.
2. Eagle, J., and B. H. Thompson Jr. 2003. Answering Lord Perry’s question: dissecting regulatory overfishing. Ocean and Coastal Management 46:649-679.
3. Efron, B. 1987. Better bootstrap confidence intervals. Journal of the American Statistical Association 82:171-200.
4. Legault, C. M., J. E. Powers, and V. R. Restrepo. 2001. Mixed Monte Carlo/bootstrap approach to assessing king and Spanish mackerel in the Atlantic and Gulf of Mexico: its evolution and impact. Pages 37-44 in J. L. Berkson, L. L. Kline, and D. J. Orth, editors. Incorporating uncertainty into fishery models. American Fisheries Society, Symposium 27, Bethesda, Maryland.
5. Lunn, D. J., A. Thomas, N. Best, and D. Spiegelhalter. WinBUGS-a Bayesian modelling framework: concepts, structure, and extensibility. Statistics and Computing 10:325-337.
6. Methot, R. D. 1989. Synthesis model: an adaptive framework for analysis of diverse stock assessment data. International North Pacific Fisheries Commission Bulletin 50:259-277.
7. MSRA (Magnuson-Stevens Fishery Conservation and Management Reauthorization Act of 2006). 2006. U.S. Public Law 109-479, 120 Statute 3575.
8. Pella, J. J. 1967. A study of methods to estimate the Schaefer model parameters with special reference to the yellowfin tuna fishery in the eastern tropical Pacific Ocean. Doctoral dissertation. University of Washington, Seattle.
9. Prager, M. H. 1994. A suite of extensions to a nonequilibrium surplus-production model. Fishery Bulletin 92:374-389.
10. Prager, M. H. 1995. User’s manual for ASPIC: a Stock Production Model Incorporating Covariates, program version 3.6x, 4th edition. National Marine Fisheries Service, Southeast Fisheries Science Center, Miami Laboratory Document MIA-2/93-55, Miami.
11. Prager, M. H., and A. D. MacCall. 1988. Sensitivities and variances of virtual population analysis as applied to the mackerel, Scomber japonicus. Canadian Journal of Fisheries and Aquatic Sciences 45:539-547.
12. Prager, M. H., C. E. Porch, K. W. Shertzer, and J. F. Caddy. 2003. Targets and limits for management of fisheries: a simple probability-based approach. North American Journal of Fisheries Management 23:349-361.
13. R Development Core Team. 2008. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Available: www. R-project.org. (October 2008).
14. Schaefer, M. B. 1957. A study of the dynamics of the fishery for yellowfin tuna in the eastern tropical Pacific Ocean. Bulletin of the Inter-American Tropical Tuna Commission 2:247-268.
15. Seber, G. A. F. 1973. The estimation of animal abundance and related parameters. Hafner Press, New York.
16. SEDAR (Southeast Data Assessment and Review). 2004. SEDAR 4 Stock assessment report 1: stock assessment of the deepwater snapper-grouper complex in the south Atlantic. South Atlantic Fishery Management Council, North Charleston, South Carolina.
17. Shertzer, K. W., M. H. Prager, and E. H. Williams. 2008. A probability-based approach to setting annual catch levels. Fishery Bulletin 106:225-232.
18. U.S. Office of the Federal Register 2009. Magnuson-Stevens Act provisions: national standard 1-optimum yield. Federal Register 74:11(16 January 2009):3178-3213. Available: ecfr.gpoaccess.gov/ (March 2009).
19. Venables, W. N., and B. D. Ripley. 2002. Modern applied statistics with S, 4th edition. Springer, New York.