Consideration of uncertainty in the design and use of harvest control rules

Yan Jiao; Kevin Reid; Tom Nudds

doi:10.3989/scimar.2010.74n2371

Autores/as

Yan Jiao Department of Fisheries and Wildlife Sciences, Virginia Polytechnic Institute and State University
Kevin Reid Ontario Commercial Fisheries Association
Tom Nudds Department of Integrative Biology, University of Guelph

DOI:

https://doi.org/10.3989/scimar.2010.74n2371

Palabras clave:

regla de control de producción, evaluación del estado de las pesquerías, incertidumbre, toma de decisiones, análisis bayesiano

Resumen

Las reglas de control de producción se usan generalmente por los organismos de gestión de recursos pesqueros para tomar decisiones y para promover la concienciación pública sobre el estado de conservación de pesquerías marinas y de aguas dulces. Muchas de las reglas de control actuales combinan puntos de referencia biológicos basados en los indicadores mortalidad por pesca y biomasa. Las reglas de control fueron introducidas como precaución contra la influencia de la incertidumbre en las evaluaciones y para reducir el riesgo de sobrepesca, pero se ven comprometidas si la incertidumbre en los puntos de referencia biológicos no se consideran explícitamente. El papel de la incertidumbre se reconoce ampliamente, pero no ha sido incorporado hasta ahora en el diseño y aplicación de reglas de control. En la presente contribución se aplica un modelo bayesiano de capturas por edad para estimar la incertidumbre en los indicadores de mortalidad por pesca, tamaño de la población y puntos de referencia biológicos. Se aplica este modelo a la pesquería de Sander vitreus del Lago Erie, y, mediante la completa incorporación de la incertidumbre de los indicadores, el riesgo de sobrepesca puede ser estimado explícitamente en las reglas de control. Se sugieren aproximaciones a corto y largo plazo para la incorporación de la incertidumbre en el diseño de reglas de control. Se sugiere también que las reglas para pesquerías particulares deben diseñarse incorporando explícitamente la incertidumbre en los puntos de referencia biológicos, en base al nivel de riesgo que se acuerde entre el organismo encargado de la gestión del recurso y sus usuarios.

Descargas

Los datos de descargas todavía no están disponibles.

Citas

ASMFC (Atlantic States Marine fisheries Commission). − 2002. Amendment 4 to the Interstate Fishery Management Plan for Atlantic Weakfish. Fish. Manag. Rep. No. 39: 1-101pp.

Brodziak, J. and C.M Legault. – 2005. Model averaging to estimate rebuilding targets for overfished stocks. Can. J. Fish. Aquat. Sci., 62(3): 544-562. doi:10.1139/f04-199

Butterworth, D.S. and P.B. Best. – 1994. The origins of the choice of 54% of carrying capacity as the protection level for baleen whale stocks, and the implications thereof for management procedures. Rep. Int. Whal. Commn., 44: 491-497.

Caddy, J.F. and R. Mahon. – 1995. Reference points for fisheries management. FAO Fish. Tech. Pap., 347.

Chen, Y. and C. Wilson. – 2002. A simulation study to evaluate impact of uncertainty on the assessment of American lobster fishery in the Gulf of Maine. Can. J. Fish. Aquat. Sci., 59(8): 1394-1403. doi:10.1139/f02-102

Chen, Y., Y. Jiao and L. Chen. – 2003. Developing robust frequentist and Bayesian fish stock assessment methods. Fish Fish., 4(2): 105-120. doi:10.1046/j.1467-2979.2003.00111.x

de Valpine, P. and A. Hasting. – 2002. Fitting population models incorporating process noise and observation error. Ecol. Monogr., 72(1): 57-76. doi:10.1890/0012-9615(2002)072[0057:FPMIPN]2.0.CO;2

FAO. – 1995. Precautionary Approach to Fisheries. Part 1: Guidelines on the precautionary approach to capture fisheries and species introductions, United Nations. FAO Fish. Tech. Pap,. 350/1.

Francis, R.I.C.C. and R. Shotton. – 1997. “Risk” in fisheries management: a review. Can. J. Fish. Aquat. Sci., 54(8): 1699-1715. doi:10.1139/cjfas-54-8-1699

Garcia S.M. – 1996. The precautionary approach to fisheries and its implications for fishery research, technology and management: An updated review. FAO Fish. Tech. Paper, 350/2.

Gilks, W.R. – 1996. Full conditional distributions. In: W.R. Gilks, S. Richardson and D.J. Spiegelhalter (eds.), Markov Chain Monte Carlo in Practice, pp. 75-78. Chapman and Hall, London, U.K.

Helser, T.E., T. Sharov and D.M Kahn. – 2001. A stochastic decision-based approach to assessing the Delaware Bay blue crab (Callinectes sapidus) stock. In: J.M. Berkson, L.L. Kline and D.J. Orth (eds.), Incorporating uncertainty into fishery models, pp. 63-82. American Fisheries Society Publication, 27. Bethesda, Md.

Hilborn R. – 2002. The dark side of reference points. Bull. Mar. Sci., 70(2): 403–408.

Hilborn, R. – 2006. Fisheries success and failure: the case of the Bristol Bay salmon fishery. Bull. Mar. Sci., 78(3): 487-498.

Hilborn, R. and C. Walters. – 1992. Quantitative Fisheries Stock Assessment: Choice, Dynamics, and Uncertainty. Chapman and Hall, New York.

Hoeting, J.A., D. Madigan, A.E. Raftery and C.T. Volinsky. – 1999. Bayesian model averaging: a tutorial. Stat. Sci., 14(4): 382-417.

Jiao, Y., Y. Chen and J. Wroblewski. – 2005. An application of the composite risk assessment method in assessing fisheries stock status. Fish. Res., 72(2-3): 173-183. doi:10.1016/j.fishres.2004.11.003

Katsukawa, T. – 2004. Numerical investigation of the optimal control rule for decision-making in fisheries management. Fish. Sci., 70(1): 123-131. doi:10.1111/j.1444-2906.2003.00780.x

Koeller, P. – 2003. The lighter side of reference points. Fish. Res., 62(1): 1-6. doi:10.1016/S0165-7836(02)00241-2

Lake Erie Walleye Task Group (LEWTG). – 2004. Report of the walleye task group to the standing technical committee. Lake Erie Committee of the Great Lakes Fishery Commission.

Lake Erie Walleye Task Group (LEWTG). – 2008. Report of the walleye task group to the standing technical committee. Lake Erie Committee of the Great Lakes Fishery Commission.

May, R.M., J.R. Beddington, C.W. Clark, S.J. Holt and R.M. Laws. – 1979. Management of multispecies fisheries. Science, 205(4403): 267-277. doi:10.1126/science.205.4403.267 PMid:17747032

McAllister, M.K. and J.N. Ianelli. – 1997. Bayesian stock assessment using catch-age data and the sampling-importance-resampling algorithm. Can. J. Fish. Aquat. Sci., 54(2): 284-300. doi:10.1139/cjfas-54-2-284

Millar, R.B. and R. Meyer. – 2000. Non-linear state-space modeling of fisheries biomass dynamics by using Metropolis-Hastings within-Gibbs sampling. Appl. Stat., 49(3): 327-342. doi:10.1111/1467-9876.00195

Munawar, M., I.F. Munawar, R. Dermott, H. Niblock and S. Carou.– 2002. Is Lake Erie a resilient ecosystem? Aquat. Ecosyst. Health Manage., 5(1): 79-93. doi:10.1080/14634980260199981

Patterson, K., R. Cook, C. Darby, S. Gavaris, L. Kell, P. Lewy, B. Mesnil, A. Punt, V. Restrepo, D.W. Skagen and G. Stefansson. – 2001. Estimating uncertainty in fish stock assessment and forecasting. Fish Fish., 2(2): 125-157. doi:10.1046/j.1467-2960.2001.00042.x

Punt, A.E. and R. Hilborn. – 1997. Fisheries stock assessment and decision analysis: the Bayesian approach. Rev. Fish. Biol. Fish., 7(1): 35-63. doi:10.1023/A:1018419207494

Quinn, T. and R.B. Deriso. – 1999. Quantitative fish dynamics. Oxford University Press, Oxford, UK.

Restrepo, V.R., and J.E. Powers. – 1999. Precautionary control rules in US fisheries management: specification and performance. ICES J. Mar. Sci., 56(6): 846-852. doi:10.1006/jmsc.1999.0546

Restrepo, V.R., G.G. Thompson, P.M. Mace, W.L. Gabriel, L.L. Wow, A.D. MacCall, R.D. Methot, J.E Powers, B.L. Taylor, P.R. Wade and J.F. Witzig. – 1998. Technical guidance on the use of precautionary approaches to implementing National Standard 1 of the Magnuson–Stevens Fishery Conservation and Management Act. NOAA Tech. Memora. NMFS–F/SPO– 31.

Roughgarden, J. and F. Smith. –1996. Why fisheries collapse and what to do about it? Proc. Natl. Acad. Sci. USA., 93(10): 5078-5083. doi:10.1073/pnas.93.10.5078

Rubin, D.B. – 1988. Using the SIR algorithm to simulate posterior distributions. In: J. Bernardo, M. DeGroot, D.V. Lindley and A.F.M. Smith (eds.), Bayesian Statistics, 3, pp. 395-402. Oxford University Press, Oxford.

SAFMC (South Atlantic Fisheries Management Council). – 2005. SEDAR stock assessment for Black Sea Bass. Beaufort, North Carolina.

Shepherd, J.G. – 1982. A versatile new stock-recruitment relationship for fisheries, and the construction of sustainable yield curves. I. Cons. Int. Explor. Mer., 40(1): 67-75.

Smith, A.F.M. and A.E. Gelfand. – 1992. Bayesian statistics without tears: A sampling-resampling perspective. Amer. Stat., 46(2): 84-88. doi:10.2307/2684170

Spiegelhalter, D.J., A. Thomas, N. Best and D. Lunn. – 2004. WinBUGS user manual (version 1.4.1). MRC Biostatistics Unit, Cambriage, U.K.

Sunstein, C.R. – 2005. Cost-benefit analysis and the environment? Ethics, 115(2): 351-385. doi:10.1086/426308

Thompson, G.G. – 1993. A proposal for a threshold stock size and maximum fishing mortality rate. Can. Spec. Publ. Fish. Aquat. Sci., 120: 303-320.