Bayesian state-space models with multiple CPUE data: the case of a mullet fishery
DOI:
https://doi.org/10.3989/scimar.04461.11AKeywords:
hierarchical models, MCMC, multiple fisheries, data-limited, stock assessment, Mugil lizaAbstract
We propose a novel Bayesian hierarchical structure of state-space surplus production models that accommodate multiple catch per unit effort (CPUE) data of various fisheries exploiting the same stock. The advantage of this approach in data-limited stock assessment is the possibility of borrowing strength among different data sources to estimate reference points useful for management decisions. The model is applied to thirteen years of data from seven fisheries of the lebranche mullet (Mugil liza) southern population, distributed along the southern and southeastern shelf regions of Brazil. The results indicate that this modelling strategy is useful and has room for extensions. There are reasons for concern about the sustainability of the mullet stock, although the wide posterior credibility intervals for key reference points preclude conclusive statistical evidence at this time
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Brodziak J., Ishmura G. 2011. Development of Bayesian production models for assessing the North Pacific swordfish population. Fish. Sci. 77: 23-34. https://doi.org/10.1007/s12562-010-0300-0
Chaloupka M., Balazs G. 2007. Using Bayesian state-space modelling to assess the recovery and harvest potential of the Hawaiian green sea turtle stock. Ecol. Model. 205: 93-109. https://doi.org/10.1016/j.ecolmodel.2007.02.010
Chen Y., Andrew N. 1998. Parameter estimation in modelling the dynamics of fish stock biomass: are currently used observation-error estimators reliable? Can. J. Fish. Aquat. Sci. 55: 749-760. https://doi.org/10.1139/f97-270
Clark C.W. 1985. Bioeconomic modelling and fisheries management. John Wiley & Sons, New Jersey. 291 pp.
Erisman B.E., Allen L.G., Claisse J.T. et al. 2011. The illusion of plenty: hyperstability masks collapses in two recreational fisheries that target fish spawning aggregations. Can. J. Fish. Aquat. Sci. 68: 1705-1716. https://doi.org/10.1139/f2011-090
Garbin T., Castello J.P., Kinas P.G. 2014. Age, growth and mortality of the mullet Mugil liza in Brazil's southern and southeastern coastal regions. Fish. Res. 149: 61-68. https://doi.org/10.1016/j.fishres.2013.09.008
Gulland J. 1983. Fish stock assessment: a manual of basic methods. Wiley, New York.
Hilborn R. 1979. Comparison of fisheries control systems that utilize catch and effort data. J. Fish. Res. Bd. Can. 36: 1477-1489. https://doi.org/10.1139/f79-215
Hilborn R., Walters C.J. 1992. Quantitative fisheries stock assessment: choice, dynamics and uncertainty. Chapman and Hall, New York. 570 pp. https://doi.org/10.1007/978-1-4615-3598-0 PMid:9908045
Kinas P.G. 1996. Bayesian fishery stock assessment and decision making using adaptive importance sampling. Can. J. Fish. Aquat. Sci. 53: 414-423. https://doi.org/10.1139/f95-189
Lemos V., Varela Jr. A., Schwingel P., et al. 2014. Migration and reproductive biology of Mugil liza (Teleostei: Mugilidae) in South Brazil. J. Fish. Biol. 85: 671-687. https://doi.org/10.1111/jfb.12452 PMid:25040915
Lemos V.M., Troca D.F.A., Castello J.P., et al. 2016. Tracking the southern Brazilian schools of Mugil liza during reproductive migration using VMS of purse seiners. Lat. Am. J. Aquat. Res. 44: 238-246. https://doi.org/10.3856/vol44-issue2-fulltext-5
Ludwig D., Walters C.J. 1985. Are age structure models appropriate for catch-effort data? Can. J. Fish. Aquat. 42: 1066-1072. https://doi.org/10.1139/f85-132
Ludwig D., Walters C.J. 1989. A robust method for parameter estimation from catch and effort data. Can. J. Fish. Aquat. Sci. 46: 137-144. https://doi.org/10.1139/f89-018
MMA (Ministério do Meio Ambiente). 2004. Instrução Normativa MMA n° 05, de 21 de maio de 2004. Publica a lista das espécies de água doce e salgada reconhecendo invertebrados aquáticos e peixes, como espécies ameaçadas de extinção e espécies sobreexplotadas ou ameaçadas de sobreexplotação. Brasilía.
Mai A.C.G., Mi-o C.I., Marins L.F.F., et al. 2014. Microsatellite variation and genetic structuring in Mugil liza (teleostei: Mugilidae) populations from Argentina and Brazil. Est. Coast. Shelf Sci. 149: 80-86. https://doi.org/10.1016/j.ecss.2014.07.013
McAllister M.K., Kirkwood G.P. 1998. Bayesian stock assessment: a review and example application using the logistic model. ICES J. Mar. Sci. 55: 1031-1060. https://doi.org/10.1006/jmsc.1998.0425
Menezes N.A., Buckup P.A., Figueiredo J.L., et al. 2003. Catálogo de Peixes Marinhos do Brasil. Museu de Zoologia da Universidade de São Paulo, São Paulo.
Meyer R., Millar R. 1999. BUGS in Bayesian stock assessment. Can. J. Fish. Aquat. Sci. 56: 1078-1086. https://doi.org/10.1139/f99-043
Millar R.B., Meyer R. 2000. Non-linear state space modelling of fisheries biomass dynamics by using Metropolis-Hastings within-Gibbs sampling. Appl. Stat. 49: 327-342. https://doi.org/10.1111/1467-9876.00195
Miranda L.V., Mendonça J.T., Cergole M.C. 2006. Diagnóstico do estoque e orientações para o ordenamento da pesca de Mugil platanus (Gunther 1980). Série documentos REVIZEE, Instituto Oceanográfico USP, São Paulo.
Miranda L.V., Carneiro M.H., Peres M.B., et al. 2011. Contribuições ao processo de ordenamento da pesca da espécie Mugil liza (Teleostei: Mugilidae) nas Regiões Sudeste e Sul do Brasil entre os anos 2006 e 2010. Séries relatórios técnicos, Instituto de Pesca de São Paulo, São Paulo.
Pella J.J., Tomlinson P.K. 1969. A generalized stock production model. Bull. I-ATTC. 3: 416-497.
Pina J.V., Chaves P.d.T. 2005. A pesca da tainha e parati na Baía de Guaratuba, Paraná, Brasil. Acta Biol. Paran. 34: 103-113.
Plummer M. 2013. rjags: Bayesian graphical models using MCMC. R package version 3.10. http://CRAN.R-project.org/package=rjags.
R Core Team. 2015. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/
Rose G.A., Kulka D.A. 1999. Hyperaggregation of fish and fish(Gadus morhua) declined. Can. J. Fish. Aquat. Sci. 56: 118-127. https://doi.org/10.1139/f99-207
Schaefer M.B. 1957. A study of the dynamics of the fishery for yellowfin tuna in the eastern tropical Pacific Ocean. Bull. I-ATTC. 2: 243-285.
Seckendorff R.W. V., Azevedo V.G. 2007. Abordagem histórica da pesca da tainha (Mugil liza) e do parati (Mugil curema) (perciformes: Mugilidae) no litoral norte do estado de São Paulo. Séries Relatórios Técnicos 28, Instituto de Pesca de São Paulo - IP/SP, São Paulo.
Sparre P., Venema S.C. 1997. Introdução à avaliação de mananciais de peixes tropicais. FAO Documentos Técnicos sobre as Pescas 306/1, Food and Agriculture Organization, Roma.
Spiegelhalter J.D., Best N.G., Carlin B.P., et al. 2002. Bayesian measures of model complexity and fit. J. R. Statist. Soc. B. 4: 583-639. https://doi.org/10.1111/1467-9868.00353
Vasconcellos M., Cochrane K. 2005. Overview of world status of data-limited fisheries: Inferences from landings statistics. In: Kruse G.K. (ed.), Fisheries assessment and management in data-limited situations. University of Alaska Fairbanks, 958 pp. https://doi.org/10.4027/famdls.2005.01 PMCid:PMC4098281
Vieira J.P. 1991. Juvenile Mullets (Pisces: Mugilidae) in the Estuary of Lagoa dos Patos, RS, Brazil. Copeia 2: 409-418. https://doi.org/10.2307/1446590
Vieira J.P., Scalabrin C. 1991. Migração reprodutiva da tainha (Mugil platanus Gunther, 1980) no Sul do Brasil. Atlantica 13: 131-141.
Vieira J.P., Garcia A.M., Grimm A.M. 2008. Evidences of El Ni-o effects on the mullet fishery of the Patos Lagoon Estuary. Braz. Arch. Biol. Technol. 51: 433-438. https://doi.org/10.1590/S1516-89132008000200025
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