A two-stage biomass dynamic model for Bay of Biscay anchovy: a Bayesian approach
1 AZTI-Tecnalia, Txatxarramendi Ugartea z/g, 48395 Sukarrieta, Spain, and Mathematics and Statistics, Lancaster University, Lancaster, LA1 4YF, UK
2 IEO, Centro Oceanográfico de Vigo, Cabo Estai—Canido, Apartado 1552, 36200 Vigo, Spain
3 AZTI-Tecnalia, Herrera Kaia Portualdea z/g, 20110 Pasaia, Spain
4 Cefas, Pakefield Road, Lowestoft, Suffolk NR33 0HT, UK
Correspondence to L. Ibaibarriaga: tel: +34 94 602 94 00; fax: +34 687 00 06; e-mail: libaibarriaga{at}suk.azti.es
Ibaibarriaga, L., Fernández, C., Uriarte, A., and Roel, B. A. 2008. A two-stage biomass dynamic model for Bay of Biscay anchovy: a Bayesian approach. – ICES Journal of Marine Science, 65: 191–205.A two-stage biomass-based state-space model with stochastic recruitment processes and deterministic dynamics was developed for the Bay of Biscay anchovy population. It is fitted in a Bayesian context with posterior computations carried out using Markov chain Monte Carlo techniques. The model is tested first on a simulated dataset and the effects of different modelling assumptions and of missing values evaluated. Then, it is applied to a real historical series of commercial catch and survey data from 1987 to 2006. Results are compared with those obtained by the standard assessment model for this stock, integrated catch-at-age analysis (ICA). From the posterior distribution of biomass in the latest year (2006), the distribution of unexploited biomass in 2007 can be derived assuming the distribution of recruitment in 2007 to be a mixture of the posterior distributions of past series recruitment. Hence, the effect of different catch options on future biomass levels can be quantified in probabilistic terms. Finally, directions for possible further improvements are indicated.
Keywords: anchovy, Bayesian, Markov chain Monte Carlo, mixture distribution, state-space model, stock assessment
Received 2 March 2007; accepted 23 December 2007.
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