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World of Statistics  
SEMINÁRIO (conjunto) CEAUL/Mestrado em Bioestatística: Statistical Methods in the Assessment of Fishery Stocks - an Application
  • Profª Ivone Figueiredo - Instituto Português do Mar e Atmosfera e Prof. Nuno Brites - CIMA/Universidade de Évora
  • FCUL - Campo Grande - Bloco C8 Piso2 - Sala: 8.2.19 - 16:30h
  • Quarta-feira, 8 de Novembro de 2017
  • Referência Projeto: Projecto FCT: UID/MAT/00006/2013



The assessment of the size and state of the stocks exploited by fisheries is one of the pillars of modern fishery management. Fishery stock assessment models are demographic analyses designed to determine the effects of fishing on fish stocks and to evaluate the potential consequences of alternative harvest policies. The assessment of fish stocks is based on the use of two main classes of models: i) the production model (e.g. Schaefer, 1954) that relies on time series of an indicator of stock abundance and on fish catches and ii) cohort analysis or virtual population analysis (VPA), that depends on time series of detailed fishery catch-at-age data to reconstruct the virtual abundance of each annual cohort that had been fished (Pope, 1972; Laurec and Shepherd, 1983). The two approaches involve the use of statistical methods at the different phases such as the input data, model adjustment and analysis of the outcomes. In this talk a brief overview on the adjustment of a production model to the Hake stock (Polacheck et al. 1993) is presented. Special emphasis is given to the main underlying assumptions of the model, the statistical methods involved, as well as, the potential sources that may contribute for a poor adjustment.



Schaefer, M.B. (1954) Some aspects of the dynamics of populations, important for the management of the commercial marine fisheries. Inter-American Tropical Tuna Commission, 1, 7-56.

Pope, J.G. (1972) An investigation of accuracy of Virtual Population Analysis. Int. Comm. NW Atl. Fish. Res. Bull. 9, 65–74.

Laurec, A. and Shepherd J. G. (1983) On the analysis of catch and effort data. J. Cons. perm. Int. Explor. Mer. 41, 81-84.

Polacheck, T., Hilborn, R., Punt, A. (1993) Fitting surplus production models: comparing methods and measuring uncertainty. Canadian Journal of Fisheries and Aquatic Sciences, 50, 2597-2607.


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