Development of a Bayesian framework for data limited stock assessment methods and management scenarios proposal. Case studies of cuttlefish (Sepia officinalis) and pollack (Pollachius pollachius)

Abstract : The assessment and the management of fish stocks aim at achieving a sustainable exploitation of the resources provided by the oceans. While progress have been made in this field for some stocks of great commercial importance, the situation is different for the so-called “data limited” stocks. Often historically less exploited, these stocks do not benefit from the same economical resources nor workforce to conduct the stock assessments required to set management measures. This work is based on two case studies, pollack (Pollachius pollachius) and cuttlefish (Sepia officinalis). The aim is to investigate the stock assessment methods adapted to data-limited situations. A first introductive part presents the background of fish stock assessment as well as the two case studies. This first chapter is followed by a review of data-limited stock assessment methods. The third part compare the results of a two-stage biomass model with the results of a multi-annual generalized depletion model applied to the English Channel stock of cuttlefish. An improved version of the Bayesian two-stage biomass model is also presented. In the fourth part, a Stock Synthesis model based on integrated analysis methods is applied to the stock of pollack in the Celtic Seas Ecoregion. The results are compared to the results of simpler models which require less data. The Stock Synthesis model results are sensitive to the assumptions on the natural mortality value, which relies on the growth parameters of the stock. The fifth part presents the collection and analysis of new data which will allow a better estimate of pollack stock status. A Bayesian hierarchical model is constructed, allowing information transfer between three stocks and the update of pollack biological parameters. The last chapter concludes this work by summarizing the main results. The discussion is extended to the research perspectives.
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Juliette Alemany. Development of a Bayesian framework for data limited stock assessment methods and management scenarios proposal. Case studies of cuttlefish (Sepia officinalis) and pollack (Pollachius pollachius). Agricultural sciences. Normandie Université, 2017. English. ⟨NNT : 2017NORMC229⟩. ⟨tel-01768150⟩

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