The demersal mixed-fisheries operating in the Bay of Biscay catch more than 150 species, but only eight of them are included in the Western Waters and adjacent waters multiannual management plan. This raises the issue of whether the current multiannual management plan is sufficient to ensure the sustainability of the whole system. In this PhD Thesis, we evaluated the impact of current and alternative management strategies on the sustainability of the system in a simulated reality. In comparison to previous works, we broadened the scope of the work to non-target and data-limited stocks. First, we applied a stock prioritization approach to identify the stocks most at risk, most exploited, and/or economically most important for the fishery. The potential risk was calculated using the Productivity-Susceptibility Analysis (PSA). Then, we evaluated by self-test simulation the ability of a low data-demand assessment model like Stock Reduction Analysis (SRA) to provide accurate population estimates under alternative data availability, population exploitation levels and initial population assumptions. This allowed us to identify the data-limited stocks whose dynamics could be reliably mimicked based on the SRA model. Finally, we evaluated the performance of current and alternative management strategies. The simulation included 28 stocks: 13 had age-structured population dynamics (9 data-rich stocks based on analytical assessments and 4 data-limited stocks using SRA model) and for 15 stocks the catch was proportional to the effort level and independent of their abundance. The obtained results contributed to providing a holistic evaluation of the management of the mixed-fisheries operating in the Bay of Biscay. // The demersal mixed-fisheries operating in the Bay of Biscay catch more than 150 species, but only eight of them are included in the Western Waters and adjacent waters multiannual management plan. This raises the issue of whether the current multiannual management plan is sufficient to ensure the sustainability of the whole system. In this PhD Thesis, we evaluated the impact of current and alternative management strategies on the sustainability of the system in a simulated reality. In comparison to previous works, we broadened the scope of the work to non-target and data-limited stocks. First, we applied a stock prioritization approach to identify the stocks most at risk, most exploited, and/or economically most important for the fishery. The potential risk was calculated using the Productivity-Susceptibility Analysis (PSA). Then, we evaluated by self-test simulation the ability of a low data-demand assessment model like Stock Reduction Analysis (SRA) to provide accurate population estimates under alternative data availability, population exploitation levels and initial population assumptions. This allowed us to identify the data-limited stocks whose dynamics could be reliably mimicked based on the SRA model. Finally, we evaluated the performance of current and alternative management strategies. The simulation included 28 stocks: 13 had age-structured population dynamics (9 data-rich stocks based on analytical assessments and 4 data-limited stocks using SRA model) and for 15 stocks the catch was proportional to the effort level and independent of their abundance. The obtained results contributed to providing a holistic evaluation of the management of the mixed-fisheries operating in the Bay of Biscay.
© 2001-2024 Fundación Dialnet · Todos los derechos reservados