
Abstract Simulation models are used extensively to evaluate the performance of fisheries management strategies, though they must be validated to ensure that they accurately represent the real system. One of the quantitative methods available to advance in the process of validating simulation models is global sensitivity analysis (GSA). However, its use in fisheries management has been very limited. When GSA is applied to management strategy evaluation implementations, it can also help manage available resources efficiently with respect to uncertainty in the management process and the conditioning of simulation models. Mixed-fisheries management plans were recently implemented for demersal fisheries in the Northeast Atlantic, which were evaluated previously using complex bioeconomic models. Here, we applied GSA to the model used in Iberian waters, employing an efficient model design to introduce uncertainty in every single input factor. While most biological factors contributed significantly to the variance of results, only few economic factors did. Moreover, we found that increasing accuracy in the stock assessment process would mainly impact management advice and that only the management of target stocks had a real impact on the system. This highlights the importance of properly managing hake (Merluccius merluccius), which is currently managed using an empirical harvest control rule.
DYNAMICS, HARVEST STRATEGIES, IMPACT, data-limited stocks, MODELS, GLOBAL SENSITIVITY-ANALYSIS, simulation, bioeconomic modelling, VALIDATION, STOCK ASSESSMENT, uncertainty conditioning, fisheries management, FISH, REFERENCE POINTS, global sensitivity analysis, BAY
DYNAMICS, HARVEST STRATEGIES, IMPACT, data-limited stocks, MODELS, GLOBAL SENSITIVITY-ANALYSIS, simulation, bioeconomic modelling, VALIDATION, STOCK ASSESSMENT, uncertainty conditioning, fisheries management, FISH, REFERENCE POINTS, global sensitivity analysis, BAY
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