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• W2078441619 abstract "Abstract The current fish stock assessment process in Europe can be very resource- and time-intensive. The scientists involved require a very particular set of skills, acquired over their career, drawing from biology, ecology, statistics, mathematical modelling, oceanography, fishery policy, and computing. There is a particular focus on producing a single “best” stock assessment model, but as fishery science advances, there are clear needs to address a range of hypotheses and uncertainties, from large-scale issues such as climate change to specific ones, such as high observation error on young hake. Key to our discussion is the use of the assessment for all frameworks to translate hypotheses into models. We propose a change to the current stock assessment procedure, driven by the use of model averaging to address a range of plausible hypotheses, where increased collaboration between the varied disciplines within fishery science will result in more robust advice." @default.
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• W2078441619 date "2014-04-01" @default.
• W2078441619 modified "2023-10-18" @default.
• W2078441619 title "Model averaging to streamline the stock assessment process" @default.
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• W2078441619 doi "https://doi.org/10.1093/icesjms/fsu043" @default.
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