tailieunhanh - A meta-analytic approach to quantifying scientific uncertainty in stock assessments

As set out in Appendix 1, we assume that there will be 12,258 vehicles in service in April 2014. In our Medium scenario, the total fleet size increases to 14,062 vehicles by the end of March 2019, a net increase of 1,804 vehicles. The Thameslink, Crossrail and IEP procurements will add, as a central estimate, around 2,500 vehicles to the fleet. On a like-for-like basis this will therefore displace around 700 vehicles. We identified 3,222 vehicles (Appendix 2) reaching the end of their nominal terms of use during CP5. Therefore by the end of CP5, there. | 217 Abstract Quantifying scientific uncertainty when setting total allowable catch limits for fish stocks is a major challenge but it is a requirement in the United States since changes to national fisheries legislation. Multiple sources of error are readily identifiable including estimation error model specification error forecast error and errors associated with the definition and estimation of reference points. Our focus here however is to quantify the influence of estimation error and model specification error on assessment outcomes. These are fundamental sources of uncertainty in developing scientific advice concerning appropriate catch levels and although a study of these two factors may not be inclusive it is feasible with available information. For data-rich stock assessments conducted on the . west coast we report approximate coefficients of variation in terminal biomass estimates from assessments based on inversion of the assessment of the model s Hessian matrix . the asymptotic standard error . To summarize variation among stock assessments as a proxy for model specification error we characterize variation among multiple historical assessments of the same stock. Results indicate that for 17 groundfish and coastal pelagic species the mean coefficient of variation of terminal biomass is 18 . In contrast the coefficient of variation ascribable to model specification error . pooled among-assessment variation is 37 . We show that if a precautionary probability of overfishing equal to is adopted by managers and only model specification error is considered a 9 reduction in the overfishing catch level is indicated. Manuscript submitted 20 September 2010. Manuscript accepted 23 February 2011. Fish. Bull. 109 217-231 2011 . The views and opinions expressed or implied in this article are those of the author or authors and do not necessarily reflect the position of the National Marine Fisheries Service NOAA. A meta-analytic approach to quantifying .

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