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The state of the art in stock assessment: where we are and where we are going
Hilborn, R. (2003). The state of the art in stock assessment: where we are and where we are going, in: Ulltang, Ø. et al. Fish stock assessments and predictions: integrating relevant knowledge: SAP Symposium held in Bergen, Norway 4-6 December 2000. Scientia Marina (Barcelona), 67(Suppl. 1): pp. 15-20
In: Ulltang, Ø.; Blom, G. (2003). Fish stock assessments and predictions: integrating relevant knowledge: SAP Symposium held in Bergen, Norway 4-6 December 2000. Scientia Marina (Barcelona), 67(Suppl. 1). Institut de Ciències de Mar: Barcelona. 374 pp., more
In: Scientia Marina (Barcelona). Consejo Superior de Investigaciones Científicas. Institut de Ciènces del Mar: Barcelona. ISSN 0214-8358, more
Peer reviewed article  

Also published as
  • Hilborn, R. (2003). The state of the art in stock assessment: where we are and where we are going. Sci. Mar. (Barc.) 2003: 15-20, more

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Document type: Conference paper

Keywords
    Fisheries; Fishery management; Models; Stock assessment; Marine

Author  Top 
  • Hilborn, R.

Abstract
    Throughout the world's major commercial fisheries the standard paradigm includes fitting a stock assessment model to the data and then applying some form of reference point or a range of reference points, usually a target exploitation rate, to calculate a point estimate of the annual allowable catch. Over the last decade the methods available to be used in these models have changed dramatically from those using only catch, catch-at-age and survey or CPUE data to methods that now use every source of data available in a totally integrated framework. The use of meta-analysis has provided formal statistical methods for incorporating information learned from other stocks. Modern methods make it possible to express uncertainty in all model outputs, but management agencies are only now learning to deal with explicit recognition of uncertainty and have lagged far behind the scientific capability to express uncertainty. While modern stock assessment models have grown increasingly complex and their development is limited to a priesthood of experts, I believe the future trend will be to base management decisions on simple rules that are more often data-based rather than model-based, while the complex models will serve primarily to evaluate the robustness of these decision rules

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