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Policy Analysis and the Incorporation of Biological Objectives into Fishery Management Decisions

  • Thomas M. Leschine
  • M. C. Healey
Conference paper
Part of the Lecture Notes on Coastal and Estuarine Studies book series (COASTAL, volume 28)

Abstract

management has revitalized and seemingly rationalized a complex and fragmented management system. With renewed emphasis on applying a mix of conservation and exploitation objectives in management decisions, attention has been focused on how well particular objectives have fared under these new management regimes. Strategies for advancing conservation or biological objectivcs, or for treating all the objectives of management comprehensively and explicitly in decisions, have been advanced with increasing frequency. Yet schemes emphasizing comprehensive prior evaluation of proposed management policies (decision analysis) or emphasizing evaluation of the results of management initiatives with feedback to policy design (adaptive management) have achieved very limited acceptance by managing agencies to date. Empirically derived theories of organizational decision-making behavior under conditions like those which prevail in OY-based fishery management suggest that decision-making processes will differ significantly from the expectations of these schemes. Observations of U.S. fishery management systems tend to corroborate these theories. These realities will have to be better accounted for if proposed policy analytic schemes to aid fishery management decisions are to gain significant acceptance. Implementationlevel considerations suggest that the ideas underlying the emerging concept of “decision support” systems are much more in tune with the needs of OY oriented fisheries managers than present decision theory-based paradigms.

Keywords

Decision Maker Decision Analysis Adaptive Management Fishery Management Maximum Sustainable Yield 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1988

Authors and Affiliations

  • Thomas M. Leschine
    • 1
  • M. C. Healey
    • 2
  1. 1.Institute for Marine StudiesUniversity of WashingtonUSA
  2. 2.Pacific Biological StationNanaimoCanada

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