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ICES Journal of Marine Science: Journal du Conseil 2000 57(3):731-741; doi:10.1006/jmsc.2000.0737
© 2000 by ICES/CIEM International Council for the Exploration of the Sea/Conseil International pour l'Exploration de la Mer
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Design of operational management strategies for achieving fishery ecosystem objectives

Keith J. Sainsbury, André E. Punt and Anthony D. M. Smith

Division of Marine Research, CSIRO GPO Box 1538, Hobart, Tasmania 7001, Australia Tel: +61 3 6232 5369; fax: +61 3 6232 5199; e-mail: Keith.Sainsbury{at}marine.csiro.au

Ecosystem objectives in fisheries management usually flow from high-level national policies or strategies and international agreements. Consequently they are often broadly stated and hence are difficult to incorporate directly in management plans. Predicting the results of any management action is very uncertain because the dynamics of ecosystems are complex and poorly understood. Methods to design and evaluate operational management strategies have advanced considerably in the past decade. These management-strategy-evaluation (MSE) methods rely on simulation testing of the whole management process using performance measures derived from operational objectives. The MSE approach involves selecting (operational) management objectives, specifying performance measures, specifying alternative management strategies, and evaluating these using simulation. The MSE framework emphasizes the identification and modelling of uncertainties, and propagates these through to their effects on the performance measures. The framework is outlined and illustrated by three ecosystem-related applications: management of benthic habitats and broad fish community composition; by-catch of species of high conservation value; and food-chain interactions and dependencies. Challenges to be overcome before broader ecosystem-related objectives can be fully handled are discussed briefly.

Keywords: ecosystem indicators, ecosystem objectives, fisheries management, management strategy evaluation (MSE), operational management strategies (design and evaluation), uncertainty


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