Designing intelligent management strategies for shrimp aquaculture systems require recognising the uncertainty and risks associated with different processes of aquaculture production. To account for natural variability and other sources of uncertainty, estimates of appropriate aquaculture bio‐economic indicators are needed to re‐evaluate periodically the production system and establish new reference points and corresponding management strategies. This paper concentrates on this aspect of the management process and presents a simple classification of indicators and reference points for aquaculture production systems. The uncertainty causing variability in the estimated values of bio‐economic parameters is incorporated through the use of Monte Carlo analysis to estimate the probability of exceeding limit reference points. To illustrate this process, the risks (i.e. probabilities of exceeding bioeconomic limit reference points) associated to alternative timing of harvesting decisions were estimated by randomly generating uncertain prices and natural mortalities with the appropriate probability density functions and corresponding variance. Alternative approaches to deal with risk and uncertainty in data limited management contexts are discussed.
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Juan Carlos Seijo (2004) studied this question.
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