Forecasting in South African pelagic fisheries management: the use of expert and decision support systems

Abstract

Understanding long-term variability of pelagic fish populations is important in developing forecasting strategies for fisheries management and planning. However, many current fisheries models have only short-term datasets available, whereas those of suitable duration often lack reliability. As resources are placed under increasing pressure, all available information should be used to assist management. Two simple rule-based deterministic modelling approaches are described, which use semi-quantitative and qualitative rules to relate recruitment success of South African anchovy Engraulis capensis to physical and biological indices. The first model relates recruitment success to indices of wind and sea surface temperature by way of a rule-based decision support system. In the second model, significant environmental and biological factors were identified and related to anchovy recruitment by way of an expert system approach. These two approaches are evaluated and compared. It is suggested that these types of models, when satisfactorily validated, have great potential in supporting the future management of the South African anchovy fishery in the dynamic environment of the Benguela Current.