Uncertainty and risk associated with optimised fishing patterns in a tropical penaeid fishery

Simulation was used to improve the management of prawn fisheries by indicating patterns of fishing effort which favour the harvest of more highly valued, larger animals. Attempts to use conventional local optimisation methods to find the optimum pattern of weekly fishing efforts were ineffective. Simulating annealing, a global optimisation method, was used effectively to find fishing effort patterns which maximised catch values. Sensitivity of the maximum catch value to the parameters used to model fishing and biological behaviour was also investigated. The optimum catch value was not sensitive to variations in trawl net selectivity or catchability parameters, although the optimum fishing season to obtain these maxima altered. In contrast, changes to biological parameters had a notable effect on the maximum catch value, despite compensatory changes to the optimum weekly pattern of fishing effort. The risk associated with achieving management goals using a range of fishing strategies was also assessed when recruitment timing and growth rates were modelled as partly stochastic. With uncertainty in recruitment timing, it was found that the optimum fishing pattern did not change. Uncertainty in growth rates made fishing earlier the best strategy, and increased harvest values in 43% of simulations. Simulation was used to improve the management of prawn fisheries by indicating patterns of fishing effort which favour the harvest of more highly valued, larger animals. Attempts to use conventional local optimisation methods to find the optimum pattern of weekly fishing efforts were ineffective. Simulating annealing, a global optimisation method, was used effectively to find fishing effort patterns which maximised catch values. Sensitivity of the maximum catch value to the parameters used to model fishing and biological behaviour was also investigated. The optimum catch value was not sensitive to variations in trawl net selectivity or catchability parameters, although the optimum fishing season to obtain these maxima altered. In contrast, changes to biological parameters had a notable effect on the maximum catch value, despite compensatory changes to the optimum weekly pattern of fishing effort. The risk associated with achieving management goals using a range of fishing strategies was also assessed when recruitment timing and growth rates were modelled as partly stochastic. With uncertainty in recruitment timing, it was found that the optimum fishing pattern did not change. Uncertainty in growth rates made fishing earlier the best strategy, and increased harvest values in 43% of simulations.