Development of a spatial Decision Support System (DSS) for the Spencer Gulf penaeid prawn fishery, South Australia

Abstract

The Spencer Gulf penaeid prawn fishery in South Australia has undergone a substantial increase in fishing efficiency (and profitability) mainly due to the implementation of adaptive harvest strategies requiring rapid response for change to harvesting plans. This paper describes the management background and the decision-making process leading to the development of a basic Decision Support System (DSS) that uses spatial information techniques and near real-time fishery-independent survey data. The system is implemented through linking an Oracle database to ArcGIS, Genstat and Splus. Two examples show the application of the DSS for optimal harvest timing and assessment of fishery sustainability. Fishery-independent survey data are used to assess stock and model population growth. The first example shows the information flow leading to a dynamic stock model and the estimate of value change as a function of harvest time. The second example shows how the DSS is used to validate and refine existing biological reference limits by evaluating long-term detailed data sets of the prawn population structure and catch dynamics. We conclude that it is important for the economic benefit and sustainability of the fishery to maintain and improve the collection of long-term data sets that are independent of commercial fishery statistics.