Environmental Modelling & Software 22 (2007) 137e148 www.elsevier.com/locate/envsoft
Development of a spatial Decision Support System (DSS) for the Spencer Gulf penaeid prawn fishery, South Australia N.A. Carrick a, B. Ostendorf b,* b
a 19 Osborn Avenue, Beulah Park, Adelaide, South Australia, 5067, Australia School of Earth and Environmental Sciences, University of Adelaide, Glen Osmond, South Australia, 5064, Australia
Received 11 October 2004; received in revised form 13 June 2005; accepted 14 July 2005 Available online 17 November 2005
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. Ó 2005 Elsevier Ltd. All rights reserved. Keywords: DSS; Reference points; Real-time management; Adaptive harvest strategies; Harvest model; Sustainability; Biological reference points; Profitability; Oracle; GIS
Software availability
1. Introduction
DSS data: Partly classified government property and cannot be distributed. A standard export file of the Oracle database constituting the core of the DSS can be requested from the corresponding author without charge Name: PRS Developers: Rowan Hoskins, Neil Carrick First available: 2005 Minimum hardware requirements: 1 GHz, 256 MB RAM Software requirements: Operating system Win 2000, NT, XP Language: English
There are three prawn fisheries in South Australia e Spencer Gulf, Gulf St Vincent and West Coast e all of which are based exclusively on the western king prawn Melicertus latisulcatus (Penaeidae). The Spencer Gulf fishery (Fig. 1) is the largest Australian producer of western king prawns and is one of five Australian commercial trawl fisheries that produce more than 1500 t per annum. Descriptions of the fishery, prawn fishery biology and management are documented (Carrick, 1982, 1996, 2003; Carrick and Ostendorf, 2005). It has long been recognized by research and members of the Spencer Gulf prawn fishing industry that fishery sustainability can only be maintained if fishing effort is constrained and directed in space and time, with an adaptive and real-time management approach. Adaptive harvest policy changes are
* Corresponding author. University of Adelaide, Glen Osmond, SA 5064, Australia. Tel.: þ61 8 8303 7210; fax: þ61 8 8303 6717. E-mail address:
[email protected] (B. Ostendorf). 1364-8152/$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.envsoft.2005.07.025
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N.A. Carrick, B. Ostendorf / Environmental Modelling & Software 22 (2007) 137e148
Fig. 1. Geographical location of the South Australian prawn fisheries.
expected to improve yield and economic performance compared to simpler regulatory systems that do not take advantage of information about changes in distribution and abundance and spatio-temporal changes in prawn size composition. Such limitations on harvest strategies (e.g. closures and controls of trawl effort) are often difficult to define and the interests of individuals in the fishing industry may influence management decisions with a potential impact on the fishery. Discussions about how to limit the spatial and temporal extent of fishery trawl closures and the amount of trawl effort (and catch) will always occur within the fishing industry. This is where objective decision support is needed the most (Walters and Ludwig, 1987; Hilborn and Walters, 1992) yet few integrated intelligent systems based on fishery-independent survey and commercial catch and effort data have been developed in fisheries for the evaluation and prediction of stock and for the determination of allowable catch levels (Riolo, in press; Sazonova et al., 1999; Walters and Collie, 1989). The objectives of this paper are to describe the Spencer Gulf prawn industry, the need for management, and the constraints to the design of a DSS due to government regulations. We show how a basic DSS is used to address these issues and recommend that impediments hindering innovation and further development of database systems and the DSS be removed through industry having a larger role in the research and management process. We show two examples of how the DSS is used to increase fishery profitability and fishery sustainability.
1.1. Management of the fishery Industry has an important role in the fishery decisionmaking process through a Fishery Management Committee (FMC) consisting of members of industry and government. Real-time adaptive management is undertaken by a subcommittee of the FMC, the ‘‘Committee at Sea’’ and government (Primary Industries and Resources South Australia, PIRSA). Government management policy has instilled strict guidelines for research and management, including requirements for mandatory completion by fishers of fishery catch and effort logbooks, fishery-independent trawl surveys for stock assessment and fine-tuning of harvest strategies. The priority in the management of the prawn fisheries is to ensure that the fishery is sustainable so that future generations may benefit from the exploitation of the resource. Primary management objectives for the Spencer Gulf fishery are as follows: To maintain the biomass within historical levels and eliminate the risk of recruitment decline due to overfishing; To ensure harvesting procedures are directed towards optimising size at capture; To maintain and enhance the profitability of the fishery by optimising prawn size, market timing, minimising the costs of fishing and the administrative costs of managing the fishery; and To minimise bycatch and trawl impact to the benthos through the development of more effective and efficient gear and harvesting strategies.
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Caddy and McMahon (1995) and others have provided a detailed background into the conceptual and applied aspects of reference points for fisheries management. Reference points allow a decision framework to be developed, however, reference points and performance indicators need to be updated and refined regularly. This is particularly important as reference points are to a large degree based on anecdotal knowledge as long-term consistent and detailed data are not available, however, a continuous stream of current and future fishery data will allow these reference points to be substantiated. Reference points provide a quantitative measure of a performance indicator that is used as a benchmark of performance against objectives, and can be used to trigger a management response. They are agreed and quantitative measures used to assess the performance of the fishery based on defined management objectives. Government, in collaboration with industry developed the biological reference points for the Spencer Gulf fishery. The reference points that drive the requirements for information collection are as follows:
areas are opened and closed based on the size of prawns, catch rates, depletion, spawning status and likely migration patterns of prawns. The types of closures in Spencer Gulf consist of the following:
Maintain exploitation rates at present levels of effort. The target reference point for effective effort is between 70 and 80 fishing nights, while the limit reference point is 80 effective effort nights. Effective effort is a function of the amount of trawl effort (hours, days) and the fishing power (or catching efficiency) of the fleet. Maintain at least 50% of the virgin spawning biomass. This target indicator is the level of the recruit of the year spawning biomass, which remains after fishing and is assessed in NovembereDecember. The limit reference point for protecting the resource is that exploitation should not reduce the stock to a level of less than 40%. Maintain the recruitment index at a level that ensures suitable recruitment to the fishery. The reference point is based on the assessment of recruits to grounds in the February period of each year. The target reference point developed by management (Morgan, 1996) is the number of prawns (male and female) 2000 recruits/nm) occurred most frequently when the catch of spawners was 43 mm CL, whilst recruits were male and female prawns
