WAMSI Node 3.2.3 - An Evaluation of Management Strategies for Line Fishing in the Ningaloo Marine Park

Brief description

This project was developed for the Ningaloo Research Program (NRP) to explore the effects of managing recreational fishing, which is perhaps the most important extractive activities in the Ningaloo Marine Park. The project used simulation techniques known as Management Strategy Evaluation (MSE) to explore the consequences of a range of management actions, under a series of alternative future scenarios on the management of a major target species on Ningaloo Reef, spangled emperor (Lethrinus nebulosus). The results of the scenarios are examined against the objectives set out by management and other stakeholders in the park. A simulation model, known as ELFSim, was used. ELFSim is a decision support software system designed to evaluate options for conservation and harvest management, and includes a number of key components: a population dynamics model of target species that captures the full life history (including larval dispersal, reproduction, development, and habits) of the target species, a model of fishing dynamics that captures the exploitation pattern due to fishing behaviour, a management model that simulates the implementation of management actions. ELFSim was developed for other coral reef fisheries where commercial fishing was the primary fishing activity, and in this sought to develop a simulation model of recreational fishing dynamics. This model was agent-based, meaning that individual recreational fishing boats were represented in the model, and a range of management measures were tested on the ability to manage these virtual recreational fishers. These management measures, derived from stakeholder workshops include the effect of increasing the no-take sanctuary zones, and restricting the fishing in sanctuary zones that occurs from shore. The effectiveness of these management actions in the simulation model was measured against the management objectives of the stakeholders. Management objectives were classified according to ecological (conservation) objectives, or social and economic objectives. The results showed that the current management arrangement perform adequately against the range of ecological and social objectives. However, for other management actions, the results showed the inherent trade-off that exists between the ecological objective and the social objectives. For example, restricting fishing in sanctuaries from shore did well to achieve the conservation objectives, but did not achieve the social objectives as well as other management strategies. Imposing catch restrictions, increasing compliance monitoring and implementing an education program to reduce infringement also performed well against both social and ecological objectives, but consideration of effectiveness, and cost are uncertainties that our analysis did not consider. Such factors are likely to be extremely important and weighed in any realistic implementation of these management actions. Under the alternative scenarios the management strategy that was most likely to achieve the objectives was the hypothetical "Catch Limit" . The management strategy that allowed effort to increase was best at achieving the social objective of maximizing catches, including the catch of large fish. Although the simulations indicated that the "Catch Limit" strategy as an effective strategy for future alternative scenarios, in practice a combination of strategies limiting effort, or something else quite novel and resource intensive (like pink snapper tags in Freycinet Estuary in Shark Bay, WA for implementing a recreational Catch Limit), may need to be used for indirectly limiting the overall level of catch of spangled emperor from this sector. Of course such a strategy is also species specific and does not limit potential sustainability risks for other species. It is for this reason that DoFWA uses spangled emperor as an indicator species for the suite of demersal scalefish species in the Gascoyne Bioregion.

Lineage

Progress Code: completed

Maintenance and Update Frequency: notPlanned

Statement: See WAMSI Node 3.2.3 Final report for details.

Notes

Credit
Beth Fulton and Miriana Sporcic of CSIRO for collaborative efforts. Dan Gaughan (DoFWA) for his input at the start of the project, and all of the stakeholders including Kelly Waples and Chris Simpson, who attended our workshops. Russ Babcock and Bill de la Mare (CSIRO) provide much needed advice throughout the project. We also thank Norm Hall, Lyndsay Joll and Brett Molony for their helpful comments on earlier drafts. Wendy Steele (CSIRO) is thanked for her efficient project management.

Credit
Rich Little (Rich.LittleAcsiro.au) Olivier Thébaud (Olivier.Thebaud@csiro.au) Fabio Boschetti (Fabio.Boschetti@csiro.au) A. David McDonald (David.McDondald@csiro.au) Ross Marriott (Ross.Marriott@fish.wa.gov.au) Brent Wise (Brent.Wise@fish.wa.gov.au) Rod Lenanton (Rod.Lenanton@fish.wa.gov.au)