OSS: A Spatial Decision Support System for Optimal Zoning of Marine Protected Areas

© MODSIM 2005 - International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making, Proceedings. All rights reserved. We have developed the Optimisation Support System (OSS), a spatial decision support system, to deliver optimal solutions to the problem of identifying comprehensive, adequate and representative locations for conservation planning. The South Australian Government is committed to establishing a comprehensive, adequate and representative system of 19 marine protected areas (MPAs) by 2010. Each MPA will be the target for detailed investigations into its biophysical, ecological, social, economic and cultural assets. The aim is to use this information to delineate each MPA into a series of zones that offer various levels of protection and use. At the highest level all marine use and extraction activities will be excluded to allow maximum protection of species diversity and habitat. Community consultation and collaboration is therefore critical for successful MPA establishment. A demand exists for the development of a process that allows public participation within a conservation planning environment. The concept of excluding certain activities, including recreational fishing, has generated much interest in the local media. Recent headlines such as 'Calls to Shelve Marine Parks', 'Anglers Fight For Future of Jetty Fishing' and '330+ Submissions on MPA Proposal' demonstrate the importance of open consultation and the need to provide an inclusive and transparent decision-making process for the design of MPAs. A decision support tool can facilitate decision-making within a negotiating and conflict resolution environment. We have collated and processed a large database of spatial layers describing the biophysical and human-use features of the marine environment. The biophysical data was then used to identify surrogate ecological regions within the Encounter Pilot MPA. The datasets were categorised into classes describing bathymetry, sea surface temperature, chlorophyll 'a' concentration levels, benthic and coastal habitat types, and shoreline exposure and type. Locations that most efficiently represent these surrogates of biodiversity were selected using a common mathematical integer programming optimisation algorithm. Established conservation planning principles underpin this research. Inputs into OSS are a suite of environmental, social, cultural and economic datasets. Optimal solutions are found using integer programming algorithms. Implementation is within a Geographic Information System environment (ESRI's ArcGIS) and third-party commercial software (ILOG's CPLEX) provides the optimisation engine. The user interface of OSS can be accessed through a toolbar button and comprises a series of input modules. Fields are quick and easy to populate and in many cases are read directly from an ArcGIS map document Table of Contents. Solutions are found in less than 1 minute when using datasets described in this paper This paper briefly demonstrates the application of systematic conservation planning to optimal MPA design and the development of OSS, and explores options for public participation. We demonstrate how OSS and systematic conservation planning can be taken to the wider community to produce on-the-fly outputs. Our novel approach has the potential to build partnerships with community groups and give the community a sense of ownership in the decision-making process. It is more likely that conflicts will be minimised and negotiation hastened for a better MPA zoning outcome for all.