Ranking management strategies with complex outcomes: An AHP-fuzzy evaluation of recreational fishing using an integrated agent-based model of a coral reef ecosystem

Abstract

The management of recreational fishing requires resolving conflicting interests and is thus among the most controversial natural resource related issues. Decision making is difficult because of two main factors: first, there is lack of prediction tools that help managers and other stakeholders assess the potential impacts of management changes; second, decisions or management strategies affect multiple social and ecological outcomes and picking the best among sets of multiple outcomes is a complex task. Resource management and stakeholder dialogue can be greatly improved by addressing these problems. In this paper, we propose a decision support system (DSS) for assessing management strategies. The DSS incorporates an integrated agent-based simulation model for tackling the first obstacle and an analytical hierarchy process (AHP)-fuzzy comprehensive evaluation approach to facilitate multi-criteria decision making.The agent-based simulation model incorporates recreational fishing behaviour within a reef ecosystem. Angler behaviour is driven by empirically estimated site choice models which link recreational choices to site attributes and angler characteristics. Coral reef ecosystem dynamics is modelled using a trophic-dynamic model describing the relationship among fish populations, fishing activities as well as algal and coral growth. The second component of the DSS, the AHP-fuzzy comprehensive evaluation part, allows one to combine resource managers’ preferences with simulated economic and ecosystem outcomes in the assessment of alternative strategies. A fuzzy multi-criteria, multi-layer evaluation method is used to obtain final ranking.As a case study for this paper, we focus on the management of recreational fishing sites from the Ningaloo Marine Park, an iconic coral reef system in Western Australia. A set of management strategies, including a “business-as-usual” strategy and alternative site closure strategies are assessed using the proposed DSS. The site closure strategies evaluated vary in length and timing. Further, these evaluations are undertaken for two fishing pressure scenarios (high and low). We illustrate the usefulness of the DSS by evaluating these strategies. We also present some results from a sensitivity analysis focussing on changes in preferences.