Quantitative decision support tools facilitate social-ecological alignment in community-based marine protected area design

Abstract

Marine protected areas (MPAs) are increasingly used to support both biodiversity conservation and fisheries management. However, MPA performance is likely to be compromised if people who depend on fishing are excluded from MPA design decision making. Participatory MPA design helps to address this problem by engaging local stakeholders in all critical decisions, including the total coverage, placement, and local size of no-take marine reserves. Here, we report the findings from a participatory MPA design project on Selayar Island, Indonesia, in which a community initiated collaborations with scientists to access modern quantitative tools for community-led MPA scenario testing. The outcomes highlight a local disagreement between ecologically and socially desirable MPA designs. Focused on social considerations, the initial community-supported MPA design consisted of four small reserves (0.5-1 km wide) in predominately southern community waters, where they were intended to restrict external fishers. Ecologically optimal MPA designs, in contrast, consisted of one or two large reserves (4-6 km wide) in northern community waters, where they were expected to restrict primarily local fishers but better support the rebuilding of fish populations and fisheries. However, ecologically optimal MPA designs were socially infeasible. Using quantitative MPA performance assessments, the community negotiated an alternative MPA design consisting of two 1.5-2 km wide reserves at socially and ecologically favorable locations. Compared to the initial proposal, this revised MPA design was estimated (1) to protect three to four times more individuals of key fishery species within reserve boundaries and (2) to double local fishery catches. We conclude that even simple MPA design tools, which quantify and visualize local conservation and fishery outcomes under alternative MPA scenarios, add value to participatory decision making and likely MPA performance.

Using Gaming Technology to Explore and Visualize Management Impacts on Marine Ecosystems

“…Despite its limitations and potential improvements, upsurges in the interest in stakeholder-driven ecosystem management supported by decision support tools (Pınarbaşı et al, 2017;Keijser et al, 2018;Ernst, 2019;Krueck et al, 2019), and the emergence of ecological decision support tools that not only support the full problem solving cycle but also provide visions of the future based on plausible solutions (Steenbeek et al, 2020), have led us to believe that OceanViz may hold potential for this renewing landscape. EwE ecosystem models are increasingly being used for ecosystem-based fisheries management and integrative assessments (Christensen and Walters, 2011;.…”

Community champions of ecosystem services: The role of local agency in protecting Indonesian coral reefs

“…With their broad and strong capabilities and networks, champions can facilitate the resolution of natural resource management conflicts (Ross et al, 2019;Abdurrahim et al, 2020a,b;Hastuti and Abdurrahim, 2021), inspire and encourage participation of others in their communities (Cockburn et al, 2019) and increase the effectiveness of landscape management (van Noordwijk et al, 2020). Local champions can help their communities to collaborate with government, scientists, and other key stakeholders to increase the effectiveness of marine and fisheries conservation (Krueck et al, 2019). Champions may find solutions for resource issues through a collaborative process emphasizing choice, trust, and feedback mechanisms (Desrochers and Szurmak, 2020).…”

An MPA Design Approach to Benefit Fisheries: Maximising Larval Export and Minimising Redundancy

“…Settled juveniles were then subjected to density dependent mortality before entering the adult population by calculating recruitment according to a Beverton-Holt stock-recruitment relationship [35]. Further detail on principal equations and procedures used are available in multiple previous studies [22,36].…”