Fishing for insights: Tailoring a relevant choice experiment to explore low-literate community preferences in the design of marine protected areas

Abstract

Discrete choice experiments (DCEs) can help explore stakeholders' preferences in the design of policy interventions, including nature conservation efforts. For a DCE to yield relevant and valid results, the careful selection of attributes and attribute levels is crucial. In this study, we offer a systematic mixed-methods approach to tailor highly pertinent DCEs conducted within low-literate communities, involving the use of a novel pictorial-based scoring tool. We illustrate our approach with a case study, describing how attributes and attribute levels were selected for a future DCE investigating local community preferences in the design of marine protected areas (MPAs) in Senegal. By 2030, the United Nations aims to protect 30 % of the ocean, which requires tripling the global coverage of MPAs, with a significant expansion expected in low-income countries. Social support, which largely depends on stakeholders’ perceptions, is essential for MPAs to achieve their conservation goals. MPAs vary in governance, management, and surrounding development features. In our case, MPA users, who depend on these areas for their livelihoods, identified the development of infrastructure for the fishing sector and basic community needs as the most impactful MPA features. Significant differences were noted between stakeholder groups: men underscored the importance of conflict resolution mechanisms, communication methods, and MPA boundary visibility, while women stated being more affected by specific fishing restrictions. In addition, MPA managers and officers did not fully grasp community members' perceptions. These findings highlight the need for managers to regularly consult local communities within MPAs using appropriate tools in order to ensure their long-term success. Our study allowed us to identify the most relevant attributes and levels in our case. The semi-qualitative approach proposed to DCE design offers a valuable tool for researchers planning to conduct DCEs in low-literate communities, helping them optimise their study design and ensure relevant findings.