Integrating socioeconomic and ecological data into restoration practice

Abstract

Driven by the United Nations Decade on Restoration and international funding initiatives, such as the Mangrove Breakthrough, investment in mangrove restoration is expected to increase. Yet, mangrove restoration efforts frequently fail, usually because of ad hoc site-selection processes that do not consider mangrove ecology and the socioeconomic context. Using decision analysis, we developed an approach that accounts for socioeconomic and ecological data to identify sites with the highest likelihood of mangrove restoration success. We applied our approach in the Biosphere Reserve Marismas Nacionales Nayarit, Mexico, an area that recently received funding for implementing mangrove restoration actions. We identified 468 potential restoration sites, assessed their restorability potential based on socioeconomic and ecological metrics, and ranked sites for implementation with spatial optimization. The metrics we used included favorable conditions for propagules to establish and survive under sea-level rise, provision of ecosystem services, and community dynamics. Sites that were selected based on socioeconomic or ecological metrics alone had lower likelihood of mangrove restoration success than sites that were selected based on integrated socioeconomic and ecological metrics. For example, selecting sites based on only socioeconomic metrics captured 16% of the maximum attainable value of functioning mangroves able to provide propagules to potential restoration sites, whereas selecting sites based on ecological and socioeconomic metrics captured 46% of functioning mangroves. Our approach was developed as part of a collaboration between nongovernmental organizations, local government, and academics under rapid delivery time lines given preexisting mangrove restoration implementation commitments. The systematic decision process we used integrated socioeconomic and ecological considerations even under short delivery deadlines, and our approach can be adapted to help mangrove restoration site-selection decisions elsewhere.