RESUMO
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.
Integración de datos socioeconómicos y ecológicos en las prácticas de restauración Resumen Se espera que la inversión en la restauración de los manglares incremente debido a la Década de Restauración de las Naciones Unidad y las iniciativas internacionales de financiamiento, como The Mangrove Breakthrough. Sin embargo, los esfuerzos de restauración de manglares fallan con frecuencia, generalmente por los procesos de selección de sitios adhoc que no consideran la ecología del manglar y el contexto socioeconómico. Usamos el análisis de decisiones para desarrollar una estrategia que considera los datos socioeconómicos y ecológicos para identificar los sitios con mayor probabilidad de éxito de restauración. Aplicamos nuestra estrategia en la Reserva de la Biósfera Marismas Nacionales Nayarit, México, un área que recibió financiamiento reciente para la restauración del manglar. Identificamos 468 sitios potencialmente restaurables, evaluamos su potencial de restauración con base en medidas ecológicas y socioeconómicas y clasificamos los sitios para la implementación con la optimización espacial. Las medidas que usamos incluían las condiciones favorables para que los propágulos se establezcan y sobrevivan con el incremento en el nivel del mar, el suministro de servicios ambientales y las dinámicas de la comunidad. Los sitios seleccionados sólo con base en las medidas ecológicas o socioeconómicas tuvieron una menor probabilidad de éxito de restauración que los sitios que se seleccionaron con base en medidas socioeconómicas y ecológicas integradas. Por ejemplo, la selección de sitios con base sólo en las medidas socioeconómicas capturó el 16% del máximo valor alcanzable de manglares funcionales capaces de proporcionar propágulos a los sitios potenciales de restauración, mientras que la selección basada en medidas ecológicas y socioeconómicas capturó el 46% de los manglares funcionales. Desarrollamos nuestra estrategia como parte de una colaboración entre organizaciones no gubernamentales, el gobierno local y académicos sujetos a una fecha pronta de entrega debido a los compromisos preexistentes para la restauración de manglares. El proceso de decisión sistemática que usamos integró las consideraciones ecológicas y socioeconómicas incluso con plazos cortos de entrega. Nuestra estrategia puede adaptarse para apoyar en la selección de sitios de restauración de manglares en otros sitios.
Assuntos
Conservação dos Recursos Naturais , Fatores Socioeconômicos , Conservação dos Recursos Naturais/métodos , Conservação dos Recursos Naturais/economia , México , Recuperação e Remediação Ambiental/economia , Ecossistema , Técnicas de Apoio para a DecisãoRESUMO
Mangroves have among the highest carbon densities of any tropical forest. These 'blue carbon' ecosystems can store large amounts of carbon for long periods, and their protection reduces greenhouse gas emissions and supports climate change mitigation. Incorporating mangroves into Nationally Determined Contributions to the Paris Agreement and their valuation on carbon markets requires predicting how the management of different land-uses can prevent future greenhouse gas emissions and increase CO2 sequestration. We integrated comprehensive global datasets for carbon stocks, mangrove distribution, deforestation rates, and land-use change drivers into a predictive model of mangrove carbon emissions. We project emissions and foregone soil carbon sequestration potential under 'business as usual' rates of mangrove loss. Emissions from mangrove loss could reach 2391 Tg CO2 eq by the end of the century, or 3392 Tg CO2 eq when considering foregone soil carbon sequestration. The highest emissions were predicted in southeast and south Asia (West Coral Triangle, Sunda Shelf, and the Bay of Bengal) due to conversion to aquaculture or agriculture, followed by the Caribbean (Tropical Northwest Atlantic) due to clearing and erosion, and the Andaman coast (West Myanmar) and north Brazil due to erosion. Together, these six regions accounted for 90% of the total potential CO2 eq future emissions. Mangrove loss has been slowing, and global emissions could be more than halved if reduced loss rates remain in the future. Notably, the location of global emission hotspots was consistent with every dataset used to calculate deforestation rates or with alternative assumptions about carbon storage and emissions. Our results indicate the regions in need of policy actions to address emissions arising from mangrove loss and the drivers that could be managed to prevent them.