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Due to the public good nature of many of mangrove's ecosystem services, markets for them do not exist and there is limited potential to manage them with conventional markets. Moreover, because of the difficulties in estimating the value of these non-marketed services, mangroves are often undervalued in benefit cost analysis of conservation versus commercial land uses causing their degradation and loss. With the goal of supporting the current efforts of the government of Costa Rica to develop a new PES scheme that include these ecosystems, as well as other policy initiatives on wetlands conservation and restoration, we applied a hybrid approach to estimate the value of ecosystem services from mangrove forests in the Gulf of Nicoya. Our method consists of traditional benefit transfer and expert modified benefit transfer for 11 ecosystem services, and the application of more specific methods to estimate three of those ecosystem services (i.e. climate regulation, fisheries and coastal protection). Using traditional benefit transfer, we estimated the total economic value of ecosystem services of mangroves in the Gulf of Nicoya in $812 million per year (median=$88 million/year), and the total mean value of the ecosystem services provided by all the mangroves in Costa Rica as $1.5 billion per year (median=$160 million/year). By applying the expert modified benefit transfer we estimated that the mean total value of the mangrove forests of the Gulf of Nicoya is $470 million per year, and a median value of $75 million per year.

Due to the public good nature of many of mangrove's ecosystem services, markets for them do not exist and there is limited potential to manage them with conventional markets. Moreover, because of the difficulties in estimating the value of these non-marketed services, mangroves are often undervalued in benefit cost analysis of conservation versus commercial land uses causing their degradation and loss. With the goal of supporting the current efforts of the government of Costa Rica to develop a new PES scheme that include these ecosystems, as well as other policy initiatives on wetlands conservation and restoration, we applied a hybrid approach to estimate the value of ecosystem services from mangrove forests in the Gulf of Nicoya. Our method consists of traditional benefit transfer and expert modified benefit transfer for 11 ecosystem services, and the application of more specific methods to estimate three of those ecosystem services (i.e. climate regulation, fisheries and coastal protection). Using traditional benefit transfer, we estimated the total economic value of ecosystem services of mangroves in the Gulf of Nicoya in $812 million per year (median=$88 million/year), and the total mean value of the ecosystem services provided by all the mangroves in Costa Rica as $1.5 billion per year (median=$160 million/year). By applying the expert modified benefit transfer we estimated that the mean total value of the mangrove forests of the Gulf of Nicoya is $470 million per year, and a median value of $75 million per year.

With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30 m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250 m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kg m−3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha−1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies. ; Full Text

With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kgm*3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha*1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies.

With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kgm*3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha*1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies.