Estimated mangrove carbon stocks and fluxes to inform MRV for REDD+ using a process-based model

Mangrove forests are important due to their strong capability for carbon storage, especially in soils. Understanding carbon dynamics in these forests is fundamental to estimate their roles in carbon storage and mitigating climate change. This study used a process-based model, MCAT-DNDC, to assess mangrove carbon sequestration and fluxes at a 30-m spatial resolution in three African countries, Gabon, Mozambique and Tanzania. The simulated above- and below-ground biomass at inventory plots in each country was approximate to actual observations with mean errors <5% for aboveground biomass and <8% for belowground biomass, indicating that the MCAT-DNDC model can be a useful tool for assessing mangrove carbon storage and fluxes. The results from assessing mangrove carbon storage and fluxes for the three countries showed that the mangroves in these countries are large carbon pools, they export large amounts of dissolved and particulate carbon components to riverine and oceanic ecosystems, and they bury a large amount of carbon in soils. However, soil-borne greenhouse gases CO2, CH4 and N2O fluxes from mangrove forest lands were low. There were large differences in all mangrove carbon components among the mangroves in the three countries, indicating that regional or global mangrove carbon stocks estimated using a process-based model may be better than the extrapolations using limited inventories.