Evaluating, predicting and mapping belowground carbon stores in Kenyan mangroves.

Despite covering only approximately 138,000 km2, mangroves are globally important carbon sinks with carbon density values 3 to 4 times that of terrestrial forests. A key challenge in evaluating the carbon benefits from mangrove forest conservation is the lack of rigorous spatially resolved estimates of mangrove sediment carbon stocks; most mangrove carbon is stored belowground. Previous work has focused on detailed estimations of carbon stores over relatively small areas, which has obvious limitations in terms of generality and scope of application. Most studies have focused only on quantifying the top 1m of belowground carbon (BGC). Carbon stored at depths beyond 1m, and the effects of mangrove species, location and environmental context on these stores, is poorly studied. This study investigated these variables at two sites (Gazi and Vanga in the south of Kenya) and used the data to produce a country-specific BGC predictive model for Kenya and map BGC store estimates throughout Kenya at spatial scales relevant for climate change research, forest management and REDD+ (Reduced Emissions from Deforestation and Degradation). The results revealed that mangrove species was the most reliable predictor of BGC; Rhizophora muronata had the highest mean BGC with 1485.5t C ha-1. Applying the species-based predictive model to a base map of species distribution in Kenya for the year 2010 with a 2.5m2 resolution, produced an estimate of 69.41 Mt C (± 9.15 95% C.I.) for BGC in Kenyan mangroves. When applied to a 1992 mangrove distribution map, the BGC estimate was 75.65 Mt C (± 12.21 95% C.I.); an 8.3% loss in BGC stores between 1992 and 2010 in Kenya. The country level mangrove map provides a valuable tool for assessing carbon stocks and visualising the distribution of BGC. Estimates at the 2.5m2 resolution provide sufficient detail for highlighting and prioritising areas for mangrove conservation and restoration.