Aboveground and belowground tree basic densities varied between and within the three mangrove species. If appropriately determined and applied, basic density may be useful in estimation of tree biomass. Predictive accuracy of the common (i.e. multi-species) models including aboveground/belowground basic density was better than for common models developed without either basic density. However, species-specific models developed without basic density performed better than common models including basic density.
Reducing Emissions from Deforestation and forest degradation and the role of sustainable forest management, conservation and enhancement of carbon stocks (REDD+) initiatives offer an opportunity for sustainable management of forests including mangroves. In carbon accounting for REDD+, it is required that carbon estimates prepared for monitoring reporting and verification schemes should ensure that all known sources of uncertainty are minimised as much as possible. However, uncertainties of applying indirect method of biomass determination are poorly understood. This study aimed to assess importance of tree basic density in modelling aboveground and belowground biomass and examine uncertainties in estimation of tree biomass using indirect methods. This study focused on three dominant mangrove species (Avicennia marina (Forssk.) Vierh, Sonneratia alba J. Smith and Rhizophora mucronata Lam.) in Tanzania. A total of 120 trees were destructively sampled for aboveground biomass, and 30 among them were sampled for belowground biomass. Tree merchantable volume and both aboveground and belowground basic densities were determined. Biomass models including basic density as a predictor variable were developed using the non-linear mixed-effects modelling approach. Results showed that both tree aboveground and belowground basic density varied significantly between sites between tree species, among individuals of the same species and between tree components. The use of tree- and component-specific aboveground basic density resulted in unbiased tree aboveground biomass estimates; however, uncertainties were high when using aboveground basic density values from the Global Wood Density (GWD) database. Predictive accuracy of the common models including aboveground/belowground basic density was better than for the common models developed previously without basic density. However, the species-specific models developed previously without basic density were superior to the common models including basic density developed in the present study. Tree aboveground and belowground basic densities were useful in modelling tree aboveground and belowground biomass, respectively. This is demonstrated by improved goodness of fit associated with inclusion of basic density. However, species-specific models developed without basic density performed better than common models including basic density. If appropriately determined and applied, basic density may be useful in estimation of tree biomass and hence contribute to improved accuracy of carbon stock estimates for REDD+ and sustainable management of mangroves in general.