A solution for reducing high bias in estimates of stored carbon in tropical forests (aboveground biomass)

Abstract: A nondestructive method for estimating the amount of carbon stored by individuals, communities, vegetation types, and coverages, as well as their volume and aboveground biomass, is presented. This methodology is based on information on carbon stocks obtained through three-dimensional analysis of tree architecture and artificial neural networks. This technique accurately incorporates the diversity of plant forms measured in plots, transects, and relev\'es. Stored carbon in any vegetation type is usually calculated as half the biomass of sampled individuals, estimated with allometric formulas. The most complete of these formulas incorporate diameter, height, and specific gravity of wood but do not consider the variation in carbon stored in different organs or different species, nor do they include information on the wide array of architectures present in different plant communities. To develop these allometric models, many individuals of different species must be sacrificed to identify and validate samples and to minimize error. It is common to find cutting-edge studies that encourage logging to improve estimates of carbon. In our approach we replace this destructive methodology with a new technique for quantifying global aboveground carbon. We demonstrate that carbon content in forest aboveground biomass in the pantropics could rise to 723.97 Pg C. This study shows that a reevaluation of climatic and ecological models is needed to move toward a better understanding of the adverse effects of climate change, deforestation, and degradation of tropical vegetation.