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      A solution to the high bias in estimates of carbon held in tropical forest above-ground biomass


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          Non-destructive methods were used to estimate the volume, aerial biomass and amount of carbon stored by individuals of different plant species, communities, vegetation types and coverage based on using elemental information capture, three-dimensional architecture and recurrent neural networks. This methodology accurately captures the diversity of plant forms present in plots or releves. The calculation of stored carbon in a vegetation type is a result from half the estimates of the biomass of sampled individuals in significant plots by the use of allometric formulas. The most complete formulas incorporate the diameter, height and specific gravity of trees but do not consider the variation in carbon stored in different organs or different species as well as exclude information on the wide variety of architectures present in different plant communities. To develop an allometric model, many individuals of different species must be sacrificed for the identification processes, validation and error minimization. It is common to find cutting-edge studies in which logging is encouraged to improve estimates of carbon. In this study, we replace this destructive methodology and provide an important contribution to quantifying global aboveground carbon. We have demonstrated with our methodology that carbon content in forest above-ground biomass in the pantropic could rise to 723.97 Pg C. This would involve the reassessment of many climatic and ecological models in order to move towards a better understanding of the adverse effects of climate change.

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          Quantitative & Systems biology


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