Articles | Volume 13, issue 5
Biogeosciences, 13, 1553–1570, 2016
https://doi.org/10.5194/bg-13-1553-2016
Biogeosciences, 13, 1553–1570, 2016
https://doi.org/10.5194/bg-13-1553-2016
Research article
11 Mar 2016
Research article | 11 Mar 2016

Predicting biomass of hyperdiverse and structurally complex central Amazonian forests – a virtual approach using extensive field data

Daniel Magnabosco Marra et al.

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Short summary
Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests requires the inclusion of predictors that express inherent variations in species architecture. The model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases.
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