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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ED: Publish subject to minor revisions (Editor review) (22 Feb 2016) by Jochen Schöngart
AR by Daniel Magnabosco Marra on behalf of the Authors (23 Feb 2016)  Author's response    Manuscript
ED: Publish subject to technical corrections (26 Feb 2016) by Jochen Schöngart
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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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