Articles | Volume 13, issue 5
Biogeosciences, 13, 1553–1570, 2016
https://doi.org/10.5194/bg-13-1553-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Biogeosciences, 13, 1553–1570, 2016
https://doi.org/10.5194/bg-13-1553-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
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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Cited
16 citations as recorded by crossref.
- Relasphone—Mobile and Participative In Situ Forest Biomass Measurements Supporting Satellite Image Mapping M. Molinier et al. 10.3390/rs8100869
- Aboveground biomass and carbon of the highly diverse Atlantic Forest in Brazil: comparison of alternative individual tree modeling and prediction strategies M. Colmanetti et al. 10.1080/17583004.2018.1503040
- Weighing trees with lasers: advances, challenges and opportunities M. Disney et al. 10.1098/rsfs.2017.0048
- Windthrows control biomass patterns and functional composition of Amazon forests D. Magnabosco Marra et al. 10.1111/gcb.14457
- Climate change alters the ability of neotropical forests to provide timber and sequester carbon U. Hiltner et al. 10.1016/j.foreco.2021.119166
- Estimation of above ground biomass Shorea spp (Dipterocarpaceae) using allometric models S. Latifah & M. Zahrah 10.1088/1755-1315/959/1/012029
- Fragmentation increases wind disturbance impacts on forest structure and carbon stocks in a western Amazonian landscape N. Schwartz et al. 10.1002/eap.1576
- Integrating climate, soil and stand structure into allometric models: An approach of site-effects on tree allometry in Atlantic Forest V. Cysneiros et al. 10.1016/j.ecolind.2021.107794
- Tree Climbing Techniques and Volume Equations for Eschweilera (Matá-Matá), a Hyperdominant Genus in the Amazon Forest B. Gimenez et al. 10.3390/f8050154
- Allometric models to estimate the aboveground biomass of forest: A literature review S. Latifah et al. 10.1088/1757-899X/1122/1/012047
- Recovery of Forest Structure Following Large-Scale Windthrows in the Northwestern Amazon J. Urquiza Muñoz et al. 10.3390/f12060667
- Important role of forest disturbances in the global biomass turnover and carbon sinks T. Pugh et al. 10.1038/s41561-019-0427-2
- Variation of non‐structural carbohydrates across the fast–slow continuum in Amazon Forest canopy trees C. Signori‐Müller et al. 10.1111/1365-2435.13971
- Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries P. Ploton et al. 10.5194/bg-13-1571-2016
- Does biomass growth increase in the largest trees? Flaws, fallacies and alternative analyses D. Sheil et al. 10.1111/1365-2435.12775
- Allometric Models for Estimation of Forest Biomass in North East India A. Nath et al. 10.3390/f10020103
13 citations as recorded by crossref.
- Relasphone—Mobile and Participative In Situ Forest Biomass Measurements Supporting Satellite Image Mapping M. Molinier et al. 10.3390/rs8100869
- Aboveground biomass and carbon of the highly diverse Atlantic Forest in Brazil: comparison of alternative individual tree modeling and prediction strategies M. Colmanetti et al. 10.1080/17583004.2018.1503040
- Weighing trees with lasers: advances, challenges and opportunities M. Disney et al. 10.1098/rsfs.2017.0048
- Windthrows control biomass patterns and functional composition of Amazon forests D. Magnabosco Marra et al. 10.1111/gcb.14457
- Climate change alters the ability of neotropical forests to provide timber and sequester carbon U. Hiltner et al. 10.1016/j.foreco.2021.119166
- Estimation of above ground biomass Shorea spp (Dipterocarpaceae) using allometric models S. Latifah & M. Zahrah 10.1088/1755-1315/959/1/012029
- Fragmentation increases wind disturbance impacts on forest structure and carbon stocks in a western Amazonian landscape N. Schwartz et al. 10.1002/eap.1576
- Integrating climate, soil and stand structure into allometric models: An approach of site-effects on tree allometry in Atlantic Forest V. Cysneiros et al. 10.1016/j.ecolind.2021.107794
- Tree Climbing Techniques and Volume Equations for Eschweilera (Matá-Matá), a Hyperdominant Genus in the Amazon Forest B. Gimenez et al. 10.3390/f8050154
- Allometric models to estimate the aboveground biomass of forest: A literature review S. Latifah et al. 10.1088/1757-899X/1122/1/012047
- Recovery of Forest Structure Following Large-Scale Windthrows in the Northwestern Amazon J. Urquiza Muñoz et al. 10.3390/f12060667
- Important role of forest disturbances in the global biomass turnover and carbon sinks T. Pugh et al. 10.1038/s41561-019-0427-2
- Variation of non‐structural carbohydrates across the fast–slow continuum in Amazon Forest canopy trees C. Signori‐Müller et al. 10.1111/1365-2435.13971
3 citations as recorded by crossref.
- Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries P. Ploton et al. 10.5194/bg-13-1571-2016
- Does biomass growth increase in the largest trees? Flaws, fallacies and alternative analyses D. Sheil et al. 10.1111/1365-2435.12775
- Allometric Models for Estimation of Forest Biomass in North East India A. Nath et al. 10.3390/f10020103
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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.
Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex...
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