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| Titel |
Predicting tree heights for biomass estimates in tropical forests – a test from French Guiana |
| VerfasserIn |
Q. Molto, B. Hérault, J.-J. Boreux, M. Daullet, A. Rousteau, V. Rossi |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 11, no. 12 ; Nr. 11, no. 12 (2014-06-16), S.3121-3130 |
| Datensatznummer |
250117464
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| Publikation (Nr.) |
 copernicus.org/bg-11-3121-2014.pdf |
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| Zusammenfassung |
The recent development of REDD+ mechanisms requires
reliable estimation of carbon stocks, especially in tropical forests that
are particularly threatened by global changes. Even though
tree height is a crucial variable for computing
aboveground forest biomass (AGB), it is
rarely measured in large-scale forest censuses because it requires extra effort.
Therefore, tree height has to be predicted with height models.
The height and diameter of all trees over 10 cm in diameter
were measured in 33 half-hectare plots and 9 one-hectare plots
throughout northern French Guiana, an area with substantial
climate and environmental gradients. We compared four different
model shapes and found that the Michaelis–Menten shape was most
appropriate for the tree biomass prediction. Model
parameter values were significantly different from one
forest plot to another, and this leads
to large errors in biomass estimates.
Variables from the forest stand structure explained a sufficient
part of plot-to-plot variations of the height model parameters
to improve the quality of the AGB predictions.
In the forest stands dominated by
small trees, the trees were found to have rapid height growth for
small diameters. In forest stands dominated by larger trees, the
trees were found to have the greatest heights for large diameters.
The aboveground biomass estimation uncertainty of the forest plots
was reduced by the use of the forest structure-based height
model. It demonstrated the feasibility and the importance of height
modeling in tropical forests for carbon mapping.
When the tree heights are not measured in an inventory,
they can be predicted with a height–diameter model and incorporating
forest structure descriptors may improve the predictions. |
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