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| Titel |
Mortality as a key driver of the spatial distribution of aboveground biomass in Amazonian forest: results from a dynamic vegetation model |
| VerfasserIn |
N. Delbart, P. Ciais, J. Chave, N. Viovy, Y. Malhi, T. Toan |
| 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 ; 7, no. 10 ; Nr. 7, no. 10 (2010-10-06), S.3027-3039 |
| Datensatznummer |
250005006
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| Publikation (Nr.) |
 copernicus.org/bg-7-3027-2010.pdf |
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| Zusammenfassung |
Dynamic Vegetation Models (DVMs) simulate energy, water and carbon fluxes
between the ecosystem and the atmosphere, between the vegetation and the
soil, and between plant organs. They also estimate the potential biomass of
a forest in equilibrium having grown under a given climate and atmospheric
CO2 level. In this study, we evaluate the Above Ground Woody Biomass
(AGWB) and the above ground woody Net Primary Productivity (NPPAGW)
simulated by the DVM ORCHIDEE across Amazonian forests, by comparing the
simulation results to a large set of ground measurements (220 sites for
biomass, 104 sites for NPPAGW). We found that the NPPAGW is on
average overestimated by 63%. We also found that the fraction of biomass
that is lost through mortality is 85% too high. These model biases nearly
compensate each other to give an average simulated AGWB close to the ground
measurement average. Nevertheless, the simulated AGWB spatial distribution
differs significantly from the observations. Then, we analyse the
discrepancies in biomass with regards to discrepancies in NPPAGW and
those in the rate of mortality. When we correct for the error in
NPPAGW, the errors on the spatial variations in AGWB are exacerbated,
showing clearly that a large part of the misrepresentation of biomass comes
from a wrong modelling of mortality processes.
Previous studies showed that Amazonian forests with high productivity have a
higher mortality rate than forests with lower productivity. We introduce
this relationship, which results in strongly improved modelling of biomass
and of its spatial variations. We discuss the possibility of modifying the
mortality modelling in ORCHIDEE, and the opportunity to improve forest
productivity modelling through the integration of biomass measurements, in
particular from remote sensing. |
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