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| Titel |
Year-to-year variability of ecosystem CO2 and H2O exchange of European forests inferred from eddy covariance flux data: patterns, factors and driving processes |
| VerfasserIn |
M. Reichstein, D. Papale, F. Angermüller, G. Lasslop, M. Mahecha, P. Ciais, G. Le Maire, S. Running |
| Konferenz |
EGU General Assembly 2009
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 11 (2009) |
| Datensatznummer |
250025264
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| Zusammenfassung |
| In this analysis we are trying to characterize the year-to-year variability of carbon
fluxes, and identify the driving processes (e.g. assimilation versus respiration) as
well as the climatic versus biological controls at European forest sites. Overall,
between-year differences in annual NEP can be largely be attributed to variability in
GPP and less in TER. Sometimes even positive correlations of NEP with TER are
found, which is counterintuitive and shows that high TER is indicative of high
productivity under most conditions. Moreover variability of year-to-year NEP seems to be
largely caused by summer-time variability, except in some Boreal sites. No simple
climate index could be identified that explains interannual variability, but it became
evident that changes in GPP are largely due to variation in radiation-use and less by
radiation absorption, i.e. ecophysiological control exceeds biophysical control. An
analysis of light-response curves throughout the seasons also reveal a strong control of
NEE variability by changes in ecosystem properties (e.g. assimilatory capacities
identifiend from light response curves) than climatic trends. It is discussed, whether these
changes are related themselves to climatic variability and rising CO2 or intrinsic
forest dynamics. Finally the site-level findings are up-scaled data-adaptive modeling
approaches. The dominance of GPP versus TER in controlling IAV is confirmed in
this spatial application, but exceptional regions are identified where accordings to
the data-derived model TER dominates variability of annual NEP. These regions
might include low-productivity ecosystems and ecosystems with large soil carbon
stocks.
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