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| Titel |
Autumn temperature and carbon balance of a boreal Scots pine forest in Southern Finland |
| VerfasserIn |
T. Vesala, S. Launiainen, P. Kolari, J. Pumpanen, S. Sevanto, P. Hari, E. Nikinmaa, P. Kaski, H. Mannila, E. Ukkonen, S. L. Piao, P. Ciais |
| 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. 1 ; Nr. 7, no. 1 (2010-01-13), S.163-176 |
| Datensatznummer |
250004371
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| Publikation (Nr.) |
 copernicus.org/bg-7-163-2010.pdf |
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| Zusammenfassung |
| We analyzed the dynamics of carbon balance components: gross primary
production (GPP) and total ecosystem respiration (TER), of a boreal Scots
pine forest in Southern Finland. The main focus is on investigations of
environmental drivers of GPP and TER and how they affect the inter-annual
variation in the carbon balance in autumn (September–December). We used standard
climate data and CO2 exchange measurements collected by the eddy
covariance (EC) technique over 11 years. EC data revealed that increasing
autumn temperature significantly enhances TER: the temperature sensitivity
was 9.5 gC m−2 °C−1 for the period September–October (early
autumn when high radiation levels still occur) and 3.8 gC m−2 °C−1
for November–December (late autumn with suppressed radiation
level). The cumulative GPP was practically independent of the temperature in
early autumn. In late autumn, air temperature could explain part of the
variation in GPP but the temperature sensitivity was very weak, less than 1 gC m−2 °C−1.
Two models, a stand photosynthesis model (COCA)
and a global vegetation model (ORCHIDEE), were used for estimating stand GPP
and its sensitivity to the temperature. The ORCHIDEE model was tested
against the observations of GPP derived from EC data. The stand
photosynthesis model COCA predicted that under a predescribed 3–6 °C
temperature increase, the temperature sensitivity of 4–5 gC m−2 °C−1
in GPP may appear in early autumn. The analysis by the ORCHIDEE
model revealed the model sensitivity to the temporal treatment of
meteorological forcing. The model predictions were similar to observed ones
when the site level 1/2-hourly time step was applied, but
the results calculated by using daily meteorological forcing, interpolated
to 1/2-hourly time step, were biased.
This is due to the nonlinear relationship between the processes and the
environmental factors. |
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