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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
Sprache Englisch
ISSN 1726-4170
Digitales Dokument URL
Erschienen In: Biogeosciences ; 7, no. 1 ; Nr. 7, no. 1 (2010-01-13), S.163-176
Datensatznummer 250004371
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/bg-7-163-2010.pdf
 
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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