Tree Physiology Advance Access originally published online on February 19, 2009
Tree Physiology 2009 29(5):621-639; doi:10.1093/treephys/tpp010
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Contributions of climate, leaf area index and leaf physiology to variation in gross primary production of six coniferous forests across Europe: a model-based analysis
1 Department of Forest Ecology, University of Helsinki, P.O. Box 27, FI-00014 Helsinki, Finland
2 Corresponding author (remkoduursma{at}gmail.com)
3 Finnish Meteorological Institute, Climate and Global Change Research, P.O. Box 503, FI-00101 Helsinki, Finland
4 INRA, UR1263 EPHYSE, 71 Av Edouard Bourlaux, F-33883 Villenave d’Ornon, France
5 Department of Meteorology, Institute of Hydrology and Meteorology, Technical University Dresden, Pienner Strasse 23, D-01737 Tharandt, Germany
6 Department of Physical Geography and Ecosystems Analysis, Lund University, SE-223 62 Lund, Sweden
7 Research Group of Plant and Vegetation Ecology, Department of Biology, University of Antwerp, Universiteitsplein 1, B-2610 Antwerp, Belgium
8 Laboratory of Plant Ecology, Department of Applied Ecology and Environmental Biology, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium
9 Division of Atmospheric Sciences, Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland
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Abstract |
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Gross primary production (GPP) is the primary source of all carbon fluxes in the ecosystem. Understanding variation in this flux is vital to understanding variation in the carbon sink of forest ecosystems, and this would serve as input to forest production models. Using GPP derived from eddy-covariance (EC) measurements, it is now possible to determine the most important factor to scale GPP across sites. We use long-term EC measurements for six coniferous forest stands in Europe, for a total of 25 site-years, located on a gradient between southern France and northern Finland. Eddy-derived GPP varied threefold across the six sites, peak ecosystem leaf area index (LAI) (all-sided) varied from 4 to 22 m2 m–2 and mean annual temperature varied from –1 to 13 °C. A process-based model operating at a half-hourly time-step was parameterized with available information for each site, and explained 71–96% in variation between daily totals of GPP within site-years and 62% of annual total GPP across site-years. Using the parameterized model, we performed two simulation experiments: weather datasets were interchanged between sites, so that the model was used to predict GPP at some site using data from either a different year or a different site. The resulting bias in GPP prediction was related to several aggregated weather variables and was found to be closely related to the change in the effective temperature sum or mean annual temperature. High R2s resulted even when using weather datasets from unrelated sites, providing a cautionary note on the interpretation of R2 in model comparisons. A second experiment interchanged stand-structure information between sites, and the resulting bias was strongly related to the difference in LAI, or the difference in integrated absorbed light. Across the six sites, variation in mean annual temperature had more effect on simulated GPP than the variation in LAI, but both were important determinants of GPP. A sensitivity analysis of leaf physiology parameters showed that the quantum yield was the most influential parameter on annual GPP, followed by a parameter controlling the seasonality of photosynthesis and photosynthetic capacity. Overall, the results are promising for the development of a parsimonious model of GPP.
Keywords: forest carbon uptake, forest productivity, process-based model
Received November 18, 2008; Accepted January 27, 2009
* Present address: Centre for Plant and Food Science, University of Western Sydney, Bourke Street, Richmond, NSW 2753 Australia