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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
© Author(s) 2013. This work is distributed
under the Creative Commons Attribution 3.0 License.
Development and technical paper
04 Nov 2013
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This discussion paper has been under review for the journal Geoscientific Model Development (GMD). The revised manuscript was not accepted.
Are vegetation-specific model parameters required for estimating gross primary production?
W. Yuan1,2, S. Liu3, W. Cai1, W. Dong1, J. Chen4,5, A. Arain6, P. D. Blanken7, A. Cescatti8, G. Wohlfahrt9, T. Georgiadis10, L. Genesio11, D. Gianelle12, A. Grelle13, G. Kiely14, A. Knohl15, D. Liu1, M. Marek16, L. Merbold17, L. Montagnani18, O. Panferov15, M. Peltoniemi19, S. Rambal20, A. Raschi11, A. Varlagin21, and J. Xia1 1State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
2State Key Laboratory of Cryospheric Sciences, Cold and Arid Regions Environmental and Engineering Research Institute, The Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
3State Engineering Laboratory of Southern Forestry Applied Ecology and Technology, Central South University of Forestry and Technology, Changsha, Hunan 410004, China
4International Center for Ecology, Meteorology and Environment, School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
5Department of Environmental Sciences, University of Toledo, Toledo, OH 43606, USA
6School of Geography and Earth Sciences, McMaster University, Hamilton, Ontario, Canada
7Department of Geography, University of Colorado at Boulder, Boulder, CO 80309, USA
8European Commission, Joint Research Center, Institute for Environment and Sustainability, Ispra, Italy
9Institute of Ecology, University of Innsbruck, Sternwartestrasse 15, 6020 Innsbruck, Austria
10IBIMET-CNR, Institute of Biometeorology, National Research Council, Via Gobetti, 101, Bologna, 40129, Italy
11IBIMET-CNR, Institute of Biometeorology, National Research Council, Via G. Caproni, 8, Firenze, 50145, Italy
12Sustainable Agro-ecosystems and Bioresources Department, Research and Innovation Centre, Fondazione E. Mach, San Michele all'Adige, Italy
13Department of Ecology, Swedish University of Agricultural Sciences, 750 07, Uppsala, Sweden
14Civil & Environmental Engineering Dept and Environmental Research Institute, University College Cork, Cork, Ireland
15Bioclimatology Group, Büsgen Institute, Georg-August University of Göttingen, Göttingen, Germany
16Department of Forest Ecology, Mendel University Brno, Zemedělská 3, 603 00 Brno, Czech Republic
17ETH Zurich, Institute of Agricultural Sciences, 8092 Zurich, Switzerland
18Forest Services of Autonomous Province of Bolzano, Bolzano, Italy
19Finnish Forest Research Institute, 01301 Vantaa, Finland
20DREAM, CEFE, CNRS, UMR5175, 1919 route de Mende, 34293 Montpellier Cedex 5, France
21A. N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow 119071, Russia
Abstract. Models of gross primary production (GPP) are currently parameterized with vegetation-specific parameter sets and therefore require accurate information on the distribution of vegetation to drive them. Can this parameterization scheme be replaced with a vegetation-invariant set of parameter that can maintain or increase model applicability by reducing errors introduced from the uncertainty of land cover classification? Based on the measurements of ecosystem carbon fluxes from 150 globally distributed sites in a range of vegetation types, we examined the predictive capacity of seven light use efficiency (LUE) models. Two model experiments were conducted: (i) a constant set of parameters for various vegetation types and (ii) vegetation-specific parameters. The results showed no significant differences in model performances to simulate GPP while using both sets of parameters. These results indicate that a universal set of parameters, which is independent of vegetation cover type and characteristics can be adopted in prevalent LUE models. Availability of this well tested and universal set of parameters would help to improve the accuracy and applicability of LUE models in various biomes and geographic regions.

Citation: Yuan, W., Liu, S., Cai, W., Dong, W., Chen, J., Arain, A., Blanken, P. D., Cescatti, A., Wohlfahrt, G., Georgiadis, T., Genesio, L., Gianelle, D., Grelle, A., Kiely, G., Knohl, A., Liu, D., Marek, M., Merbold, L., Montagnani, L., Panferov, O., Peltoniemi, M., Rambal, S., Raschi, A., Varlagin, A., and Xia, J.: Are vegetation-specific model parameters required for estimating gross primary production?, Geosci. Model Dev. Discuss., 6, 5475-5488, doi:10.5194/gmdd-6-5475-2013, 2013.
W. Yuan et al.
W. Yuan et al.


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