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Title: Global parameterization and validation of a two-leaf light use efficiency model for predicting gross primary production across FLUXNET sites: TL-LUE Parameterization and Validation

Light use efficiency (LUE) models are widely used to simulate gross primary production (GPP). However, the treatment of the plant canopy as a big leaf by these models can introduce large uncertainties in simulated GPP. Recently, a two-leaf light use efficiency (TL-LUE) model was developed to simulate GPP separately for sunlit and shaded leaves and has been shown to outperform the big-leaf MOD17 model at 6 FLUX sites in China. In this study we investigated the performance of the TL-LUE model for a wider range of biomes. For this we optimized the parameters and tested the TL-LUE model using data from 98 FLUXNET sites which are distributed across the globe. The results showed that the TL-LUE model performed in general better than the MOD17 model in simulating 8-day GPP. Optimized maximum light use efficiency of shaded leaves (εmsh) was 2.63 to 4.59 times that of sunlit leaves (εmsu). Generally, the relationships of εmsh and εmsu with εmax were well described by linear equations, indicating the existence of general patterns across biomes. GPP simulated by the TL-LUE model was much less sensitive to biases in the photosynthetically active radiation (PAR) input than the MOD17 model. The results of this study suggestmore » that the proposed TL-LUE model has the potential for simulating regional and global GPP of terrestrial ecosystems and it is more robust with regard to usual biases in input data than existing approaches which neglect the bi-modal within-canopy distribution of PAR.« less
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  1. Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing China; Joint Center for Global Change Studies, Beijing China
  2. International Institute for Earth System Sciences, Nanjing University, Nanjing China; Joint Center for Global Change Studies, Beijing China
  3. International Institute for Earth System Sciences, Nanjing University, Nanjing China; Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application, Nanjing China
  4. Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing China
  5. State Key Laboratory of Earth Surface Processes and Resource Ecology, Future Earth Research Institute, Beijing Normal University, Beijing China
  6. Faculty of Land and Food Systems, University of British Columbia, Vancouver British Columbia Canada
  7. Department of Environmental Engineering, Technical University of Denmark (DTU), Kgs. Lyngby Denmark
  8. Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang China
  9. South China Botanical Garden, Chinese Academy of Sciences, Guangzhou China
  10. Centre for Forest Studies, Faculty of Forestry, Geography and Geomatics, Laval University, Quebec City Quebec Canada
  11. CIRAD-Persyst, UMR Ecologie Fonctionnelle and Biogéochimie des Sols et Agroécosystèmes, SupAgro-CIRAD-INRA-IRD, Montpellier France; CATIE (Tropical Agricultural Centre for Research and Higher Education), Turrialba Costa Rica
  12. Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining China
  13. Environmental Research Institute, Civil and Environmental Engineering Department, University College Cork, Cork Ireland
  14. Department of Biological Sciences, University of Alabama, Tuscaloosa Alabama USA
  15. Laboratory of Plants Ecological Physiology, Institute of Systems Biology and Ecology AS CR, Prague Czech Republic
  16. Forest Services, Autonomous Province of Bolzano, Bolzano Italy; Faculty of Sciences and Technology, Free University of Bolzano, Bolzano Italy
  17. Institute for Ecology, University of Innsbruck, Innsbruck Austria; European Academy of Bolzano, Bolzano Italy
  18. Grassland Sciences Group, Institute of Agricultural Sciences, ETH Zurich Switzerland
  19. Atmospheric and Climate Research Program, Environmental Science Division, Argonne National Laboratory, Argonne Illinois USA
  20. McMaster Centre for Climate Change and School of Geography and Earth Sciences, McMaster University, Hamilton Ontario Canada
  21. INRA Nancy, UMR EEF, Champenoux France
  22. School of Earth and Environment, The University of Western Australia, Crawley Australia
  23. Department of Geography, University of Colorado Boulder, Boulder Colorado USA
  24. UMR ECOSYS, INRA, AgroParisTech, Université Paris-Saclay, Thiverval-Grignon France
  25. Department of Crop and Soil Sciences, College of Agricultural and Environmental Sciences, University of Georgia, Athens Georgia USA
  26. Viea San Camillo Ed LellisViterbo, University of Tuscia, Viterbo Italy
  27. MTA-SZIE Plant Ecology Research Group, Szent Istvan University, Godollo Hungary
  28. Meteorology Department, Poznan University of Life Sciences, Poznan Poland; Department of Matter and Energy Fluxes, Global Change Research Center, Brno Czech Republic
  29. Department of Land, Air and Water Resources, University of California, Davis California USA; Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge USA
  30. A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow Russia
Publication Date:
OSTI Identifier:
DOE Contract Number:
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Geophysical Research. Biogeosciences; Journal Volume: 121; Journal Issue: 4
American Geophysical Union
Research Org:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org:
National Natural Science Foundation of China (NNSFC); Chinese Academy of Sciences (CAS); USDOE Office of Science - Office of Biological and Environmental Research; National Science Foundation (NSF)
Country of Publication:
United States
54 ENVIRONMENTAL SCIENCES; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; FLUXNET; MODIS; gross primary productivity; sunlit and shaded leaves; two-leaf light use efficiency model