FCE LTER Journal Articles


Yanlian Zhou, Nanjing University, China
Xiaocui Wu, Nanjing University, China
Weimin Ju, Nanjing University, China; iangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application
Jing M. Chen, Nanjing University, China
Shaoqiang Wang, Chinese Academy of Sciences
Huimin Wang, Chinese Academy of Sciences
Wenping Yuan, Beijing Normal University
T. Andrew Black, University of British Columbia
Rachhpal Jassal, University of British Columbia
Andreas Ibrom, Technical University of Denmark
Shijie Han, Chinese Academy of Sciences
Junhua Yan, Chinese Academy of Sciences
Hank Margolis, Laval University
Olivier Roupsard, CIRAD-Persyst, UMR Ecologie Fonctionnelle and Biogéochimie des Sols et Agroécosystèmes, SupAgro-CIRAD-INRAIRD; CATIE (Tropical Agricultural Centre for Research and Higher Education)
Yingnian Li, Chinese Academy of Sciences
Fenghua Zhao, Chinese Academy of Sciences
Gerard Kiely, University College Cork
Gregory Starr, University of Alabama - Tuscaloosa
Marian Pavelka, Institute of Systems Biology and Ecology AS CR
Leonardo Montagnani, Forest Services, Autonomous Province of Bolzano; University of Bolanzo
Georg Wohlfahrt, University of Innsbruck; European Academy of Bolanzo
Petra D'Odorico, Institute of Agricultural Sciences
David Cook, Argonne National Laboratory
M. Altaf Arain, McMaster University
Damien Bonal, INRA Nancy, UMR EEF
Jason Beringer, The University of Western Australia
Peter D. Blanken, University of Colorado Boulder
Benjamin Loubet, UMR ECOSYS, INRA, AgroParisTech, Université Paris-Saclay
Monique Y. Leclerc, University of Georgia
Giorgio Matteucci, University of Tuscia
Zoltan Nagy, Szent Istvan University
Janusz Olejnik, Poznan University of Life Sciences; Global Change Research Center, Brno, Czech Republic
Kyaw Tha Paw U, University of California; Massachusetts Institute of Technology
Andrej Varlagin, Russian Academy of Sciences


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 six 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 suggest 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 bimodal within-canopy distribution of PAR.


© 2016 Zhang et al. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

DOI: 10.1002/ecs2.1366

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DEB-1237517, #DBI-0620409, and #DEB-9910514. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.