Abstract
Despite the importance of net primary productivity (NPP) and net biome productivity (NBP), estimates of NPP and NBP for China are highly uncertain. To investigate the main sources of uncertainty, we synthesized model estimates of NPP and NBP for China from published literature and the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP). The literature-based results showed that total NPP and NBP in China were 3.35 ± 1.25 and 0.14 ± 0.094 Pg C yr−1, respectively. Classification and regression tree analysis based on literature data showed that model type was the primary source of the uncertainty, explaining 36% and 64% of the variance in NPP and NBP, respectively. Spatiotemporal scales, land cover conditions, inclusion of the N cycle, and effects of N addition also contributed to the overall uncertainty. Results based on the MsTMIP data suggested that model structures were overwhelmingly important (>90%) for the overall uncertainty compared to simulations with different combinations of time-varying global change factors. The interannual pattern of NPP was similar among diverse studies and increased by 0.012 Pg C yr−1 during 1981–2000. In addition, high uncertainty in China's NPP occurred in areas with high productivity, whereas NBP showed the opposite pattern. Our results suggest that to significantly reduce uncertainty in estimated NPP and NBP, model structures should be substantially tested on the basis of empirical results. To this end, coordinated distributed experiments with multiple global change factors might be a practical approach that can validate specific structures of different models.
| Original language | English |
|---|---|
| Pages (from-to) | 1372-1393 |
| Number of pages | 22 |
| Journal | Journal of Geophysical Research: Biogeosciences |
| Volume | 121 |
| Issue number | 5 |
| DOIs | |
| State | Published - May 1 2016 |
Funding
The data used in this analysis are shown in the supporting information. We thank the three anonymous reviewers for their constructive comments and suggestions. This research was financially supported by the National Natural Science Foundation of China (Grant 31370489), the Program for Professor of Special Appointment (Eastern Scholar) at the Shanghai Institutions of Higher Learning, and the national “Thousand Young Talents” Program in China. Funding for the Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP; http://nacp.ornl.gov/MsTMIP.shtm) activity was provided through NASA ROSES Grant NNX10AG01A. Data management support for preparing, documenting, and distributing model driver and output data was performed by the Modeling and Synthesis Thematic Data Center at Oak Ridge National Laboratory (ORNL; http://nacp.ornl.gov), with funding through NASA ROSES Grant NNH10AN681. Finalized MsTMIP data products are archived at the ORNL DAAC (http://daac.ornl.gov). This is MsTMIP contribution #5. Acknowledgments for specific MsTMIP participating models: Biome-BGC: Biome-BGC code was provided by the Numerical Terradynamic Simulation Group at the University of Montana. The computational facilities provided by NASA Earth Exchange at NASA Ames Research Center. CLM: This research is supported in part by the U.S. Department of Energy (DOE), Office of Science, Biological, and Environmental Research. Oak Ridge National Laboratory is managed by UTBATTELLE for DOE under contract DE-AC05-00OR22725. CLM4VIC: CLM4VIC simulations were supported in part by the U.S. Department of Energy (DOE), Office of Science, Biological, and Environmental Research (BER) through the Earth System Modeling program and performed using the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the U.S. DOE-BER and located at Pacific Northwest National Laboratory (PNNL). Participation of M. Huang in the MsTMIP synthesis is supported by the U.S. DOE-BER through the Subsurface Biogeochemical Research Program (SBR) as part of the SBR Scientific Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL). PNNL is operated for the U.S. DOE by BATTELLE Memorial Institute under contract DE-AC05-76RLO1830. DLEM: The Dynamic Land Ecosystem Model (DLEM) developed in the International Center for Climate and Global Change Research at Auburn University has been supported by NASA Interdisciplinary Science Program, NASA Land Cover/Land Use Change Program (LCLUC), NASA Terrestrial Ecology Program, NASA Atmospheric Composition Modeling and Analysis Program; NSF Dynamics of Coupled Natural-Human System Program, Decadal and Regional Climate Prediction using Earth System Models; DOE National Institute for Climate Change Research; USDA AFRI Program; and EPA STAR Program. ISAM: Integrated Science Assessment Model (ISAM) simulations were supported by the U.S. National Science Foundation (NSF-AGS-12-43071 and NSF-EFRI-083598), the USDA National Institute of Food and Agriculture (2011-68002–30220), the U.S. Department of Energy (DOE) Office of Science (DOE-DE-SC0006706), and the NASA Land Cover and Land Use Change Program (NNX14AD94G). ISAM simulations were carried out at the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-05CH11231, and at the Blue Waters sustained-petascale computing, University of Illinois at Urbana-Champaign, which is supported by the National Science Foundation (awards OCI-0725070 and ACI-1238993) and the state of Illinois. LPJ-wsl: This work was conducted at LSCE, France, using a modified version of the LPJ version 3.1 model, originally made available by the Potsdam Institute for Climate Impact Research. ORCHIDEE-LSCE: ORCHIDEE is a global land surface model developed at the IPSL institute in France. The simulations were performed with the support of the GhG Europe FP7 grant with computing facilities provided by LSCE (Laboratoire des Sciences du Climat et de l'Environnement) or TGCC (Très Grand Centre de Calcul). TRIPLEX-GHG: TRIPLEX-GHG developed at University of Quebec at Montreal (Canada) and Northwest A&F University (China) has been supported by the National Basic Research Program of China (2013CB956602) and the National Science and Engineering Research Council of Canada (NSERC) Discover Grant. VISIT: VISIT was developed at the National Institute for Environmental Studies, Japan. This work was mostly conducted during a visiting stay at Oak Ridge National Laboratory.
Keywords
- China
- interannual variability
- model structure
- net biome productivity
- net primary productivity
- uncertainty