Global validation of a process-based model on vegetation gross primary production using eddy covariance observations

Dan Liu; Wenwen Cai; Jiangzhou Xia; Wenjie Dong; Guangsheng Zhou; Yang Chen; Haicheng Zhang; Wenping Yuan

doi:10.1371/journal.pone.0110407

Global validation of a process-based model on vegetation gross primary production using eddy covariance observations

PLoS One. 2014 Nov 6;9(11):e110407. doi: 10.1371/journal.pone.0110407. eCollection 2014.

Authors

Dan Liu¹, Wenwen Cai¹, Jiangzhou Xia¹, Wenjie Dong¹, Guangsheng Zhou², Yang Chen¹, Haicheng Zhang¹, Wenping Yuan¹

Affiliations

¹ State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China.
² Chinese Academy of Sciences, Institute of Botany, State Key Laboratory of Vegetation and Environmental Change, Beijing, China; Chinese Academy of Meteorological Sciences, Beijing, China.

Abstract

Gross Primary Production (GPP) is the largest flux in the global carbon cycle. However, large uncertainties in current global estimations persist. In this study, we examined the performance of a process-based model (Integrated BIosphere Simulator, IBIS) at 62 eddy covariance sites around the world. Our results indicated that the IBIS model explained 60% of the observed variation in daily GPP at all validation sites. Comparison with a satellite-based vegetation model (Eddy Covariance-Light Use Efficiency, EC-LUE) revealed that the IBIS simulations yielded comparable GPP results as the EC-LUE model. Global mean GPP estimated by the IBIS model was 107.50±1.37 Pg C year(-1) (mean value ± standard deviation) across the vegetated area for the period 2000-2006, consistent with the results of the EC-LUE model (109.39±1.48 Pg C year(-1)). To evaluate the uncertainty introduced by the parameter Vcmax, which represents the maximum photosynthetic capacity, we inversed Vcmax using Markov Chain-Monte Carlo (MCMC) procedures. Using the inversed Vcmax values, the simulated global GPP increased by 16.5 Pg C year(-1), indicating that IBIS model is sensitive to Vcmax, and large uncertainty exists in model parameterization.

Publication types

Research Support, Non-U.S. Gov't
Validation Study

MeSH terms

Carbon Cycle*
Climate*
Ecosystem*
Models, Theoretical*

Grants and funding

This study was supported by the National Science Foundation for Excellent Young Scholars of China (41322005), the National High Technology Research and Development Program of China (863 Program) (2013AA122003), National Natural Science Foundation of China (41201078), Program for New Century Excellent Talents in University (NCET-322 12-0060) and the Fundamental Research Funds for the Central Universities. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.