Global Validation of a Process-Based Model on Vegetation Gross Primary Production Using Eddy Covariance Observations

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

doi:10.1371/journal.pone.0110407

Title: Global Validation of a Process-Based Model on Vegetation Gross Primary Production Using Eddy Covariance Observations

Journal Article · Thu Nov 06 00:00:00 EST 2014 · PLoS ONE

DOI:https://doi.org/10.1371/journal.pone.0110407· OSTI ID:1627735

Liu, Dan ^[1]; Cai, Wenwen ^[1]; Xia, Jiangzhou ^[1]; Dong, Wenjie ^[1]; Zhou, Guangsheng ^[2]; Chen, Yang ^[1]; Zhang, Haicheng ^[1]; Yuan, Wenping ^[1]

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

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.

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Research Organization:: Oregon State Univ., Corvallis, OR (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER); CarboEuropeIP; FAO-GTOS-TCO; iLEAPS; Max Planck Institute for Biogeochemistry; National Science Foundation (NSF); University of Tuscia; Université Laval; Environment Canada

Grant/Contract Number:: FG02-04ER63917; FG02-04ER63911

OSTI ID:: 1627735

Journal Information:: PLoS ONE, Vol. 9, Issue 11; ISSN 1932-6203

Publisher:: Public Library of ScienceCopyright Statement

Country of Publication:: United States

Language:: English

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