Modelling carbon fluxes of different forests by coupling a remote-sensing model with an ecosystem process model

Abstract

A new model (GLOPEM-CEVSA) to determine terrestrial carbon budgets was developed by coupling remote sensing with ecosystem process simulation, and was validated with reference to the carbon fluxes of three forests. MODIS FPAR (MOD15A2 product) was applied together with meteorological data on flux towers. The seasonal variances of modelled gross primary production and ecosystem respiration were significantly correlated with observed values (correlation coefficient, r > 0.9). The seasonal dynamics of the modelled net ecosystem production over the plant-growth season showed significant agreement with observed values with a r range of 0.64 to 0.87. This work demonstrates the potential of GLOPEM-CEVSA to quantify the spatial patterns and temporal dynamics of terrestrial ecosystem carbon sources and sinks with consideration of the spatial heterogeneity of ecosystems based on remote sensing.

Acknowledgements

We gratefully acknowledge the Chinese Terrestrial Ecosystem Flux Research Network (ChinaFLUX), Fluxnet, MODIS Land Products Subsets, and the BigFoot project for providing carbon flux data at Qianyanzhou Forest, site information and MODIS data of the two US sites, and LAI data of Harvard Forest. We are grateful to Prof. Steven Wofsy of Harvard University and Prof. David Hollinger of the USDA Forest Service North-east Experimental Station for kindly providing the tower data from Harvard Forest and Howland Forest, and Dr. Katherine Owen of the Department of Plant Ecology, University of Bayreuth, Germany, for processing the flux data from Howland. We are grateful to Dr. Warwick Harris of Landcare Research, New Zealand, for his careful review and constructive suggestions to improve the manuscript. We thank Prof. Jingming Chen, University of Toronto, Dr. Harbin Li, USDA Forest Service Southern Research Station, Dr. Xiangming Xiao, University of Oklahoma, and Prof. Jiangwen Fan, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences for their comments and suggestions during the preparation of this manuscript. This work was supported by grants from the National Key Basic Research and Development Program (2009CB421105) and the National Natural Science Foundation of China (Nos. 30500064, 40501048), the ‘Hundred Talent’ Program of the Chinese Academy of Sciences, and the Chinese Academy of Sciences International Partnership Project ‘Human Activities and Ecosystem Changes’ (CXTD-Z2005-1).