IGN 17-3
The balance of greenhouse gases in the terrestrial biosphere: can we predict large-scale and long-term patterns from short-term plot level observations?

Thursday, August 8, 2013
101E, Minneapolis Convention Center
Hanqin Tian, International Center for Climate and Global Change Research and School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL
Chaoqun Lu, International Center for Climate and Global Change Research and School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL
Wei Ren, International Center for Climate and Global Change Research and School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL
Bo Tao, International Center for Climate and Global Change Research and School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL
Jia Yang, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL
Kamaljit Banger, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL
Shufen Pan, International Center for Climate and Global Change Research and School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL
Bowen Zhang, International Center for Climate and Global Change Research and School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL
Qichun Yang, School of forestry and wildlife sciences, Auburn University, Auburn, AL
Guangsheng Chen, Environmental Science Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN
Xiaofeng Xu, School of Forestry and Wildlife Sciences, Auburn University, AL
We are faced with a plethora of large-scale environmental problems, most of which are not amenable to direct experimentation.  Spatially-explicit, process-based ecosystem modeling approach is now playing a crucial role in synthesizing a huge quantity of data, conducting cross-scale extrapolation, analyzing multiple-factor interactions, and predicting large-scale ecological patterns and processes in a changing global environment. In this study, we have integrated a spatially-explicit, coupled biogeochemical model with multiple sources of data to explore the magnitude, spatial and temporal patterns of major greenhouse gas fluxes (CO2, CH4 and N2O) in the terrestrial biosphere and uncertainties associated with spatial and temporal scaling.