Prediction of Continental-Scale Net Ecosystem Carbon Exchange by Combining MODIS and AmeriFlux Data

There is growing interest in scaling up net ecosystem exchange (NEE) measured at eddy covariance flux towers to regional scales. Here we used remote sensing data from the MODIS instrument on board NASA's Terra satellite to extrapolate NEE measured at AmeriFlux sites to the continental scale. We combined MODIS data and NEE measurements from a number of AmeriFlux sites with a variety of vegetation types (e.g., forests, grasslands, shrublands, savannas, and croplands) to develop a predictive NEE model using a regression tree approach. The model was trained using 2000-2003 NEE measurements, and the performance of the model was evaluated using independent data over the period 2004-2006. We found that the model predicted NEE with reasonable accuracy at the continental scale. The R-squared values are 0.50 for all vegetation types combined and 0.72 for deciduous forests. We then applied the model to the conterminous U.S. and predicted NEE for each 500m by 500m cell over the period 2001-2006. Based on the wall-to-wall NEE estimates, we examined the spatial and temporal distributions of annual NEE and interannual variability of annual NEE across the conterminous U.S. over the study period (2001-2006). Our scaling-up approach implicitly considered the effects of climate variability, land use/land cover change, disturbances, extreme climate events, and management practices, and thus our annual NEE estimates represents the net carbon fluxes between the terrestrial biosphere and the atmosphere in the conterminous U.S.