One common goal in ecosystem ecology is the acquisition and processing of real-time biophysical data. Two examples of this are (a) ground-based measurement of biosphere-atmosphere exchanges of carbon and (b) optical reflectance data from NASA satellites. Both of these data types contain complementary information about ecosystem-scale biosphere-atmosphere exchanges of carbon. These data were used in a process-based ecosystem model to analyze carbon fluxes of ecosystem components. Model parameters were estimated via a Markov Chain Monte Carlo method using: (a) only ground-based data, (b) only satellite data, or (c) both ground and satellite data. Measures of model performance improved using both ground and satellite data in the parameter estimation method. Different model results of ecosystem carbon fluxes were obtained depending on the data type used in the parameter estimation method. These results highlight differences in the information contained in "bottom-up" (tower-based) or "top-down" (satellite-based) ecological data. Further development of this approach will lead to additional understanding of the information content in a particular data type and its usefulness when applied to an ecosystem model