Estimating forest carbon fluxes by the integration of ground and remote sensing data.

Recent studies have demonstrated that accurate estimates of forest gross primary production (GPP) can be obtained by the use of a parametric model (C-Fix) which combines ground and remotely sensed data. A methodology is presented to convert these GPP estimates into values of net ecosystem exchange (NEE). It is based on the use of a process model, BIOME-BGC, which, after proper calibration, simulates all main functions of forest ecosystems at climax condition. The estimated photosynthesis and respirations are transformed into net carbon fluxes of actual forests by using a simplified approach which considers the difference between actual and potential woody biomass as an indicator of ecosystem distance from climax. The methodology was applied to all Tuscany forests for an eight-year period (1999-2006). Its validation was performed by comparing the NEE estimates to the ground data collected in San Rossore, a pine forest site for which eddy covariance measurements are available. The results obtained indicate the potential of the approach, which is finally applied to yield inputs for the analysis of forest NEE trends at regional scale.