Estimating forest carbon fluxes in a disturbed southeastern landscape: Integration of remote sensing, forest inventory, and biogeochemical modeling

Quantifying carbon fluxes between the atmosphere and land surface requires detailed knowledge of the disturbance regime as well as the photosynthetic response of vegetation to climate. In this study, we use a combination of satellite remote sensing, forest inventory data, and biogeochemical modeling to assess forest carbon fluxes from central Virginia, a landscape pervasively disturbed by harvest. Using historical Landsat imagery, we have reconstructed the disturbance history and age structure of forest stands at a resolution of 90 m, from 1973 - 1999. Forest inventory data provide breakdowns of forest type and age structure for older stands. These data, together with climate and vegetation greenness from advanced very high resolution radiometer (AVHRR), are used as inputs to a version of the Carnegie-Stanford-Ames (CASA) biogeochemical model, which simulates the uptake, allocation, and respiration of carbon and associated effects of disturbance. Modeling results indicate that forests in the study region have an average net ecosystem productivity (NEP) of similar to 80 gC m(-2) yr(-1), reflecting the young age structure of rapid-rotation forests. Variability in annual forest carbon fluxes due to variations in clearing rate and climate are also examined. We find that observed variations in clearing rate may account for NEP variability of similar to 30 gC m(-2) yr(-1), while observed variations in climate may account for NEP variability of 80 - 130 gC m(-2) yr(-1). Increased temperatures tend to drive both increased photosynthesis and increased heterotrophic respiration, buffering the system from larger swings in NEP. However, this response depends strongly on stand age.