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ABSTRACT
Carbon storage of forested land areas is geographically variable. The spatial distribution can be a result of: 1) local site conditions (such as climate, geomorphology, and soil) that determine long-term carbon dynamics; 2) previous land use and current forest management practices that manipulate site conditions and change carbon pools; and 3) forest types, a consequence of both above. Although many studies on carbon accounting of forests and soils have been conducted, the challenge remains of how to incorporate various environmental factors to estimate and predict carbon storage and dynamics. There is still need for a credible tool that integrates climate, soil, and forest attributes, combined in a form conducive to spatial analysis, to predict changes in carbon storage in forested land areas. The US government has invested in the establishment of the State Soil Geographic Database (STATSGO) and the nationwide data for the Forest Inventory and Analysis (FIA) program. However, no attempt to link the two geographical information databases for carbon analysis has been published. This study examines a methodology to link STATSGO and FIA data for carbon accounting of forested lands. In this process, using the data for South Carolina as an example, soil and forest attributes were combined; carbon storage was classified by soil types and forest types; and spatial relationships among site conditions and forest attributes were analyzed. The poster presents the results and discusses opportunities for dynamic modeling of carbon storage by linking STATSGO and FIA.
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