Land-Use and Land-Cover Change: Decadal-Scale Dynamics of Land Ownership Land Management and Carbon Storage Patterns in the Southeastern Lower Coastal Plain Region of the U.S.

We are studying how climate variability and land ownership influences carbon storage dynamics in forested ecosystems in the southeastern United States. Our time extent is from A.D. 1975 to 2000. The questions for this project are "How much carbon has been lost or gained from the SE forests as a consequence of climate variation and ownership patterns?" and "How can we model future changes in carbon storage if we know how ownership will change?” Our focus is on non-public (private industrial, private non-industrial) lands in the region. Four small (15 km x 15 km) sample areas were selected in year 1 for intensive study to determine the spatial and temporal patterns of changing land ownership and changing carbon storage over the 25-year period covered by data available from the Landsat program. Digital maps of land ownership compiled and mapped from local-government records for the year 2000 were completed in year 2 of the project, and historical maps at 2 to 5-year intervals are being inferred (property appraisers keep no historical maps, and we have developed a method for inferring previous parcels). The database model is described, as is the method for inferring land transfers in historical time. Carbon storage is being measured with remote sensing methods calibrated by on-the-ground measurements in an ecosystem that has been under intense study for nearly 20 years. This project is partially funding biomass (C) and net ecosystem exchange (NEE) measurements in a natural-regeneration stand of upland pine forest. Weather records from several stations within the study area define climate variability, and we will use the weather records to 1) examine relationships between landscape-wide carbon content changes and climate variation and 2) model C uptake and biomass change with models that use meteorological variables as inputs. Salient accomplishments include the development of a general database model for tracking ownership, ownership type, and spatial extent of parcels over time, the development of a land-cover classification system that can be linked to biomass/carbon data reported in the literature, the development of a literature database of biomass and carbon content of the major forests of the S.E. U.S. coastal plain, NEE measurements of the natural regrowth stand, which represents ~20% of the upland forests of Florida, the acquisition and processing of over half of the cloud-free Landsat data for the study area from 1975 to 2000, and the nearly finished development of statistical models of the relationships between Landsat data and biomass/C storage. The delay of approvals for year 2 acquisitions of Landsat data is the only major issue slowing progress. We anticipate finishing the time-series land-ownership maps, and two alternative approaches to C storage maps, early in the third year of the study. Final analysis will be conducted in the middle of year three, and we anticipate writing a number of papers for submission to peer reviewed journals.