PARENT SESSION
Oral Session # 85: GIS and Remote Sensing II; Ecological Modeling III.
Presiding: Y Lin
Thursday, August 7. 1:30 PM to 5:00 PM, SITCC Meeting Room 203.
Decadal-scale dynamics of land ownership and carbon storage in the southeastern lower coastal plain region of the U.S.
Binford, Michael*,1, Starr, Gregory1, Gholz, Henry1, 2, Barnes, Grenville1, Genc, Levent1, Smith, Scot1, Fleming, Allison1, 1 University of Florida, Gainesville, FL, USA2 US National Science Foundation, Arlington, VA
ABSTRACT- Forests of the Southeastern U.S. Coastal Plain are owned and managed by a wide variety of landowners and leaseholders, and their activities may influence ecosystem processes. We study carbon exchange and storage over 25 years at the landscape level by integrating on-the-ground measurements of biomass accumulation and net ecosystem exchange (NEE), ecosystem modeling, and satellite remote sensing methods to create several independent estimates of C dynamics within four 15 x 15 km study areas in north Florida. One of the study areas has been the site of long-term ecosystem measurements, and provides data for calibrating the models. The landscape-level, spatially explicit estimates are then combined with a time series of parcel-level ownership classes (commercial, forest products industry, private, government, mining companies, other) to examine how ownership influences C dynamics. We show an annual C uptake by ecosystem processes at the landscape level, but tree harvests, some land conversion or mining, and occasional fires often result in net annual C losses from each of our study areas. Much of the harvest C loss is removed for manufacturing forest products (e.g. paper or lumber), so contribution to atmospheric CO2 is unknown. Large-extent fires generated major C losses to the atmosphere several times in the time period. Land ownership class does not significantly affect C dynamics because owners usually lease land to others for various purposes including plantations, and the management practices of individual leaseholders determine the patterns of forest growth and harvest, and consequently C dynamics.
Key words: multi-temporal satellite remote sensing, human activities, land-use/land-cover change, ecosystem modeling