HR: 16:30h
AN: B54A-03    [Abstracts]
TI: Beyond Potential Vegetation: Combining Lidar Remote Sensing and a Height- Structured Terrestrial Ecosystem Model for Improved Estimates of Carbon Stocks and Fluxes at a Set of Sites in North and Central America
AU: * Hurtt, G C
EM: george.hurtt@unh.edu
AF: University of New Hampshire, Institute for the Study of Earth, Oceans, and Space 39 College Road, Durham, NH 03824 United States
AU: Dubayah, R
EM: dubayah@umd.edu
AF: University of Maryland, Geography Department 1149 LeFrak Hall, College Park, MD 20740 United States
AU: Fearon, M
EM: matthew.fearon@unh.edu
AF: University of New Hampshire, Institute for the Study of Earth, Oceans, and Space 39 College Road, Durham, NH 03824 United States
AU: Drake, J
EM: jbdrake@mail.ucf.edu
AF: University of Central Florida, Department of Biology , Orlando, FL 32816 United States
AU: Schwarz, P
EM: paul.schwarz@oregonstate.edu
AF: Oregon State University, Department of Forest Science Richardson Hall, Corvallis, OR 97331 United States
AU: Pacala, S
EM: steve@eno.princeton.edu
AF: Princeton University, Department of Ecology and Evolutionary Biology, Princeton, NJ 08544 United States
AU: Moorcroft, P
EM: pmoorcroft@oeb.harvard.edu
AF: Harvard University, Department of Organismic and Evolutionary Biology, Cambridge, MA 02138 United States
AB: Because of natural disturbance events, human land use, and land-use history, terrestrial ecosystems globally are generally not in a "potential" state. However, the information required to adequately describe the current state of terrestrial ecosystems is lacking and currently limiting our understanding of the carbon cycle. To address this challenge, we combined airborne lidar remote sensing of vegetation structure and the height-structured terrestrial ecosystem model ED to produce lidar-initialized model estimates of ecosystem structure, carbon stocks, and carbon fluxes at a set of 10 study sites in North and Central America. Field data were used to test model results and form the basis for improved model parameterizations. Resulting lidar-initialized ED estimates of ecosystem structure and above-ground biomass compared favorably to field-based estimates at key study sites, and corresponding model estimates of net carbon fluxes differed substantially from estimates based on bracketing alternatives. The results of this multi-site study build on earlier published results from La Selva, Costa Rica and provide additional evidence of the power of combining remote sensing data on vegetation structure with a height-structured ecosystem model to go beyond potential vegetation and address the heterogeneity in terrestrial ecosystems caused by disturbance. Extending these analyses to larger scales will require the development of regional and global lidar data sets, and the continued development and application of height-structured ecosystem models.
DE: 1600 GLOBAL CHANGE (New category)
DE: 1615 Biogeochemical processes (4805)
DE: 1640 Remote sensing
DE: 0400 Biogeosciences
SC: Biogeosciences [B]
MN: 2004 AGU Fall Meeting