HR: 0800h
AN: B51C-0219
TI: Quantifying Representativeness Importance Values for AmeriFlux Sites
AU: * Hargrove, W W
EM: hnw@fire.esd.ornl.gov
AF: Oak Ridge National Laboratory, P.O. Box 2008, M.S. 6407, Oak Ridge, TN 37831-6407 United States
AU: Hoffman, F M
EM: forrest@climate.ornl.gov
AF: Oak Ridge National Laboratory, P.O. Box 2008, M.S. 6407, Oak Ridge, TN 37831-6407 United States
AB: We are using a multivariate statistical clustering analysis to determine how well the current distribution of sites in the AmeriFlux network is representative of the dominant combinations of vegetation, soils, and climate which are present in the conterminous US. Statistical indices based on multivariate representativeness and site importance indicate how well the current network of towers "samples" the population of flux environments within the nation. The same empirical approach provides a repeatable rationale for the selection of additional flux tower sites by determining any number of additional locations such that the representation of the overall network is maximized by their addition. A representativeness importance value for each existing eddy covariance tower to the AmeriFlux network can be calculated. We have statistically created a series of nine sets of flux-relevant ecoregions which divide the conterminous U.S. into a set of areas within which the carbon flux from terrestrial ecosystems is expected to be relatively uniform and homogeneous. Starting with digital GIS layers of factors deemed important in regulating carbon fixation and loss from terrestrial ecosystems, we assembled a set of maps of multivariate factors which describe and characterize the flux environment in each map cell. Then, we used a k-means clustering procedure to classify each map cell into a particular group whose cells have sufficiently similar environments. Because there were as many as 30 environmental descriptors, each with nearly 8 million cells, it was necessary to perform the clustering process on a parallel supercomputer. Because the statistical process is quantitative, the similarity of a selected flux-ecoregion to every other ecoregion in the map can be calculated. Maps can be produced that show the degree of similarity to the chosen flux-ecoregion as a series of gray shades. By sequentially selecting flux ecoregions currently containing an AmeriFlux tower, maps showing the geographic area which is represented by measurements from that flux tower will be produced.
UR: http://research.esd.ornl.gov/~hnw/ameriflux/doe/index.html
DE: 0414 Biogeochemical cycles, processes, and modeling (0412, 0793, 1615, 4805, 4912)
DE: 0426 Biosphere/atmosphere interactions (0315)
DE: 0428 Carbon cycling (4806)
DE: 0439 Ecosystems, structure and dynamics (4815)
DE: 0476 Plant ecology (1851)
SC: Biogeosciences [B]
MN: Fall Meeting 2005

Acknowledgements
Research partially sponsored by the 1) Climate Change Research Division (CCRD) of the Office of Biological and Environmental Research (OBER), and 2) Mathematical, Information, and Computational Sciences (MICS) Division of the Office of Advanced Scientific Computing Research (OASCR) within the U.S. Department of Energy's Office of Science (SC). This research used resources of the National Center for Computational Science (NCCS) at Oak Ridge National Laboratory (ORNL) which is managed by UT-Battelle, LLC, for the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.