HR: 1340h
AN: B43D-1597    [Abstracts]
TI: Identifying Temporal Patterns in Light use Efficiency for two Loblolly Pine Plantations in a Drained Lower Coastal Plain Region of North Carolina, U.S.A.
AU: * Quirino, V F
EM: fquirino@vt.edu
AF: Department of Forestry, Virginia Polytechnic Institute and State University., 319 Cheatham Hall, Blacksburg, VA 24061, United States
AU: Wynne, R H
EM: wynne@vt.edu
AF: Department of Forestry, Virginia Polytechnic Institute and State University., 319 Cheatham Hall, Blacksburg, VA 24061, United States
AU: Noormets, A
EM: anoorme@ncsu.edu
AF: Department of Forestry and Environmental Resources and Southern Global Change Program North Carolina State University, 920 Main Campus Drive Venture Center II, Suite 300, Raleigh, NC 27606, United States
AU: Huemmrich, K F
EM: Karl.F.Huemmrich@nasa.gov
AF: Joint Center for Earth Systems Technology (JCET) University of Maryland Baltimore County, Code 614.4 Biospheric Sciences Branch NASA's Goddard Space Flight Center, Greenbelt, MD 20771, United States
AU: Sun, G
EM: Ge_Sun@ncsu.edu or gesun@fs.fed.us
AF: Southern Global Change Program USDA Forest Service, 920 Main Campus Drive Venture Center II, Suite 300, Raleigh, NC 27606, United States
AU: McNulty, S
EM: steve_mcnulty@ncsu.edu
AF: Southern Global Change Program USDA Forest Service, 920 Main Campus Drive Venture Center II, Suite 300, Raleigh, NC 27606, United States
AB: Light Use Efficiency (LUE) is a variable present in most ecosystem models driven by remote sensing. Among other factors, LUE varies with time. In this study we evaluate the temporal variation of LUE over a one year period for two loblolly pine plantations – one mid-rotation and one recently harvested. Specifically, we determine the most reasonable measurement time periods for LUE, and if these periods vary with stand age. The underlying hypothesis is that short term temporal changes in LUE cancel out over a certain amount of time, and therefore, to estimate forest productivity at landscape to regional scales using moderate resolution satellite data these intensive measurements are unnecessary. To test this hypothesis we use data collected in two micrometeorological tower sites that are a part of the Ameriflux network. They are located in the coastal plain region of North Carolina, U.S.A and are less than five kilometers apart. For this study eddy covariance measurements and photosynthetically active radiation (PAR) sensors are used to obtain gross primary production (GPP) and the fraction of incident photosynthetically active radiation absorbed by the canopy (ƒAPAR). LUE is calculated as GPP divided by fAPAR. The analysis of the data consists of first calculating daily LUE averages for the entire study period. Changes in both the trend and variance of LUE are being assessed using autoregressive conditional techniques for time series analysis.
DE: 0466 Modeling
DE: 0480 Remote sensing
SC: Biogeosciences [B]
MN: 2007 Fall Meeting