HR: 15:10h
AN: B43F-07    [Abstracts]
TI: Oregon-California Regional Carbon Budget Approach Using Model-Data Fusion to Estimate Gross Carbon Fluxes: Component of ORCA
AU: * Styles, J
EM: julie.styles@oregonstate.edu
AF: Department of Forest Science, Oregon State University, 321 Richardson Hall, Corvallis, OR 97331 United States
AU: Goeckede, M
EM: mathias.goeckede@oregonstate.edu
AF: Department of Forest Science, Oregon State University, 321 Richardson Hall, Corvallis, OR 97331 United States
AU: Law, B
EM: bev.law@oregonstate.edu
AF: Department of Forest Science, Oregon State University, 321 Richardson Hall, Corvallis, OR 97331 United States
AU: Turner, D
EM: david.turner@oregonstate.edu
AF: Department of Forest Science, Oregon State University, 321 Richardson Hall, Corvallis, OR 97331 United States
AU: Cohen, W
EM: warren.cohen@oregonstate.edu
AF: USDA Forest Service, Forestry Science Laboratory, Pacific Northwest Research Station, 3200 SW Jefferson Way, Corvallis, OR 97331 United States
AB: This study presents preliminary results from the model-data fusion component of the ORCA project, which aims to quantify carbon stocks and fluxes across the whole of Oregon and north California (see Law et al., this meeting). Process models for gross primary production (GPP), autotrophic respiration (R_A) and heterotrophic respiration (R_H) are formulated that incorporate effects of disturbance (forest stand age) on growth and respiration. The model-data fusion approach utilizes both eddy covariance and atmospheric CO₂ concentration measurements for parameter estimation, and is applied initially at three flux tower sites covering different age classes of ponderosa pine forest. Concentration data are interpreted within a one-dimensional atmospheric boundary layer model to infer daytime CO₂ flux. These flux estimates cover a larger region than the eddy covariance measurements and footprint modeling allows partitioning among surrounding land cover types and age classes (see Goeckede et al., this meeting). The simple process models for GPP, R_A and R_H are formulated with a base rate for each flux component (this rate being the light-use-efficiency in the case of GPP), and modulation with climate variables, forest structure and stand age. The simplicity of the functions make them easy to parameterize and employ across large spatial regions, driven by distributed climate data and satellite observations, while encompassing sufficient mechanistic linkages between vegetation fluxes and climate and physiological drivers to reproduce the observations effectively. The parameter optimization procedure is used to determine the dominant parameters driving diurnal and seasonal variation in flux components, and parameter uncertainties and correlations are investigated. The influences of factors such as drought, diffuse light fraction and stand age on production and/or respiration and the link between production and respiration are discussed.
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: 1615 Biogeochemical cycles, processes, and modeling (0412, 0414, 0793, 4805, 4912)
SC: Biogeosciences [B]
MN: Fall Meeting 2005