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Regional NACP Project: ORCA

Parameterization and validation of Biome-BGC model estimates of carbon stores and fluxes across Oregon and Northern California using FIA plot data. Tara Hudiburg 1 , Maureen Duane 1 , Dave Turner 1 , Yang Zhiqiang 1 , John Campbell 1 , Warren Cohen 2 and Beverly Law 1

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Regional NACP Project: ORCA

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  1. Parameterization and validation of Biome-BGC model estimates of carbon stores and fluxes across Oregon and Northern California using FIA plot data Tara Hudiburg1, Maureen Duane1, Dave Turner1, Yang Zhiqiang1, John Campbell1, Warren Cohen2 and Beverly Law1 1Department of Forest Science, Oregon State University, 321 Richardson Hall, Corvallis, OR 97331 2USDA Forest Service, PNW Research Station, 3200 SW Jefferson Way, Corvallis, OR 97331

  2. + + + + + + + Flux Tower + [CO2] Regional NACP Project: ORCA Objectives • Reduce uncertainty in understanding C sources and sinks • Determine effects of disturbance and variation in climate on carbon balance and water vapor fluxes over past 30 years • Improve predictions of regional carbon balances

  3. Data Flow for Biome-BGC Application, Validation Model Inputs Model Evaluation Landsat 2004 Vegetation Cover Flux Tower NEP, GPP Intensive Plots NPP, NEP, Rs Landsat (1972-2004) Disturbance History Biome-BGC Process Model NEP, GPP NPP, NPPAw DAYMET Surface Weather (1972-2004) Extensive Plots NPPAw,C Pools Forest Inventory Data NPPAw, NPP STATSGO Soil Texture, Soil Depth Landsat LAI Field Observations SLA, Foliar C:N Agricultural Statistics NPP Literature Ecophysiological Constants

  4. Data Flow for Parameters: Foliage Chemistry and Mass Model Parameterization Data Source Product Cover Type Map Remote Sensing Mean / Median values of C:N & LMA for each cover type within each ecoregion Data file with tree species, ecoregion, cover type, and biomass FIA Inventory Species specific (by ecoregion) values for C:N & LMA TERRA-PNW Extensive Plots

  5. Example Parameter Optimization Biome-BGC (by ecoregion) For all FIA conifer plots in the East Cascades ecoregion, BGC was run at multiple values of FLRN (fraction of leaf N as Rubisco) from ORCA data. Location and age were specified by FIA plot data. Outputs (e.g. wood mass) were compared with FIA estimates to minimize RMSE. N = 399 FIA mean = 5.37 BGC mean = 5.61 p = 0.26 Comparison of frequency distributions for total wood mass when BGC is run with the optimized FLNR.

  6. Use of Inventory Plot Data in BGC Model Application Parameterize age-specific mortality by vegetation type within ecoregion

  7. Ecoregion specific equations

  8. Future Analysis • Refine/Complete FIA Plot Carbon Estimates: • Model foliage and fine root production and biomass for FIA plots using ORCA plot data (Van Tuyl et al., 2005; Law et al., 2004) • Understory and standing dead C stocks • Use phase 3 FIA data to estimate carbon stocks and woody debris • Scale plot totals to ecoregion totals (currently reporting ecoregion means) • Determine biomass and NPP changes due to thinning operations (Fuels Reduction and Healthy Forest Act)

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