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Biosphere Modeling

Biosphere Modeling. Galina Churkina MPI for Biogeochemistry. Biosphere modeling?. Biosphere -. … all living and non-living matters which have been affected in any way by life …. Vegetation, ecosystems. Human impacts. Vegetation Modeling. Types and purposes of vegetation models

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Biosphere Modeling

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  1. Biosphere Modeling Galina Churkina MPI for Biogeochemistry

  2. Biosphere modeling? Biosphere - … all living and non-living matters which have been affected in any way by life… • Vegetation, ecosystems • Human impacts

  3. Vegetation Modeling • Types and purposes of vegetation models • Models’ verification • Advantages and issues

  4. Purposes To examine and predict: • plant population dynamics considering competition between individual species • changes in energy flows and biogeochemical cycling of ecosystems • vegetation distribution and its shifts (biogeography models)

  5. Plant population models (gap models) • To predict plant population dynamics considering: • plant competition • establishment • growth • mortality • Time step - years

  6. Soil-Vegetation-Atmosphere-Transfer • To describe vertical exchange of energy and water fluxes • Vegetation is a “barrier” between land surface and the atmosphere • Carbon flux was added • Time step - seconds

  7. Ecosystem models • Changes in carbon, nitrogen, water fluxes and/or storage of ecosystems • Trees are not defined individually • Climatic inputs + plant physiology/empiric relationships • Time step - days, months, years

  8. Dynamic Global Vegetation Models • To examine and predict changes in vegetation distribution • Changes in carbon, water fluxes and/or storage of ecosystems • Time step - months, years

  9. Inputs and outputs after Cramer et al. 1999

  10. How to verify the model results?

  11. Site Level Constraints After parameter optimization gC/m2/day gC/m2/day month month Measured data are from Tharand, Germany

  12. Spatial constrains Remotely sensed DATA from MODIS LAI simulated with BIOME-BGC model month

  13. Global constraints? Effect of industrial N deposition on global normalized NEP and NPP (kgC/m2/yr)

  14. Verification at different scales • Global: • atmospheric inversions • Regional: • country statistics (forest inventories,etc.) • remote sensing • Landsat, MODIS, SeaWiFS Vegetation model • Site level: measurements of • ecosystem/soil C fluxes, • C/N content in vegetation or soil • mean residence time of C in soil • etc.

  15. Advantages • Simulate responses of ecosystems to regionally heterogeneous • temperature and rainfall anomalies • nitrogen deposition rate • land use • Generate predictions

  16. Issue • Verification of model results at regional and global scales • Simulation of human impacts on ecosystems

  17. Radiation Water Temperature Dominant controls for carbon, energy and water fluxes Churkina & Running, 1998

  18. Can we neglect human activities?

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