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Biosphere Modeling Galina Churkina MPI for Biogeochemistry.

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Presentation on theme: "Biosphere Modeling Galina Churkina MPI for Biogeochemistry."— Presentation transcript:

1 Biosphere Modeling Galina Churkina MPI for Biogeochemistry

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

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

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  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 Soil-Vegetation-Atmosphere- Transfer

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 D ynamic G lobal V egetation M odels  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 gC/m 2 /day month Measured data are from Tharand, Germany After parameter optimization

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

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 Site level: measurements of ecosystem/soil C fluxes, C/N content in vegetation or soil mean residence time of C in soil etc. Vegetation model

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 Churkina & Running, 1998 Dominant controls for carbon, energy and water fluxes Radiation WaterTemperature

18 Can we neglect human activities?

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