Modelling the coupling between carbon turnover and climate variability of terrestrial ecosystems.

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Seminar presentation at ICRAF, Nairobi (Kenya), 1st December 2010

Seminar presentation at ICRAF, Nairobi (Kenya), 1st December 2010

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  • 1. Modelling the coupling between carbon turnover and climate variability of terrestrial ecosystems Per-Erik Jansson Department of Land and Water Resources Engineering Royal Institute of Technology KTH, Stockholm Seminar at ICRAF, Nairobi, 1 December 2010
  • 2. Outline of presentation
    • Some general features of the CoupModel representing coupled ecosystem processes
    • Examples of how model has been used to describe specific sites with detailed measurements, regional scale with only standared data and climate scenarious
    • Some implications for future studies
  • 3. A process oriented Ecosystem model - CoupModel
    • Coupled heat and mass transfer model for soil-plant-atmosphere systems
  • 4. Model Availability and Features http://www.lwr.kth.se/Vara%20Datorprogram/CoupModel/index.htm Includes documentation and tutorials
  • 5. Water and Heat Processes
  • 6. Carbon and Nitrogen Processes
  • 7. Process oriented modelling platform with many components
  • 8. Coupling between different submodels
  • 9. Transpiration and Photosynthesis
    • Transpiration is a function of net radiation and resistances in plant and atmosphere
    • Photosynthesis is a function of light and the stomata resistance
    LAI
  • 10. Single/Multiple Big Leaf Model
  • 11. Emission of NO and N20
  • 12. Methane emission model
  • 13. Modelling of carbon dynamic of Swedish forest soils
    • Using models for interpretation of data and for upscaling
    • Development of procedures for calibration and upscaling using Bayesian calibration methods
    • Producing results for various scales
  • 14.
    • We have simple data from large regions and detailed data from some few sites
    • The few sites (Lustra CFS) and regional Forest inventory have been used together
    • The model has been used as a tool to understand and to make upscaling and downscaling
    To start... x 1 yr
  • 15.
    • (1) estimation of parameters from regional data – 100 years.
    • (2) site specific data were used to calibrate the model for Flakaliden (dry mesic) and Asa (wet).
    • (3) climate change scenarios (A2, B2) were used together with parameters from the regional site (1) on a 100 year perspective for dry-mesic sites.
    3 steps ... 1 yr
  • 16.
    • Objective: Estimate trends in soil C storage
    • Approach: Regional scale with representative sites
    • Data: Standing tree biomass and soil C and N pools
    Regional approach N
  • 17. Regional input data N
  • 18. Tree Biomass simulation in for four regions
  • 19. N Decomp. rate coeff. (kh) Organic N uptake Versus min N Uptake Soil C change (g C m -2 yr -1 )
    • Current soil C pools in the south increases whereas central and northern soils are close to steady state
    • Need for another source of N in addition to mineralised N
    • Different decomposition rate coeff. along Swedish transect
  • 20. Tree and Field layer dynamics important for modelling long term dynamics South North
  • 21. Flakaliden- calibration
    • Objective : Quantify major fluxes of C, heat and water including uncertainty estimates
    • Approach: Bayesian uncertainty theory
    • Data:
      • Standing tree biomass and soil C and N pools
      • Internal fluxes i.e. litterfall, root litter production and DOC
      • Eddyflux measurements of CO 2 , heat and water
      • Soil physical properties
      • Soil temperature
    N
  • 22. Model performance (mean of accepted runs)
  • 23. Uncertainty estimates 644 ±74 363 ±43 207 ±31 -69 ±18 570 ±55 138 ±37
  • 24. Climate change scenarios
    • Objective: Effects on C-budget and on governing and limiting factors due to climate change
    • Approach: Climate change of regional approach
    • Data: IPCC climate change scenarios Hadley A2 and B2
    N
  • 25. Different response on key components of ecosystem environment
  • 26. Response for GPP (North and South)
  • 27. Seasonal Dynamics Differs (north – south)
  • 28.
      • NEP increased in all regions along the Swedish transect.
      • Major part of the increase related to tree growth.
    Climate change effect on tree growth and soil C change
  • 29. Implications for future
    • Use best uncertainty methods to allow for estimations probabilistic distributions of parameters for specific field investigations
    • Make simulation experiments to understand uncertainties of coupled models rather than single submodels
  • 30. Coupled models are necessary to understand long term behaviour of ecosystem
    • Soil climate is strongly coupled with vegetation and atmopheric climate
    • Soil physical conditions are a dynamic forcing for nitrogen and cabon turnover
    • Dynamic description of plant cover need to include both field and canopy layers for Swedish forest
    • Carbon, Nitrogen, Water and Heat have to be considered together
  • 31.
    • Upscaling and downscaling is now possible with flexibility and transparency but...
    • Uncertainties are still very difficult to express for the regional scale
    • Site specific data has generated new knowledge but no easy answers for upscaling…
    Current Climate and Management Future Climate and Management x x x Site Region 100 yr 1 yr
  • 32. Last comment
    • An adviser who believes too much in the figures from a mathematical model will be equally poor as the one who fully trusts results from field investigations.
  • 33. Thanks for Thanks for your attention