The%20C%20budget%20of%20Japan:%20Ecosystem%20Model%20(TsuBiMo) - PowerPoint PPT Presentation

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The%20C%20budget%20of%20Japan:%20Ecosystem%20Model%20(TsuBiMo)

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Estimation of carbon stock, NPP and NEP ... Satellite images (JAXA) Carbon stock changes in the pool of living organic matter ... of wood stock in m3/ha ... – PowerPoint PPT presentation

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Title: The%20C%20budget%20of%20Japan:%20Ecosystem%20Model%20(TsuBiMo)


1
The C budget of Japan Ecosystem Model (TsuBiMo)
Regional Carbon Budgets from Methodologies to
Quantification Beijing, China, 15-18 November 2004
  • Y. YAMAGATA and G. ALEXANDROV
  • Climate Change Research Project, National
    Institute for Environmental Studies, JAPAN

2
Outline
  • Structure of model
  • Calibration of model using flux data
  • Calibration using inventory data
  • Estimation of carbon stock, NPP and NEP
  • Comparison with ecological measurement and
    inventory based estimate
  • Accuracy assessment of R/S (FPAR) data use
  • Conclusion and future direction

3
Outline
  • Structure of model
  • Calibration of model using flux data
  • Calibration using inventory data
  • Estimation of carbon stock, NPP and NEP
  • Comparison with ecological measurement and
    inventory based estimate
  • Accuracy assessment of R/S (FPAR) data use
  • Conclusion and future direction

4
Structure of our forest ecosystem carbon balance
model (TsuBiMo)
5
TsuBiMo Litter-fall compartment
6
Regional Carbon Budget Assessment using TsuBiMo
Changes in total carbon stock of the managed
forests in Japan
Carbon stock changes in the pool of non- living
organic matter
Carbon stock changes in the pool of living
organic matter
GPP (Pg)
NPP (Pn)
NEP (PE)
Accumulation in biomass
NBP
Satellite images (JAXA)
CO2 fluxes (JapanFlux)
Yield tables (MAFF)
Age distribution (MAFF)
7
Input data grids of 1km resolution
  • Monthly temperature
  • Monthly precipitation
  • Monthly solar radiation
  • Forest age structure
  • Managed forest 15 age classes of 5-years
  • Natural forests 4 age classes of 20-years

8
Outline
  • Structure of model
  • Calibration of model using flux data
  • Calibration using inventory data
  • Estimation of carbon stock, NPP and NEP
  • Comparison with ecological measurement and
    inventory based estimate
  • Accuracy assessment of R/S (FPAR) data use
  • Conclusion and future direction

9
Takayama Flux Cite
Pictures From Dr. Nishida
2003/10/17
2003/11/6
10
Scheme of using CO2 flux data for calibrating
productivity model
Observation
TsuBiMo function for GPP
Pmax light-saturated photosynthesis K light
attenuation coefficient ß light-use
efficiency fPAR fraction of absorbed PAR
11
Calibrated Productivity Model (Takayama Flux Data
1999-2001)
12
CO2 fluxes v.s. Productivity Model
BLUE observed fluxes YELLOW- 28-days moving
average RED model estimates
The model could successfully replicate the forest
ecosystem CO2 flux responses to climate variations
13
Agreement with World Biometric Data of Calibrated
Productivity Model
Blue Local Calibration Red Global Calibration
14
Outline
  • Structure of model
  • Calibration of model using flux data
  • Calibration using inventory data
  • Estimation of carbon stock, NPP and NEP
  • Comparison with ecological measurement and
    inventory based estimate
  • Accuracy assessment of R/S (FPAR) data use
  • Conclusion and future direction

15
Yield Table data for Growth Function
TsuBiMo function for biomass growth
Yield table data
Age dependence of wood stock in m3/ha (yield
tables)
The estimates of conversion coefficient
specified by age
The model parameters depends on species and site
fertility, however the data from ecological
studies are not sufficient. -gt We use yield
table data for filling the gap.
16
Yield Tables v.s. Model Estimates
subtropical
warm-temperate
cool-temperate
Sugi, North Kinki (Fukuda et al., 2004)
assumed
Line shows the values produced by the function
above for b20.854772 Pnb14.61481
Dots show the values derived from the yield table
above by using the assumed conversion coefficient
17
Outline
  • Structure of model
  • Calibration of model using flux data
  • Calibration using inventory data
  • Estimation of carbon stock, NPP and NEP
  • Comparison with ecological measurement and
    inventory based estimate
  • Accuracy assessment of R/S (FPAR) data use
  • Conclusion and future direction

18
Carbon Stock in Japanese Forest
Carbon Stock is estimated using TsuBiMo
19
NPP of Japanese Forests
NPP is estimated using TsuBiMo from vegetation
period, light intensity, temperature and
precipitation
20
Forest Age and Carbon Stock in Japan
Forest age data
Carbon stock estimate
Area of the k-th age class (sk )
Carbon stock changes with age
21
NEP estimates in Japanese forest
Scenario harvest age lifted up to 70 years
Alexandrov, G.A., Yamagata, Y., 2002. Net Biome
Production of managed forests in Japan. Science
in China, 45 (Supp) 109-115
22
Outline
  • Structure of model
  • Calibration of model using flux data
  • Calibration using inventory data
  • Estimation of carbon stock, NPP and NEP
  • Comparison with ecological measurement and
    inventory based estimate
  • Accuracy assessment of R/S (FPAR) data use
  • Conclusion and future direction

23
Model v.s. Carbon Stock Data
Beech forest in Japan
Black total carbon stock after breakup Grey
carbon stock changes in the tree biomass Lines
Model estimates
(Kawaguchi and Yoda,1986)
24
Comparison of NEP estimate (tentative)
Forestry inventory
Ecological model
17.9 MtC/yr
21.0 MtC/yr
Artificial forest only
(tC/ha?yr)
25
Outline
  • Structure of model
  • Calibration of model using flux data
  • Calibration using inventory data
  • Estimation of carbon stock, NPP and NEP
  • Comparison with ecological measurement and
    inventory based estimate
  • Accuracy assessment of R/S (FPAR) data use
  • Conclusion and future direction

26
Accuracy assessment of R/S data use
Yellow MODIS Blue Ground
Productivity can be estimated by using FPAR as
input to Model
27
Conclusion and future direction
  • We have try to estimate the national level carbon
    budget using a process based ecosystem model
    (TsuBiMo)
  • Calibration with flux and inventory data showed
    that the global model underestimate the
    productivity at managed forest test sites
  • comparisons of national level estimate with
    inventory approach showed regional discrepancies
    but rather good total coincidence
  • Model-data integration using different data
    sources including R/S need to be developed
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