The C budget of Japan: Ecosystem Model (TsuBiMo)

Y. YAMAGATA and G. ALEXANDROV

Climate Change Research Project, National Institute for Environmental

Studies, JAPAN

Regional Carbon Budgets: from Methodologies to QuantificationBeijing, China, 15-18 November 2004

Outline

Structure of modelCalibration of model using flux dataCalibration using inventory dataEstimation of carbon stock, NPP and NEPComparison with ecological measurement and inventory based estimateAccuracy assessment of R/S (FPAR) data useConclusion and future direction

Outline

Structure of model Calibration of model using flux dataCalibration using inventory dataEstimation of carbon stock, NPP and NEPComparison with ecological measurement and inventory based estimateAccuracy assessment of R/S (FPAR) data useConclusion and future direction

Structure of our forest ecosystem carbon balance model (TsuBiMo)

Gross Primary Production

Autotrophic respiration

Heterotrophic respiration

Litterfall

TsuBiMo: Litter-fall compartment

very resistant fraction

non-resistant fraction

resistant fraction

Herbaceous fraction of litter-

fallWoody fraction

of litter-fall

The carbon pools of litter

The carbon pools of litter

Regional Carbon Budget Assessment using TsuBiMo

CO2 fluxes (JapanFlux)

Yield tables (MAFF)

GPP (Pg)

NPP (Pn)

NEP (PE)

NBP

Changes in total carbon stock of the managed forests in Japan

Carbon stock changes in the pool of non- living organic matter

Satellite images (JAXA)

Carbon stock changes in the pool of living organic matter

Accumulation in biomass

Age distribution (MAFF)

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

Outline

Structure of modelCalibration of model using flux dataCalibration using inventory dataEstimation of carbon stock, NPP and NEPComparison with ecological measurement and inventory based estimateAccuracy assessment of R/S (FPAR) data useConclusion and future direction

2003/10/17 2003/11/6

Pictures From Dr. NishidaTakayama Flux

Cite

Scheme of using CO2 flux data for calibrating productivity model

1 10.0432 2 [ ] ;

1 1g K

sP D p T Ln

s

max; 1 ; ;[ ]

oPAR K

K

I ps f p

p T K

TsuBiMo function for GPP :

Observation

Pmax light-saturated photosynthesis

K light attenuation coefficient

ß light-use efficiency

fPAR fraction of absorbed PAR

Re (night time flux)NEE (day time flux)

-

GPP

Calibrated Productivity Model (Takayama Flux Data 1999-2001)

CO2 fluxes v.s. Productivity

Model

BLUE – observed fluxes

YELLOW-

28-days moving average

RED –

model estimatesThe model could successfully

replicate the forest ecosystem CO2 flux responses to climate variations

Agreement with World Biometric Data of Calibrated Productivity

Model

1211

121

[ ]; 91 ;

26 ( )

m K m am

opt

w p T E kJ mol

T C Takayama

1211

121

; 91 ;

26 ( )

K m m am

opt

p w T E kJ mol

T C Takayama

121

121

1

;

162.5 ;

26 ( )

K m mm

a

opt

p w T

E kJ mol

T C TsuBiMo

Blue – Local Calibration Red – Global Calibration

Outline

Structure of modelCalibration of model using flux dataCalibration using inventory dataEstimation of carbon stock, NPP and NEPComparison with ecological measurement and inventory based estimateAccuracy assessment of R/S (FPAR) data useConclusion and future direction

Yield Table data for Growth Function

Age dependence of wood stock in m3/ha (yield tables)

21[ ] b

nB Age P b Age

The estimates of conversion coefficient specified by age

TsuBiMo function for biomass growth :Yield table

data

1nP b

2b

The model parameters depends on species and site fertility, however the data from ecological studies are not sufficient.

-> We use yield table data for filling the gap.

Yield Tables v.s. Model Estimates

Sugi, North Kinki (Fukuda et al., 2004)

Line shows the values produced by the function above for

b2=0.854772; Pnb1=4.61481

assumedDots show the values derived from the yield table above by using the assumed conversion coefficient

21[ ] b

nB Age P b Age 1 20.59181; 0.79216b b

warm-temperate

cool-temperate

subtropical

Outline

Structure of modelCalibration of model using flux dataCalibration using inventory dataEstimation of carbon stock, NPP and NEPComparison with ecological measurement and inventory based estimateAccuracy assessment of R/S (FPAR) data useConclusion and future direction

Carbon Stock in Japanese Forest

Very Low

Low

Average

High

Stock, tC/ha Stock classes

0

40

80

120

160

200

3.75 GtC

Carbon Stock is estimated using TsuBiMo

NPP of Japanese Forests NPP is estimated using TsuBiMo from vegetation period, light intensity, temperature and precipitation

Legend:

Subalpine conifer forest zone

Cool-temperate broadleaf forest zone

Warm-temperate broadleaf forest zone

Subtropical forest zone

NPP, g C/m2/yr Interpretation in terms of vegetation zones

150

350

550

700

850

1350

Forest Age and Carbon Stock in Japan

Area of the k-th age class (sk )

Forest age data

Carbon stock estimate

Carbon stock changes with age

NEP estimates in Japanese forest

Alexandrov, G.A., Yamagata, Y., 2002. Net Biome Production of managed forests in Japan. Science in China, 45 (Supp): 109-115

Scenario: harvest age lifted up to 70 years

Outline

Structure of modelCalibration of model using flux dataCalibration using inventory dataEstimation of carbon stock, NPP and NEPComparison with ecological measurement and inventory based estimateAccuracy assessment of R/S (FPAR) data useConclusion and future direction

Model v.s. Carbon Stock Data

Black: total carbon stock after breakup

Grey: carbon stock changes in the tree biomass

Lines: Model estimates (Kawaguchi and Yoda,1986)

Beech forest in Japan

Comparison of NEP estimate (tentative)

Ecological model Forestry inventory

（ tC/ha ･ yr ）

17.9 MtC/yr

21.0 MtC/yr

Artificial forest only

Outline

Structure of modelCalibration of model using flux dataCalibration using inventory dataEstimation of carbon stock, NPP and NEPComparison with ecological measurement and inventory based estimateAccuracy assessment of R/S (FPAR) data useConclusion and future direction

Accuracy assessment of R/S data use

Yellow – MODIS

Blue – Ground

0.0

2.0

4.0

6.0

8.0

10.0

12.0

4 5 6 7 8 9 10 11month

Pg

MODIS Ground

Productivity can be estimated by using FPAR as input to Model

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 coincidenceModel-data integration using different data sources including R/S need to be developed