canadian forest carbon budgets at multi scales · dr. changhui peng, uinversity of quebec at...
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Canadian Forest Carbon Canadian Forest Carbon Budgets at MultiBudgets at Multi--Scales:Scales:
Dr. Changhui Peng, Uinversity of Quebec at Montreal
Drs. Mike Apps and Werner Kurz, Canadian Forest Service
Dr. Jing M. Chen, University of Toronto
U of T
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OUTLINE
• Canada’s Forests and C Accounting System
• Canadian Forest Carbon Budgets
Modelling Approaches Data sourcesModel validation and comparison
• Future Challenges
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- 10% of global forests- 25% of global boreal forests
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C Accounting at Four Spatial Scales
National
Regional or Provincial
Operational
Stand-levelEnsures consistency across spatial scalesUses best available data for each region
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Modelling Approach:
1. Forest Inventory Based Forest Carbon Accounting:CBM-CFS (Kurz and Apps, 1992, 1999)
2. Integrated Process-Model and Remote Sensing:InTEC (J. Chen et al, 2000, 2003)
3. Hybrid Model Simulation at Stand and Landscape Levels: TRIPLEX (Peng et al, 2002; Zhou et al. 2004)
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CBM-CFS2: Carbon Budget Model of Canadian Forest Sector
• CBM-CFS– First national scale
forest analysis
• Data Driven:– Forest Inventory
(NFBI and CanFI)– Soil Data– Disturbances
• Fire• Insects• Harvests
(Kurz, Apps, Webb, McNamee; 1992, Kurz and Apps, 1999)
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Key steps in satellite-based estimation of carbon balance (NBP)
Net Biome Productivity(NBP) (annual)
Algorithms
Land CoverType
(annual)
Leaf Area Index (LAI)
(10 days)
Net PrimaryProductivity (NPP) (daily)
Net EcosystemProductivity
(NEP) (annual)
Evapo-transpiraton(ET) (daily)
Meteorological data (daily),soil and biomass data
(long term)
Changes in atmosphere,Climate (annual)
Disturbances(fire, insect, harvest)
(annual)
Fire Scar Age(annual)
SpectralReflectance
(J. Chen et al, 2003)
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Additional datasets used
• Remotely sensed land cover and LAI maps (1 km resolution)
• Modeled and partially validated NPP map for 1994 (1 km resolution)
• Gridded climate data (1901-1998, U. East Anglia, 0.5°, monthly means)
• Soil Landscape of Canada (texture, total carbon, ~10k polygons)
• Nitrogen deposition data (1983-1998, 12 stations, CAPMoN)
• Tower flux data at 4 locations
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Role of Disturbance
NBP = NEP – Fires – Harvest – Insect-induced Mortality
NBP: Net Biome Productivity
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The variation of NPP with age
0
50
100
150
200
250
300
350
400
0 50 100 150 200 250 300age (yr.)
NP
P (
g C
m-2
)
11m,measured
11m,simulated
8m,measured
8m,simulated
5m,measured
5m,simulated
259.1 /]1)25
(*0.2(1[*156age
eageNPP −+=
Site index
Role of Forest Age
(Black Spruce in Ontario)
(Chen et al. 2002)
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Ontario’s Forest Age-class Structure (1990)
Boreal Region (BO)
22.50
11.497.05
11.50 10.12
0102030
20 40 60 80 100 120 140+Age (year)
Area
(milli
on h
a)
Cool Temperate Region (CT)
2.34
1.351.06
1.691.28
0.03 0.0301
23
20 40 60 80 100 120 140+Age (year)
Area
(milli
on h
a)
Moderate Temperate Region (MT)
0.39 2.29 4.76
80.67 77.14
13.57 21.30
0
50
100
20 40 60 80 100 120 140+
Age (year)
Area
(tho
usan
d ha
)
SA
BO
CT
MT
CBM-CFS2
(Peng et al. 2000)
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Ontario's Forest Age (1920-1990)
30
40
50
60
70
80
90
100
1920 1930 1940 1950 1960 1970 1980 1990
Time (year)
Age
(ye
ar)
BorealCool TemperateModerate Temperate
CBM-CFS2
(Peng et al. 2000)
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Model Validation and Comparison
Testing model simulations against:
- Forest Growth &Yield plots- Forest Inventory- Soil measurements- Eddy Covariance Flux Towers
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Comparison of Averaged Simulations and Observations -Aboveground Biomass (Hegyi, 1972)
TRIPLEX Simulations(Peng et al. 2002)
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Comparison of modeled total aboveground
biomass carbon with forest inventoryAverage aboveground biomass carbon in different types of Canada's forests
y = 1.393x - 0.6304R2 = 0.8013
0
1
2
3
4
5
6
7
0 1 2 3 4 5 6 7
Inventory (kgC/m2)
Mod
eled
(kgC
/m2 )
Evergreen Needleleaf Forest
DeciduousBroadleaf Forest
Mixed Forest
Burns
Open Land
(J. Chen et al. 2003)
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Comparison of modeled total soil organic carbon with polygon data from Soil Landscape of Canada
Average dead organic carbon in different types of Canada's forests
y = 1.0095x - 0.3114R2 = 0.8631
10
15
20
25
30
10 15 20 25 30
Soil Landscape of Canada (kgC/m2)
Mod
eled
(kgC
/m2 )
Evergreen NeedleleafForestDeciduousBroadleafForestMixed Forest
Burns
Open Land
(J. Chen et al. 2003)
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Historical Variation in NEP 121-year old black spruce stand, Saskatchewan (53.890 oN, 105.114 oW)
-300
-250
-200
-150
-100
-50
0
50
100
150
200
1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990
Year
NEP
(gC/
m2 )
No change (baseline)climate All effectsMeasured
Tower data source: Paul Jarvis of U Edinburgh and Andy Black of UBC (J. Chen et al. 2003)
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Comparison of simulated NPP with Remoted Sensing based estimation of NPP at Landscape Level (Lake Abitibi Model Forest)
Kappa Statistic:K=0.6
(Good agreement if 0.55<K<0.70)
(a) TRIPLEX Simulation(Zhou et al, 2004)
(b) Estimation based onRemote sensing (Liu et al.2002)
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Comparison of three sets of NBP results All Canada's Forests, 1901 to 1998
-150
-100
-50
0
50
100
150
200
250
300
1910 1920 1930 1940 1950 1960 1970 1980 1990year
NBP
(Tg
C/y)
Spatially Explicit Modeling (Chen et al., 2002b)
Spatially Aggregated Modeling (Chen et al., 2000b)CBM-CFS (Kurz and Apps,1999)
(J. Chen et al. 2003)
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0
2
4
6
8
10
1920 1940 1960 1980 2000
Are
a (M
illio
nha
)Note apparent increase after 1970
What do the changes in disturbances in Canada’s forests Affect Carbon Balance?
ClearCut Fire Insects Total
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Challenges for Science• Weaknesses in Scientific Understanding:
– Allocation of C in plant tissues
– Nutrient feedback
– CO2 fertilization at ecosystem scale - is it real? important?
– Projecting changes in disturbance regimes (fire, insect, harvesting, ice damage…)
– Peatland carbon dynamics
– etc….
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Scientific Challenges
• Quantifying land-use change at 1 ha resolution.• Regional parameter databases and validation.• Accounting for forest management impacts.• Estimating C stock changes in forested wetlands.• Estimating N2O and CH4 emissions.• Incorporating inter-annual variability and long-term climate
effects.• Identifying, quantifying and reducing uncertainty.
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http://carbon.cfs.nrcan.gc.ca(Kurz and Apps, 2004)