Monitoring Effects of Interannual Variation
in Climate and Fire Regime
on Regional Net Ecosystem Production
with Remote Sensing and Modeling
D.P. Turner1, W.D. Ritts1, J. Styles1, Z. Yang1
W.B. Cohen2, B.E. Law1, P. Thornton3, M. Falk4
1Oregon
State University
2USDA Forest Service
3National Center for Atmospheric Research
4University of California, Berkeley
Western Oregon Study Area
500
250
NEP (g C m y )
-1
750
-2
Cascade Head
Chronosequences:
NEP by Age Class
0
-1
-500
y = -13392 + 14028*exp(-0.5*(ln(x/11.93)/10.51)^2)
2
r = 0.94
-750
-1000
1000
-1
250
NEP (g C m y )
-2
750
HJ Andrews
0
-250
-500
y = -1707.8 + 2014*exp(-0.5*(ln(x/53.88)/4.12)^2)
2
r = 0.94
-750
-1000
-1
NEP (g C m y )
-2
750
250
1000
Initiation
Young
Mature
Old
800
error bars represent the
standard deviation among
three replicate plots
600
400
200
0
-200
CH
1000
500
-2
-250
500
Net Ecosystem Production (g C m yr )
wet
1000
Metolius
HJ
ME
NEP Uncertainty ~25%
0
-250
-500
NEP = (NPPA + NPPB)  (RhSoil+RhCWD+RhFWD)
NEP = NPPA + TBCA – Rs  (RhCWD + RhFWD)
y = -230.4 + 434.3*exp(-0.5*(ln(x/78.15)/1.82)^2)
r2 = 0.70
-750
-1000
dry
0
100
200
300
Stand age (years)
700
800
Campbell et al. 2004
Biome-BGC Simulation
Conifer forest in West Cascades
Carbon Flux (gC m-2 yr-1)
1500
1000
500
0
-500
Net Primary Production
Heterotrophic Respiration
Net Ecosystem Production
-1000
-1500
0
100
200
300
400
Year
Turner et al. 2003
Kilometers
Stand Replacing Disturbance
in Western Oregon
1972-2002
Year and Type of Stand Replacing Disturbance
Harvest 2000-02
Fire 2000-02
Harvest 1995-00
Fire 1995-00
Harvest 1991-95
Fire 1991-95
Harvest 1988-91
Fire 1988-91
Harvest 1984-88
Fire 1984-88
Harvest 1977-84
Fire 1977-84
0
80
Prototype Area
Harvest 1972-77
Multiple Disturbances 1972-2002
Forest-no change
Non-forest
Water
J
Prognostic Modeling Approach to Bottom-up Scaling
Land base carbon budgets for two representative (100 km2) study areas.
(Units are gC/m2/yr)
__________________________________________________________
Study Area
A
B
C
Net Ecosystem
Harvest
 Land
Production
Removals
C Pool
(A+B)
Coast Range
199
-364
-165
West Cascades
177
-7
170
__________________________________________________________
Turner et al. 2004
Land Base Carbon Budget
Western Oregon Forests
(1995-2000)
_________________5 yr mean_______________
Total NEP
13.8 TgC/yr
Harvest Removals -5.5
Products (net)
1.4
Fire
-0.1
Net
9.6 TgC/yr
________________________________________
Law et al. 2005
Diagnostic Modeling Approach
Application to larger domain
Investigation of interannual variability in NEP
Daily FPAR from satellite data
Simpler process model (base rates for
light use efficiency, Ra, Rh)
No spin-ups
Same distributed climate data
Same land cover from satellite data (aggregated)
Same stand age from satellite data (aggregated)
NPP derived from USFS Inventory plot data
West Cascades
1.5
1.5
1.0
NPP (kg C m-2 y-1)
Klamath Mountains
2.0
1.0
0.5
0.5
0.0
0.0
East Cascades
Coast Range
2.5
0.8
2.0
0.6
1.5
0.4
1.0
0.2
0.5
0.0
0.0
0
100
200
300
400
500
600
0
100
200
300
400
500
600
Stand Age (years)
Van Tuyl et al. 2005
Biome-BGC Model Run
Carbon Flux (gC m-2 yr-1)
1500
1000
How to include information on
the disturbance regime?
500
0
-500
Net Primary Production
Heterotrophic Respiration
Net Ecosystem Production
-1000
Metamodeling Approach
-1500
0
100
200
300
400
Year
Stand Age Factor for GPP
GPP = ↓PAR * FPAR * eg * Ssa
1.3
y=0.745+0.52 exp(-0.0091x)
rsq=0.73
y=1, x=78.3
GPP/GPPmax_WCfire
1.2
1.1
1.0
0.9
0.8
0.7
0.6
0
100
200
300
Age
400
GPP = gross primary production
↓PAR = incoming PAR
FPAR = fraction PAR absorbed
eg = light use efficiency
Ssa = stand age factor (0-1),
output from Biome-BGC model
Biome-BGC Model Run
Carbon Flux (gC m-2 yr-1)
1500
1000
How to include information on
the disturbance regime?
500
0
-500
Net Primary Production
Heterotrophic Respiration
Net Ecosystem Production
-1000
Metamodeling Approach
-1500
0
100
200
300
400
Rh = f (Rh-base, FPAR, Tsoil, SW, SA)
Year
Stand Age Factor for Rh
1.2
y=0.318 [0.5+2.64 exp(-0.122x)+0.5(1-0.978x)]
rsq=0.84
RH/RHmax_WCcc
1.0
0.8
0.6
0.4
0.2
0.0
0
100
200
300
Age
400
Rh = heterotrophic respiration
Rh-base = base rate of
heterotrophic respiration
FPAR = Fraction PAR absorbed
Tsoil = soil temperature
SW = soil water content
SA = stand age factor,
output from Biome-BGC model
MODIS FPAR
Spatial Resolution
= 250m - 1 km
MODIS FPAR
Temporal Resolution
= 8 day
Diagnostic Model (“Fusion”)
Parameter Optimization
Daily time step
1. Daily GPP parameters optimized with tower GPP
(or Biome-BGC GPP)
2. Daily Ra parameters optimized by reference to
measured NPP (or Biome-BGC NPP)
3. Daily Rh parameters optimzed with tower NEE (or
Biome-BGC NEE)
Fusion daily NEP (line) compared to reference NEP (circles)
At the Klamath Mountains ecozone conifer optimization site.
Bars are mean NPP for FIA plots from Van Tuyl et al. 2005
Bars are mean ecoregion NEP from Law et al. (2004)
Validation
Diagnostic NPP/NEP Model
4
375
2
374
0
373
372
-2
371
-4
370
-6
369
-8
368
-10
367
-12
366
CO2 concentration ( m mol mol -1)
Fc (m mol m -2s-1)
Boundary Layer Budget
0
0
0
0
0
0
0
0
0
0
0
0
0
:0 6 :0 2 :0 8 :0 0 :0 6 :0 2 :0 8 :0 0 :0 6 :0 2 :0 8 :0 0 :0
0
0
0
1
1
0
0
1
1
0
0
1
1
0
Flux
Concentration
Top-down Flux
Bottom-up Flux
Weighting
Boundary layer budget footprint
Monthly mean from the STILT model
(Courtesy of M. Goeckede, OSU)
Conclusions
Land-based carbon sinks significantly
offset fossil carbon emissions in Oregon
Post-fire increases in heterotrophic
respiration reduce the regional carbon
sink
Interannual variation in climate can
substantially modify regional NEP