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 University2USDA Forest Service3National Center for Atmospheric Research4University of California, Berkeley

Western Oregon Study Area

Chronosequences:NEP by Age ClassCascade Head

HJ Andrews

Metolius

y = -13392 + 14028*exp(-0.5*(ln(x/11.93)/10.51)^2)r2 = 0.94

NE

P (

g C

m-2

y-1

)

-1000

-750

-500

-250

0

250

500

750

1000

y = -1707.8 + 2014*exp(-0.5*(ln(x/53.88)/4.12)^2)r2 = 0.94

NE

P (

g C

m-2

y-1

)

-1000

-750

-500

-250

0

250

500

750

1000

y = -230.4 + 434.3*exp(-0.5*(ln(x/78.15)/1.82)^2)r2 = 0.70

Stand age (years)

0 100 200 300 700 800

NE

P (

g C

m-2

y-1

)

-1000

-750

-500

-250

0

250

500

750

1000

NEP Uncertainty ~25%

NEP = (NPPA + NPPB) (RhSoil+RhCWD+RhFWD)NEP = NPPA + TBCA – Rs (RhCWD + RhFWD)

wet

dryCampbell et al. 2004

Year

0 100 200 300 400

Car

bo

n F

lux

(gC

m-2

yr-1

)

-1500

-1000

-500

0

500

1000

1500

Net Primary ProductionHeterotrophic RespirationNet Ecosystem Production

Biome-BGC SimulationConifer forest in West Cascades

Turner et al. 2003

Stand Replacing Disturbance in Western Oregon

1972-2002

J

Prototype Area

0 80

Kilometers

Year and Type of Stand Replacing Disturbance

Multiple Disturbances 1972-2002

Non-forest

Water

Forest-no change

Harvest 2000-02

Harvest 1972-77

Harvest 1977-84

Harvest 1984-88

Harvest 1988-91

Harvest 1991-95

Harvest 1995-00

Fire 2000-02

Fire 1977-84

Fire 1984-88

Fire 1988-91

Fire 1991-95

Fire 1995-00

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

Application to larger domainInvestigation 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 dataSame land cover from satellite data (aggregated)Same stand age from satellite data (aggregated)

Diagnostic Modeling Approach

0.0

0.5

1.0

1.5 West Cascades

0.0

0.5

1.0

1.5

2.0Klamath Mountains

0 100 200 300 400 500 600

0.0

0.2

0.4

0.6

0.8

NP

P (

kg

C m

-2 y

-1)

East Cascades

0 100 200 300 400 500 600

0.0

0.5

1.0

1.5

2.0

2.5 Coast Range

Stand Age (years)

NPP derived from USFS Inventory plot data

Van Tuyl et al. 2005

Age

0 100 200 300 400

GP

P/G

PP

ma

x_W

Cfir

e

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

y=0.745+0.52 exp(-0.0091x)rsq=0.73y=1, x=78.3

Year

0 100 200 300 400

Car

bo

n F

lux

(gC

m-2

yr-1

)

-1500

-1000

-500

0

500

1000

1500

Net Primary ProductionHeterotrophic RespirationNet Ecosystem Production

How to include information on the disturbance regime?

Metamodeling Approach

GPP = ↓PAR * FPAR * eg * Ssa

GPP = gross primary production↓PAR = incoming PARFPAR = fraction PAR absorbedeg = light use efficiencySsa = stand age factor (0-1), output from Biome-BGC model

Stand Age Factor for GPP

Biome-BGC Model Run

Year

0 100 200 300 400

Car

bo

n F

lux

(gC

m-2

yr-1

)

-1500

-1000

-500

0

500

1000

1500

Net Primary ProductionHeterotrophic RespirationNet Ecosystem Production

How to include information on the disturbance regime?

Metamodeling Approach

Age

0 100 200 300 400

RH

/RH

max

_WC

cc

0.0

0.2

0.4

0.6

0.8

1.0

1.2

y=0.318 [0.5+2.64 exp(-0.122x)+0.5(1-0.978x)]rsq=0.84

Rh = f (Rh-base, FPAR, Tsoil, SW, SA)

Rh = heterotrophic respirationRh-base = base rate of heterotrophic respirationFPAR = Fraction PAR absorbedTsoil = soil temperatureSW = soil water contentSA = stand age factor, output from Biome-BGC model

Stand Age Factor for Rh

Biome-BGC Model Run

MODIS FPAR

MODIS FPAR

Spatial Resolution

= 250m - 1 km

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

-12

-10

-8

-6

-4

-2

0

2

4

00:00

06:00

12:00

18:00

00:00

06:00

12:00

18:00

00:00

06:00

12:00

18:00

00:00

Fc

(mm

ol

m-2

s-1)

366

367

368

369

370

371

372

373

374

375

CO

2 co

nce

ntr

atio

n (

m mo

l m

ol-1

)Flux Concentration

Boundary Layer Budget Diagnostic NPP/NEP Model

Top-down Flux Bottom-up Flux

Boundary layer budget footprintMonthly mean from the STILT model

We

igh

tin

g(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