Carbon & Water Exchange of California Rangelands:An Oak-Grass Savanna, Annual Grassland and Peatland

Pasture Ecosystem

Dennis BaldocchiBiometeorology Lab, ESPM

University of California, Berkeley

Scientific and Management Questions

• What are the magnitudes and temporal variability of the exchanges of energy, CO2 and water vapor in terrestrial ecosystems?– Is my rangeland a Carbon Sink?– If, not, How can I manage it to become one?

• How does climate, vegetation type, physiological conditions phenology, changes in land use, management and disturbance history modulate the exchange of energy, carbon and water; and vice versa?– Can my rangeland off-set global warming?– Can it conserve water for the watershed and reservoir?

Take Home Messages

• Oak Woodlands are modest Carbon Sinks, Grasslands are Carbon Neutral, & Peatland pastures are Carbon Sources

• Year-to-year variability in Carbon Uptake is due to length of the wet season.– Oaks are risk adverse and experience less inter-annual variability in NEE

than grasslands• Savanna woodlands use/need more water than annual grasslands

– Trees tap ground-water to sustain themselves during the summer• Oak woodlands are darker and warmer than annual grasslands

Oak-SavannaTonzi Ranch Flux Tower

Annual GrasslandVaira Ranch

Oak-Grass Savanna: A Two Layer System

Summer:Trees green; grass dead

Spring:Trees green;grass green

Winter:Trees deciduous; grass green

Oak-Grass Savanna are Model Systems for Studying Ecosystem Ecology

• Structure/Function– Oak and grasses provide contrasting life forms, woody/herbaceous,

perennial/annual– The Canopy is open and heterogeneous

• gives us a opportunity to test the applicability of ecosystem and biogeophysical models, developed for ideal and closed canopies

• Environmental Biology– The Mediterranean climate provides distinct wet/ cool and dry/hot seasons to

examine the ecosystem response (photosynthesis, transpiration, respiration, stomatal conductance) to a spectrum of soil moisture and temperature conditions

• Global Change– The Mediterranean climate experiences great extremes in inter-annual

variability in rainfall; we experience a wider range in precipitation over a few years than long-term predicted changes.

Sherman Island Peatland Pasture

Peatland Pastures are a Model for studying Land Subsidence and Carbon Management in the Delta

Background Conditions

http://www.carolsatriani.com/img0005.html

Annual Precipitation ~500 - 700 mm/yMean Annual Temperature ~ 14-16 C

Cool Wet, Winters...Hot, Dry Summers

Camp Pardee, CA

Climate Trends: Pardee, CA

1940 1950 1960 1970 1980 1990 2000 2010

Me

an

te

mp

era

ture

(oC

)

14.5

15.0

15.5

16.0

16.5

17.0

17.5

18.0

1940 1950 1960 1970 1980 1990 2000 2010

Pre

cip

itat

ion

(m

m/y

ear)

0

200

400

600

800

1000

1200

Temperature Increased by about 1.25 C over 50 Years;

Precipitation Trend is Flat, but with High Inter-annual Variation

Environmental Conditions

Ma et al, in prep

Experimental Methods

• Eddy Covariance– above the stand (20 m tower)– below the stand (2 m tower)

• Micrometeorology • Sap flow (heat pulse)• Soil respiration chambers• Leaf Physiology (A-Ci curves)

Eddy Covariance

F w c ' '

Mean

Fluctuation

Results and Discussion

http://www.terrysteinke.com/pixpages/etchingpages/valleyoak.html

50 100 150 200 250 300 350-25

-20

-15

-10

-5

0

5

10

15

DOY

NE

E [

m

ol

m-2

s-1

]

Vaira Ranch, 2007

50 100 150 200 250 300 350-30

-25

-20

-15

-10

-5

0

5

10

15

20

DOY

NE

E [m

ol

m-2 s

-1]

Tonzi Ranch, 2007

‘Breathing of the Ecosystem’

0 100 200 300 400 500 600 700 800-6

-4

-2

0

2

4

6

DOY after Jan 2008

ne

e (g

C m

-2 d

-1)

Sherman Island Peatland Pasture

NEE = +27 gC m-2 y-1, 2008NEE = +82 gC m-2 y-1, April, 2007-April ,2008

mowing

Pasture is a Carbon Source

Ione, CA

Hydrological Year

00-01 01-02 02-03 03-04 04-05 05-06 06-07 07-08

NE

E (

gC m

-2 y

-1)

-200

-100

0

100

200

300

oak savanna annual grassland

Oak Woodlands are Risk Adverse, they Experience less inter-annual variation in NEE than Grasslands

Oak Woodlands are Carbon Sinks, -92 +/- 43 gC m-2 y-1

Annual Grasslands are Carbon Neutral, 30 +/- 116 gC m-2 y-1

Perspective

16.86 sheets of 8 ½ by 11 inch paper is 1 m2 in area and equals 76 g

Carbon Fluxes Scales with Spring Rainfall

Open Grassland

PPT3-6 (mm)

0 50 100 150 200 250 300

Ann

ual F

lux

(gC

m-2

)

-200

0

200

400

600

800

1000

1200

Savanna

PPT3-6 (mm)

0 50 100 150 200 250 300

GPP RecoNEE

Ma et al, 2007 AgForMet

John Battle's biometric NPP = 235 gC m-2 y-1.

NPP = GPPtree - Ra_tree - Rh = 299 gC m-2 y-1

NPP=NEP+Rh=97+186=283 gC m-2 y-1.

Net Primary Productivity

Vaira Grassland + Sierra Foothills

Year

1975 1980 1985 1990 1995 2000 2005

DM

(gD

M m

-2)

0

100

200

300

400

500

600

700

800

data of Bill Frost, L Xu, S Ma and D Baldocchi, Mel George et al

Dry Matter Production, Grasslands

Interannual Variability in NEE

d GPP/dt

-400 -300 -200 -100 0 100 200 300 400

d R

eco/

dt

-400

-300

-200

-100

0

100

200

300

400

California Savanna and Annual Grassland

dGPP/dt

-600 -400 -200 0 200 400 600 800

dR

eco

/dt

-400

-200

0

200

400

600

TreesAnnual GrasslandWoodland understoryOak-grass savanna

b[0] 28.21b[1] 0.605r ² 0.878

Interannual Variability inGPP and Reco scale with oneanother

274 276 278 280 282 284 286 288

-1

0

1

2

3

4

5

6

7

8

9

DOY

NE

E [

m

ol

m-2

s-1

]

Vaira 2008

Sustained and Elevated Rates of Respiration after Fall Rain

Impacts of Photosynthesis and rain pulse on ecosystem respiration of the Oak Woodland

Day

150 200 250 300 350

Fc

( m

ol m

-2 s

-1)

0

1

2

3

4

5

6

understoryopen grassland

Baldocchi et al, JGR, Biogeosciences, 2006

Remote Sensing of Canopy Structure and NPP

IKONOS: 1 m resolution in b/w; 4 m res. in color

LIDAR Measurement of Tree Height

-600 -400 -200 0 200 400 600-600

-400

-200

0

200

400

600tree height; mean=9.6299 m

0

5

10

15

20

25

30

35

40

Vaira 2006-2007

DOY

30 60 90 120 150 180 210 240 270 300 330 360 390 420 450 480 510 540

ND

VI

(ave

rag

e 10

00 t

o 1

500)

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

GP

P (

gC

m-2

day

-1)

0

2

4

6

8

10

12

NDVIGPP

Canopy Photosynthesis Follows changes in Canopy Structure

Jingfeng Xiao and D Baldocchi

area-averaged fluxes of NEE and GPP were -150 and 932 gC m-2 y-1

net and gross carbon fluxes equal -8.6 and 53.8 TgC y-1

Upscale GPP and NEE to the Biome Scale

Water, Energy and Evaporation

http://www.carolsatriani.com/2019.html

Sherman Island Peatland Pasture, April 2007-2008

Week

0 10 20 30 40 50

ET

(m

m w

eek-1

)

0

5

10

15

20

25

30

ET= 731 mm y-1

Evaporation from Irrigated Pasture

Inter-annual Variation in Rain and Evaporation

Tonzi Ranch, Ione, CA

Year

2001 2002 2003 2004 2005 2006 2007 2008 2009

E,P

(m

m y

-1)

300

400

500

600

700

800

900

EP

On Average, Woodland Uses 410 mm of Water on 540 mm of Rain

156 158 160 162 164 166

158

158.02

158.04

158.06

158.08

158.1

158.12

158.14

158.16

158.18

158.2

DOY

gro

un

d w

ate

r e

lev

ati

on

[m

]

groundwater elevation at Tonzi

G. Miller, Y. Rubin, D. Baldocchi unpublished data

Oak Trees Tap Ground Water, and Must to Survive

G. Miller, Y. Rubin, S. Ma, D. Baldocchi unpublished data

Oak Trees Access a Significant Fraction of Water from Water Table

Role of Land Management on Water and Energy Exchange and Climate

Case Study:Savanna Woodland vs Grassland

2006

Day

0 50 100 150 200 250 300 350

Air

Te

mp

era

ture

(C

)

0

10

20

30

40

GrasslandSavanna

Mean Potential Temperature difference Equals 0.84 C; grass: 290.72 K vs savanna: 291.56 K

2006, Ione, CA

Potential Temperature, Grassland

275 280 285 290 295 300 305 310 315

Po

ten

tial

Tem

per

atu

re, O

ak S

avan

na

275

280

285

290

295

300

305

310

315

b[0] -2.67b[1] 1.012r ² 0.953

Oak Woodlands are Warmer than Grasslands

2006

Day

0 50 100 150 200 250 300 350

Ene

rgy

Flu

x D

en

sity

(M

J m

-2 d

-1)

0

5

10

15

20

25

30

35

Solar RadiationNet Radiation, GrasslandNet Radiation, Savanna

1. Savanna absorbs much more Radiation (3.18 GJ m-2 y-1) than the Grassland (2.28 GJ m-2 y-1) ; DRn: 28.4 W m-2

Available Energy Drives Heat Exchange and Evaporation

u*, oak woodland, daily average

0.0 0.2 0.4 0.6 0.8 1.0

u*,

gras

slan

d, d

aily

ave

rage

0.0

0.1

0.2

0.3

0.4

0.5

2002

Tall and Rougher Savanna Promotes Turbulent mixing over Short, Smoother Grassland

Savanna injects more Sensible Heat into the atmosphere because it has more Available Energy and it is Aerodynamically Rougher

2006

Day

0 50 100 150 200 250 300 350

Sen

sibl

e H

eat

Flu

x D

ensi

ty (

MJ

m-2

d-1)

0

2

4

6

8

10

12

14

GrasslandSavanna

Gs (mm s-1)

0 2 4 6 8 10 12 14 16

LE/L

Eeq

0.0

0.2

0.4

0.6

0.8

1.0

Savanna WoodlandAnnual Grassland

Monthly Averages

Landscape Differences on Short Time Scales:Grass ET > Forest ET

California Savanna

Hydrological Year

N.a.N. 01_02 02_03 03_04 04_05 05_06 06_07

Eva

pora

tion

(mm

y-1

)

240

260

280

300

320

340

360

380

400

420

440

Oak WoodlandAnnual Grassland

Role of Land Use on ET on Annual Time Scales:Annual Oak ET (400 +/-35 mm/y) > Grass ET (322 +/-48 mm/y)

Photosynthesis >Respiration

DOY

100 150 200 250 300 350V

cmax

0

20

40

60

80

100

120

140

Quercus alba (Wilson et al)Quercus douglasii (Xu and Baldocchi)

CO2

Ps Capacity must be Great,For Short Period to Facilitatehigh rates of photosynthesis

Leaf N and Leaf Thicknessmust be adequate tosupport Ps Machinery

At Ecosystem scale LeafArea is limited enabling theSparse Canopy to Reduce

ET, too

20 40 60 80 100 120 140 160 180

20

40

60

80

100

120

140

160

180

200

Broadleaved, Deciduous Trees

Specific Leaf Area (m2 g-1)

60 80 100 120 140 160 180 200

Am

ass

(nm

ol g

-1 s

-1)

0

50

100

150

200

250

300

Quercus douglasii

data of Reich et al and Xu and Baldocchi

v (%

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.05 m0.50 m

Savanna, 2005

Day

0 50 100 150 200 250 300 350

Wat

er F

lux

0

100

200

300

400

500

600

700

ET ppt

E T (m m d-1

)

0 1 2 3 4

GP

P (

gC

m-2

d-1

)

0

2

4

6

8

1 0

Synthesis/Conclusions

Conclusions

• Oak Woodlands are Carbon Sinks, Grasslands are Carbon Neutral

• Year to year variability in Carbon Uptake is due to length of wet season.– Oaks are risk adverse and experience less inter-annual variability in

NEE than grasslands• Photosynthesis and Respiration are tightly linked

– Oaks need high N levels to attain sufficient rates of carbon assimilation for the short growing season

• Savanna woodlands need about 80 mm more water to function than nearby grasslands– Trees tap ground-water to sustain themselves during the summer

• Oaks are darker and warmer than grasslands

Biometeorology Team

Funding: US DOE/TCP; NASA; WESTGEC; Kearney; Ca Ag Expt Station

Questions

• How would you use these data to make land mgt Decisions?– Are you compelled to cut-trees for grass, to save water and

cool the climate?• What about Topography and the role of trees to maintain soils

and serve as habitat

– Encourage trees on grasslands to sequester carbon?• Do you have enough rain?

– Should Delta Peatland Pastures revert back to tules and wetlands?

• What about methane emissions (20x CO2), mosquitoes and water quality?

Annual ET and Interannual Variation

Vaira 2004

Day

0 50 100 150 200 250 300 350

E (

mm

d-1

)

0

1

2

3

4

5

2001: 301 mm 2002: 292 mm 2003: 353 mm 2004 : 284 mm

Savanna Soil Stores about 80 mm water and uses that much extra to sustain a sparse woodland, over a grassland

Oak Savanna

Day

0 50 100 150 200 250 300 350

ET

(m

m d

-1)

0

1

2

3

4

5

2002: 389 mm2003: 422 mm2004: 340 mm2005: 484 mm2007: 385 mm2008: 350 mm

Canopy Structure:Laser Altimeter Data

Goals of Research

• Quantify the Biophysical Controls on Ecosystem Metabolism (carbon gains and losses) and Water Balance of Oak Woodlands and Peatland Pastures

• Quantify and understand mechanisms controlling net annual budgets and inter-annual variability of carbon, water and energy exchange of oak woodland and annual grassland and Peatland Pastures

• Produce predictive and mechanistic ability to quantify future conditions, e.g. global warming, elevated CO2 and ozone, perturbed water supply, and land use change, land subsidence, methane emissions and in order to manage rangelands

• Upscale fluxes to the region for management decisions

Kueppers et al 2005 PNAS

IKONOS:Grassland

Sherman Island Peatland Pasture

365 456 547 639 730 821 912 1003 10950.01

0.10

1.00

10.00

100.00

1000.00

At-mo-sphere

Leaf Midday

Leaf Predawn

Day after 1/1/2006

To

tal

Wa

ter

Po

ten

tia

l (M

Pa

)

G. Miller 2009, PhD Dissertation

Evidence of Trees Tapping Ground Water

Grassland

weighted by roots (cm3 cm-3)

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40

E/ E

eq

0.00

0.25

0.50

0.75

1.00

1.25

summer rain

Oak Savanna

weighted by roots(cm3 cm-3)

0.00 0.05 0.10 0.15 0.20 0.25 0.30

E/ E

eq

0.0

0.2

0.4

0.6

0.8

1.0

ET and Soil Water Deficits:Root-Weighted Soil Moisture

Baldocchi et al., 2004 AgForMet

Grassland

weighted by roots (cm3 cm-3)

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40

E/ E

eq

0.00

0.25

0.50

0.75

1.00

1.25

summer rain

Oak Savanna

weighted by roots(cm3 cm-3)

0.00 0.05 0.10 0.15 0.20 0.25 0.30

E/ E

eq

0.0

0.2

0.4

0.6

0.8

1.0

Dynamics of Grassland Canopy Structure

Annual Grassland, Vaira Ranch

Day of Year

-100 -50 0 50 100 150 200

Leaf

Are

a In

dex

0.0

0.5

1.0

1.5

2.0

2.5

3.0

2001-20022002-20032003-20042004-2005

Grass Understory, Tonzi Ranch

Day of Year

-100 -50 0 50 100 150 200

Leaf

Are

a In

dex

0.0

0.5

1.0

1.5

2.0

2.5

3.0

2001-20022002-20032003-20042004-2005