Carbon & Water Exchange of an Oak-Grass Savanna

EcosystemDennis Baldocchi

ESPMUC Berkeley

Oak-Savanna Model System for Studying Ecosystem Ecology

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

perennial/annual– The Canopy is open and heterogeneous, giving us a opportunity to

test the applicability of ecosystem and biogeophysical models, mostly 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 pptover a few years than long-term predicted changes.

Oak-Grass Savanna: A Two Layer System

Summer:Trees green; grass dead

Spring:Trees green;grass green

Winter:Trees deciduous; grass green

Water and the Environment: Biogeophysical-Ecohydrological View

Water

SurfaceConductance

Transpiration/Evaporation

AvailableEnergy

Photosynthesis/Respiration

LAI

Carbon

NutrientsLitterSoil Moisture

PBL ht

Sensible Heat

Goals of Research

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

• Quantify net annual budgets and inter-annual variability of carbon, water and energy exchange of oak woodland and annual grassland

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

Kueppers et al 2005 PNAS

Land use in Northern CA

From Joe McFadden

Precipitation ~500 - 700 mm/y

Mean Temperature and Precipitation

Camp Pardee, CA

Climate Trends:Pardee, CA

1940 1950 1960 1970 1980 1990 2000 2010

Mea

n te

mpe

ratu

re (o C

)

14.5

15.0

15.5

16.0

16.5

17.0

17.5

18.0

1940 1950 1960 1970 1980 1990 2000 2010

Prec

ipita

tion

(mm

/yea

r)

0

200

400

600

800

1000

1200

Temperature Increased by about 1.25 C over 50 Years

Inferred Trends in Phenology;leaf-out about 10 days earlier over 50 years

Estimate of onset of photosynthesis for blue oak woodland

Year

1940 1950 1960 1970 1980 1990 2000 2010

Day

NEE

= 0

82

84

86

88

90

92

94

96

98Coefficients:b[0] 303.01b[1] -0.108r ? 0.331

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

IKONOS: Savanna & Fetch

IKONOS:Grassland

Results and Discussion

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

Dynamics of 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

Canopy Structure: Tonzi Ranch

– Blue oak (Quercus douglasii)– LAI=0.90– Height 7.1 +/- 3.05 m– Diameter at breast height

26.6 +/- 0.11 cm– Understory: annual C3

grasses• Brachypodium distachyon,

Hypochaeris glabra, Bromus madritensis

Canopy Structure:Laser Altimeter Data

20 40 60 80 100 120 140 160 180

20

40

60

80

100

120

140

160

180

200

0.14835 to 5.7046 5.7046 to 12.581 12.581 to 24.942 24.942 to 40.76 40.76 to 399.8

Trees and Leaf Area Index

[N]ppt/Eeq

0.1 1 10 100

LAI

0.1

1

10

various functional types:Baldocchi and Meyers (1998)savanna:Eamus et al. 2001Oak Savanna, CA

b[0]: -0.68b[1]: 0.84r ?: 0.69

MeteorologySavanna, Overstory

(Tonzi Ranch)

Year2002 2003 2004 2005 2006

Tair

(o C)

-20

-10

0

10

20

30

40

50

Prec

ipita

tion

(mm

)

0

20

40

60

80

100

120

mean TairMin TairMax Tairprecipitation(mm)

Soil Moisture

Savanna, Overstory(Tonzi Ranch)

Year2002 2003 2004 2005 2006

Soi

l Moi

stur

e (c

m3

cm-3

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0 cm20 cm50 cm

Leaf Physiology

How Does Stomatal Conductance Respond to Drought?

• H0: Ball-Berry Coefficient Varies– Sala & Tenhunen– Damesin, Rambal,

Joffre

• H1: Ball-Berry Coefficient is constant– Vcmax varies and

stomata gradually close to keep Ci/Ca ~ 0.7

– Joe Berry, SIB II– Gabriel Cornic

0ss

k Arhg gC

= +

Physiological Capacity:Seasonal Dynamics

DOY

90 120 150 180 210 240 270

Dar

k R

espi

ratio

n ( μ

mol

m-2

s-1)

0

2

4

6

8

10

Normalized Vcmax to 25oC Blue Oak leafTonzi Ranch 2001

DOY

90 120 150 180 210 240 270

V cmax

( μm

ol m

-2s-1

)

0

20

40

60

80

100

Xu and Baldocchi, 2003 Tree Physiology

Predawn Ψ and Stomatal conductance

DOY

100 150 200 250 300Stom

atal

con

duct

ance

(mol

m-2

s-1)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

DOY

100 150 200 250 300 350

Ψpd

(MPa

)

-8

-6

-4

-2

0

Quercus douglasii

PreDawn Water Potential (MPa)

-7 -6 -5 -4 -3 -2 -1 0

V cmax

( μm

ol m

-2 s

-1)

0

20

40

60

80

100

120

140

Vcmax varies with time and scales with Pre-Dawn Water Potential

DOY100 150 200 250 300 350

Vcm

ax

0

20

40

60

80

100

120

140

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

High Vcmax must be Achieved in Seasonal lyDroughted Ecosystems to attain Positive Carbon

Balance

Stomatal ConductanceTonzi oak leaf, tree #92, Li-Cor 6400 measurement, 2001

ARH/Ca (mol m-2s-1)

0.00 0.01 0.02 0.03 0.04 0.05

g s (m

ol m

-2s-1

)

0.0

0.1

0.2

0.3

0.4

0.5b[0] 0.0063b[1] 8.88r ? 0.88

Ball-Berry Coef is constant with Pre-dawn water potential down to –70 bars

Xu and Baldocchi2003, Tree Physiol

Tree Leaf Age (Days)

0 50 100 150 200 250

Ci/C

a

0.5

0.6

0.7

0.8

Day of Year

0 50 100 150 200 250

N (%

)

1.0

1.5

2.0

2.5

3.0

3.5

4.0

From Leaf Isotope and Nutrition Measurements,Ci/Ca is relatively constant, near 0.7, and N is high early in

the season

Ma et al in prep

gs

0.0 0.1 0.2 0.3 0.4 0.5

Ci/C

a

0.4

0.6

0.8

1.0

Gas Exchange Data suggest Ci/Ca decreases with Drought

‘Isotope derived Ci/Ca are cumulative, Not the same as gas exchange’ Kevin Tu

Ecosystem Ecology

Switches, Pulses and Lags are Evident in Annual Time Series of Trace Gas Exchange

Vaira Grassland 2001

Day/Hour

0 50 100 150 200 250 300 350

Fc (μ

mol

m-2

s-1

)

-25

-20

-15

-10

-5

0

5

10

15

Xu and Baldocchi, AgForestMet, 2004

Complicating Dynamical Factors

G rass lands

D ay

0 50 100 150 200 250 300 350

NE

E (g

C m

-2 d

-1)

-6

-4

-2

0

2

4

M ed ite rran ean G rass lan dT em p era te C 4 g rass lan d

D a ta s o u rc e s : V a len tin i e t a l. 1 99 6 ; B a ld o c c h i + X u , u n p u b lis h e d ; V e rm a + S u yk e r

Late s

pring ra

ins

GPP(+)

S p rin g /S u m m er D ro u g h tθ (-)G P P (-); R eco(-)

G P P > 0 ;AM F ro s t:G P P (-)

T m in > 0 oCG P P = f(L AI) (+ )

R a in P u lseR eco(++ )G P P =0

Au tu m n R a in s :T (-), θ (++ )G P P (+), R eco(-)

sn o w co v eredd o rm an t g rassG P P =0 , R eco > 0

• Pulses• Switches• Lags

Daily Carbon Fluxes

Savanna, Overstory(Tonzi Ranch)

Day2002 2003 2004 2005 2006

NE

E (g

C m

-2 d

ay-1

)

-8

-6

-4

-2

0

2

4

6

8

10

12

NEERecoGPP

Annual C balance:NEE = GPP + Reco

Oak Savanna

Day

0 50 100 150 200 250 300 350

NEE

(gC

m-2

d-1

)

-8

-6

-4

-2

0

2

4

6

8

10

2002: -140 gC m-2 y-1

2003: -622004: -722005: -128

Day

0 50 100 150 200 250 300 350

GPP

(gC

m-2

d-1

)

0

2

4

6

8

10

12

2002: 840gC m-2 y-1

2003: 8902004: 8312005: 1059

Day

0 50 100 150 200 250 300 350

Rec

o (g

C m

-2 d

-1)

0

2

4

6

8

2002: 657 gC m-2 y-1

2003: 8012004: 6872005: 919

Ione, CA

Hydrological Year

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

NE

E (g

C 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

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

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

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

Carbon Fluxes Scale with Spring Rainfall

Open Grassland

PPT3-6 (mm)

0 50 100 150 200 250 300

Annu

al 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

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

dRec

o/dt

-400

-200

0

200

400

600

TreesAnnual GrasslandWoodland understoryOak-grass savanna

b[0] 28.21b[1] 0.605r ?0.878

Interannual Variability inGPP and Reco scale with oneanother

Grassland CO2 flux vs Sunlight at different LAI

F C ( μ

mol

m-2

s-1) -20

-15

-10

-5

0

5

F C ( μ

mol

m-2

s-1)

-20

-15

-10

-5

0

5

Qp (μmol m-2s-1)

0 500 1000 1500 2000-25

-20

-15

-10

-5

0

5

0 500 1000 1500 2000-25

-20

-15

-10

-5

0

5

(a) DOY025-040, LAI=1.0(b) DOY071-080, LAI=1.8

(c) DOY096-105, LAI=2.4

(d) DOY130-140 end of senesence

Xu + Baldocchi, AgForMet 2004

0 10 20 30

R eco (

μmol

m-2

s-1)

-2

0

2

4

6

8

10

Soil temperature (oC)0 10 20 30

R eco (

μmol

m-2

s-1)

-2

0

2

4

6

8

10

DOY347-365Q10=2.51

DOY180-230, Q10=2.11

DOY129-139,Q10=2.2

(a) (b)

Ecosystem Respiration

Xu + Baldocchi, AgForMet 2004

Environmental Controls on Respiration

Soil volumetric water content (m3 m-3)

0.0 0.1 0.2 0.3 0.4

Rec

o/Rre

f

0.0

0.5

1.0

1.5

2.0Fast growth period data

Rain pulse

Xu + Baldocchi, AgForMet 2004

274 276 278 280 282 284 286 288

-1

0

1

2

3

4

5

6

7

8

9

DOY

NEE

[ μm

ol m

-2 s

-1]

Vaira 2008

Sustained and Elevated Respiration after Fall Rain

Impact of rain pulse on ecosystem respiration: Fast response

Day

150 200 250 300 350

Fc

(μm

ol m

-2 s

-1)

0

1

2

3

4

5

6

understoryopen grassland

Baldocchi et al, JGR, Biogeosciences, 2006

Quantifying the impact of rain pulses on respiration: Assessing the Decay Time constant

Day after rain (d)-5 0 5 10 15 20

Rec

o (gC

m-2

d-1)

0

2

4

6

8

10

0 2 4 6 8 10 12 140

1

2

3d214 2003 understory

(τ, Max/e)

Amount of the rain (mm)0 10 20 30 40 50 60

Tim

e co

nsta

nt (d

)0

2

4

6

8

10

Understoryb0=1.43b1=0.097r2=0.95

Grasslandb0=0.88b1=0.07r ? 0.98

Xu, Baldocchi, Tang, 2004 Global Biogeochem Cycles R b b t

eco = +−

0 1 exp( )τ

Respiration Enhancement Depends on Initial Condition

R e c o p u l s e - b a c k g r o u n d v s b a c k g r o u n d . d a t a f r o m g r a s s l a n d a n d s a v a n n a

R e c o _ b a c k g r o u n d ( g C / m 2 d )

0 . 0 0 . 5 1 . 0 1 . 5 2 . 0 2 . 5 3 . 0

Peak

of p

ulse

-bac

kgro

ud (g

C/m

2s)

0

2

4

6

8

Xu, Baldocchi, Tang Global Biogeochem Cycles 2004

Soil tempreture (oC)

30 35 40 45 500.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

14:50h

6hFo=0.037e0.0525T, Q10=1.69, R2=0.95

Tonzi Open areas

Soil temperature (oC)25 30 35

1.1

1.2

1.3

1.4

1.5

1.6

1.7

Under treesDOY 211

Fu=0.337e0.0479T, Q10=1.61, R2=0.80

20h

6h

12:50h12h

16h

Tonzi Under trees

10h

24h

Tang, Baldocchi, Xu, Global Change Biology, 2005

Respiration and Photosynthesis

Lags and Leads in Ps and Resp: Diurnal

June

Time (hour)

0 4 8 12 16 20 24

Flux

Den

sity

-10

-8

-6

-4

-2

0

6

7

soil respirationcanopy photosynthesis

Tang et al, Global Change Biology 2005.

Soil Resp Lags Ps by about 5 to 6 hours

June, Rsoil-Ps lag

lag (30 min intervals)

-30 -20 -10 0 10 20 30

lag

corre

latio

n

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

Tang et al, Global Change Biology 2005.

•Photosynthesis Switches Partitioning between dominance by Roots vs Microbes

Stimulation of Autotrophic is much delayed after onset of photosynthesis

2003, Nocturnal CO2 Efflux (0-5, 19-24)

Day

0 50 100 150 200 250 300 350

F unde

rsto

ry-F

gras

slan

d (μ m

ol m

-2 s

-1)

-6

-4

-2

0

2

4

6Oak Savanna, 2003

Day

0 50 100 150 200 250 300 350 400

Can

opy

Phot

osyn

thes

is (g

C m

-2 d-1

)

-10

-8

-6

-4

-2

0

2

Baldocchi et al, JGR, Biogeosciences, 2006

Remote Sensing of NPP

LED sensor intercomparison and calibration

Falk, Ma, Ruiz, Hehn, Baldocchi . in prep

Vaira 2006-2007

DOY

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

ND

VI (a

vera

ge 1

000

to 1

500)

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0G

PP (g

C m

-2 d

ay-1

)

0

2

4

6

8

10

12

NDVIGPP

-120 0 120 240

-0.2

0.0

0.2

0.4

-4

0

4

LSW

I

MODIS - LSWI

gC

day

-1

Daily NEE

-0.2 0.0 0.2 0.4

-5

0

5

daily

NE

E

LSWI

R2 =0.74

Land Surface Water Index (LSWI) plotted with daily NEE for 2004/2005

PRI and NEE

-120 -60 0 60 120 180

-0.10

-0.08

-0.06-4

-2

0

2

4

6

PR

I

DOY after 1/1/2005

PRI

gC

day

-1

14 day NEE

Land Surface Water Index LSWI = (ρ860 - ρ1640)/(ρ860 + ρ1640)

PRI = (ρ531 - ρ570) / (ρ531 + ρ570)

Falk, Ma, Ruiz, Hehn, Baldocchi . in prep

Jingfeng Xiao and D Baldocchi

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

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

Water and Evaporation

Annual ET and Interannual Variation

Vaira 2004

Day

0 50 100 150 200 250 300 350

E (m

m d

-1)

0

1

2

3

4

5

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

Oak Savanna

Day

0 50 100 150 200 250 300 350

ET

(mm

d-1

)

0

1

2

3

4

5

2002: 389 mm2003: 422 mm2004: 340 mm2005: 484 mm

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

Grassland

θ, weighted by roots (cm3 cm-3)

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40

λ E/λ

Eeq

0.00

0.25

0.50

0.75

1.00

1.25

summer rain

ET and Soil Water Deficits:Root-Weighted Soil Moisture

Baldocchi et al., 2004 AgForMet

Oak Savanna

θ weighted by roots (cm3 cm-3)

0.00 0.05 0.10 0.15 0.20 0.25 0.30

λE/λ

Eeq

0.0

0.2

0.4

0.6

0.8

1.0

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 DifferencesOn Short Time Scales, Grass ET > Forest ET

Ryu, Baldocchi, Ma and Hehn, JGR-Atmos, submitted

156 158 160 162 164 166158

158.02

158.04

158.06

158.08

158.1

158.12

158.14

158.16

158.18

158.2

DOY

grou

nd w

ater

ele

vatio

n [m

]groundwater elevation at Tonzi

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

Oak Trees Tap Ground Water

California Savanna

Hydrological Year

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 Scale, Forest ET > Grass ET

Ryu, Baldocchi, Ma and Hehn, JGR-Atmos, submitted

Photosynthesis >Respiration

DOY100 150 200 250 300 350

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

A(

l)

0

50

100

150

200

250

300

Quercus douglasii

data of Reich et al and Xu and Baldocchi

θ 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

Wt

Fl

0

100

200

300

400

500

600

700

ET ppt

E T (m m d-1

)

0 1 2 3 4

GP

P (g

C m

2d

)

0

2

4

6

8

10

Synthesis/Conclusions

Role of Land Management on Water and Energy Exchange and Climate

Case Study:Savanna Woodland vs Grassland

Case Study:

Energetics of a Grassland and Oak Savanna

Measurements and Model

2006

Day

0 50 100 150 200 250 300 350

Ener

gy F

lux

Den

sity

(MJ

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) ; ΔRn: 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*, g

rass

land

, dai

ly a

vera

ge

0.0

0.1

0.2

0.3

0.4

0.5

2002

4b. Savanna injects more Sensible Heat into the atmosphere because it has more Available Energy and it is Aerodynamically Rougher

4a. U* of tall, rough Savanna > short, smooth Grassland

2006

Day

0 50 100 150 200 250 300 350

Sen

sibl

e H

eat F

lux

Den

sity

(MJ

m-2

d-1)

0

2

4

6

8

10

12

14GrasslandSavanna

2006

Day

0 50 100 150 200 250 300 350

Air

Tem

pera

ture

(C)

0

10

20

30

40GrasslandSavanna

5. Mean Potential Temperature differences are relatively small (0.84 C; grass: 290.72 vs savanna: 291.56 K); despite large differences in Energy Fluxes--albeit the Darker vegetation is Warmer

Compare to Greenhouse Sensitivity ~2-4 K/(4 W m-

2)

2006, Ione, CA

Potential Temperature, Grassland

275 280 285 290 295 300 305 310 315

Pote

ntia

l Tem

pera

ture

, Oak

Sav

anna

275

280

285

290

295

300

305

310

315

b[0] -2.67b[1] 1.012r ? 0.953

Vapor Pressure

LongwaveEnergy

ShortwaveEnergy

Sensible HeatLatent Heat

PBL Height

Time 1

Time 2

Time 3

Temperature

Conceptual Diagram of PBL Interactions

Time (hrs)

6 8 10 12 14 16 18

pbl h

t (m

)

0

500

1000

1500

2000

2500

3000

Time (hrs)

6 8 10 12 14 16 18e a (

Pa)

0

500

1000

1500

2000

2500

3000

H and LE: Analytical/Quadratic version of Penman-Monteith Equati

T im e

6 8 10 12 14 16 18 20

T su

rfac

e

280

290

300

310

albedo = 0 .3; R c=2560 s /malbedo = 0 .15; R c = 320 s /m

ET-PBL O ak-G rass Savanna Land U se

T im e

6 8 10 12 14 16 18 20

Rne

t (W

m-2

)

0

200

400

600

800

albedo = 0.3; R c=2560 s /malbedo = 0.15; R c = 320 s /m

•The Energetics of afforestation/deforestation is complicated

•Forests have a low albedo, are darker and absorb more energy

•But, Ironically the darkerforest maybe cooler (Tsfc) than a bright grassland due to evaporative cooling

And Smaller Temperature Difference, like field measurements, if weconsider PBL, Rc, Ra and albedo….!!

Summer Conditions

Time (hours)

4 6 8 10 12 14 16 18 20

Tair

(K)

286

288

290

292

294

296

298

grass, albedo = 0.30; Rc = 2560 s/m; Ra = 40 s/msavanna, albedo=0.15; Rc = 320 s/m; Ra= 10 s/m

u* savanna = 2 u* grassland

0200

400600

800

0.10.2

0.30.4

0.5288

289

290

291

292

293

RsAlbedo

T air

289.5

290

290.5

291

291.5

292

292.5

Tair can vary by 3 C by changing albedo and Rs

Biometeorology Team

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

Conclusions

• Savanna woodlands need about 80 mm more water to function than nearby grasslands

• Year to year variability in Carbon Uptake is due to length of wet season.

• Photosynthesis and Respiration are tightly linked