Why Ecologists Need Soil Physics, and Vice Versa

Dennis Baldocchi

Ecosystem Sciences Division

Dept of Environmental Science, Policy and Management

University of California, Berkeley

Campbell LectureWashington State University

Feb 16, 2010

The Big Picture

• Soil Physics Drives Many of the Biological Processes in the Soil that are of interest to Ecologists and Relevant to Life in the Soil– Soil Temperature, Moisture, Trace Gas Diffusion

• Ecologists Have Many interesting Questions that relate to Mass and Energy Transfer and Require Collaboration with Soil Physicists– Greenhouse Gas (H2O, CO2, N2O, CH4,) Production through Soil

Evaporation and Respiration, Organic Matter Decomposition, DeNitrification and Methanogenesis

Outline

• Flux Measurement Methods/Models– Better Experimental Design– Eddy Covariance, an alternative to Chambers– Soil CO2 probes & Fickian Diffusion– Improved Incubation Measurement Protocols

• How Temperature modulates Soil Respiration

• How Photosynthesis modulates Soil Respiration

• How Moisture and Rain Regulates Soil Respiration & Evaporation

• Lessons on Soil Evaporation Modeling using Understory Eddy Covariance Measurements

Soil Respiration and Evaporation:Chambers Perturb Solar Energy Input & Wind and

Turbulence, Humidity and Temperature Fields

Soil Chamber

Time

0 200 400 600 800 1000 1200

Flu

x

-2.05e-6

-2.00e-6

-1.95e-6

-1.90e-6

-1.85e-6

-1.80e-6

-1.75e-6

Chamber h: 0.1 mChamber h: 0.3 m

Soil Chamber

Time

1 10 100 1000 10000

[C]

0.0003

0.0004

0.0005

0.0006

0.0007

0.0008

0.0009

Chamber h: 0.1 mChamber h: 0.3 m

( )c F F c

t z h

Scalar Fluxes Diminish with Time, using Static Chambers, due to C build-up and its negative Feedback on F

Ability to measure dC/dt well is a function of chamber size and F

Understory Eddy Flux Measurement System:An Alternative Means of Measuring Soil CO2 and Energy Fluxes:

LE and H

Rn Forest Floor (W m-2)

-50 0 50 100 150 200 250 300

H +

E

+ G

(W

m-2

)

-50

0

50

100

150

200

250

300

slope = 1.22int = 4.66

Reasonable Energy Balance Closure can be Achieved

Jack pine

Baldocchi et al. 2000 AgForMet

CO2 Diffusion Model, t =768 hoursMillington and Quick Tortuosity

CO2, ppm

0 2000 4000 6000 8000 10000 12000 14000 16000

De

pth

, m

0.01

0.1

1

F=1 F3.0F=5

Soil Respiration, F = 3 mol m-2 s-1

CO2 (ppm)

100 1000 10000 100000

Z (

m)

0.001

0.01

0.1

1

soil moisture: 0.1 m3 m-3

0.20.3

Design Experiment and Interpret Data by Modeling CO2 in Soil

Model derived from Campbell’s ‘Soil Physics with Basic’

CO2 Diffusion Model, t =768 hoursMillington and Quick Tortuosity

CO2, ppm

0 2000 4000 6000 8000 10000 12000 14000 16000

De

pth

, m

0.01

0.1

1

F=1 F3.0F=5

Continuous Soil Respiration with Soil CO2 Sensors and Eddy Covariance

8 cm

16

cm

2 cm

7.5

cm

Transmitters

Datalogger

Probe (sensor)

Casing

Theory/Equations

Moldrup et al. 1999

a c

CF D

z

2( ) Fcpc

a

D

D

1.750 ( / 293.15) ( /101.3)a aD D T P

Fcp: fraction silt and sand; : constant; porosity;: air-filled pore space

Validation with Chambers

2003

Fc: chamber (mol m-2 s-1)

0 1 2 3 4 5 6 7

Fc: fl

ux-g

radi

ent (

mol

m-2

s-1

)

0

1

2

3

4

5

6

7

under treeopen

Coefficients:b[0]: -0.115b[1]: 0.943r ²: 0.915

Tang et al, 2005, Global Change Biology

Validation with Understory Eddy Covariance System

Baldocchi et al, 2006, JGR Biogeosciences

CO2 Efflux, Oak Savanna, 2003

Day

150 200 250 300 350

Fc

(m

ol m

-2 s

-1)

-1

0

1

2

3

4

Eddy CovarianceFlux-Gradient

2004

Day

0 50

-1

0

1

2

3

4

‘Dennis, you should perform incubation studies to interpret you field data’

Paraphrase, Eldor Paul

Continuous Flow Incubation System

Intact soil core of known volume and density to assess water potential

Vaira Soil

Volumetric Soil Moisture (cm3 cm-3)

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

Wat

er P

oten

tial,

MP

a

-40

-30

-20

-10

0

a: -0.0178b: -2.0129

Re-Designing Incubation Studies

• Use Closed path IRGA– Data log CO2 continuously with precise time stamp to better

compute flux from dC/dt at time ‘zero’.– Avoid/ exclude P and C perturbation when closing lid

• Use soil samples with constrained volume– If you know bulk density and gravimetric water content, you can

compute soil water potential from water release curve

• Expose treatment to Temperature range at each time treatment, a la Fang and Moncreif.– Reduces artifact of incubating soils at different temperatures and

thereby burning off different amounts of the soil pool– Remember F = [C]/t– Because T will be transient sense temperature at several places

in the soil core.

Temperature and Soil Respiration

Janssens and Pilegaard, 2003 GCB

Soil Respiration vs Soil Temperature, measured at one depth, yields Complicated functional responses, Hysteresis and Scatter

Irvine and Law, GCB 2002

Day 204, 2001, Vaira Grassland

Time (hours)

0 5 10 15 20

So

il T

emp

erat

ure

10

15

20

25

30

35

40

2 cm4 cm8 cm16 cm32 cm

It is critical to measure Soil Temperature at Multiple Depths and with Logarithmic Spacing

Soil Temperature Amplitude and Phase Angle Varies with Depth

Measure Soil Temperature at the Location of the Source

Tsoil (C)

10 15 20 25 30 35 40

Rso

il at

8 c

m (

mo

l m-2

s-1

)

2.0

2.5

3.0

3.5

4.0

4.5

2 cm4 cm8 cm16 cm32 cm

Otherwise Artificial Hysteresis or Poor Correlations may be Observed

( ) ( )exp( )ar

E TR T R T

RT

Curiel-Yuste, Ma, Baldocchi, 2010 Biogeochemistry

Soil Respiration Acclimates with Temperature over Time:Cold Incubated Soils (10C) doubled their rates of respiration compared to warm soil incubations (30 C) after 140 days

Savanna: Ideal Model to Separate Contributions from Autotrophs (Roots)

and Soil Heterotrophs (Microbes)

Under a Tree:~Ra+Rh

Open Grassland:~Rh (summer)

Soil tempreture (oC)

30 35 40 45 50

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

14:50h

6h

Fo=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, GCB, 2005

Soi

l Res

pira

tion

But Sometimes Hysteresis between Soil Respiration and Temperature is Real:

The Role of Photosynthesis and Phloem Transport

Soil CO2 is Greater Under Trees than Senescent Grassland

2003-2004Open Grassland

Day after Jan 1, 2003

0 100 200 300 400 500

CO

2 (p

pm)

1000

10000

100000

2 cm8 cm16 cm

2003-2004Savanna UnderStory

Day after Jan 1, 2003

0 100 200 300 400 500

CO2,

Dai

ly Av

erag

e

1000

10000

100000

2 cm8 cm16 cm

Baldocchi et al, 2006, JGR Biogeosciences

Impact of Rain Pulse and Metabolism on Ecosystem respiration: Fast and Slow Responses

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, 2006, JGR Biogeosciences

Lags and Leads in Ps, Soil Temperature and Soil Respiration

Tang et al, Global Change Biology 2005.

June

0 4 8 12 16 20 24

So

il R

esp

ira

tio

n (

mo

l m

-2 s-1 )

6.0

6.1

6.2

6.3

6.4

6.5

0 4 8 12 16 20 24

Ca

no

py P

ho

tosyn

th

esis

(

mo

l m

-2 s-1 )

-10

-8

-6

-4

-2

0

Time

0 4 8 12 16 20 24

So

il T

em

pe

ra

ture

, 8

cm

22

24

26

28

30

32

34

36

38

40

42

July, Rsoil-Ps lag

lag (30 min)

-30 -20 -10 0 10 20 30

lag

corr

elat

ion

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

Continuous Measurements Enable Use of Inverse Fourier Transforms to Quantify Lag Times

Tang et al, Global Change Biology 2005.

Thompson and Holbrook 2003 J Theor Biol

Photosynthetic Priming Effect?

Phoelem Transport Model shows that Sucrose Fronts travel at ~ 2 m/hour;Blue Oak trees are 13 m tall…~6 hour lag

Photo

Res

p

5 10 15 20

02

46

FC

O2,

B(µ

mol

m-2

s-1)

GPPA (µmol m-2 s-1)

Figure 10. Nighttime understory CO2 flux below the main canopy as a function of whole canopy GPP

y = 0.23x r2 = 0.78, p<0.01

Misson et al. AgForMet. 2007

Irvine et al 2005 Biogeochemistry

Other Evidence that Soil Respiration Scales with GPP

Understory Eddy Flux Auto Chambers

Impact of Rain Pulses on Soil Respiration:

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 Respiration after Fall Rain from Senescent Grassland

Rains Pulsed Do Not have Equal Impacts

Rec

o (g

C m

-2d-1

)

2

4

6

8

10

PP

T (

mm

d-1

)

10

20

30

40

50

60

DOY270 285 300 315

v (c

m3 cm

-3)

0.0

0.1

0.2

0.3

v (c

m3 c

m-3

)

0.0

0.1

0.2

0.3

Reco

PPT

Xu, Baldocchi Agri For Meteorol , 2004

Why Do Rain pulses Produce more C from Open Grassland than Understory?

Amount of precipitation (mm)

0 10 20 30 40 50 60 70

Tot

al c

arbo

n re

spire

d (g

C m

-2)

0

20

40

60

Grasslandintercept=5.84slope=0.96r ²=0.86

understoryintercept=3.66slope=0.47r ²=0.91

Xu et al. 2003 GBC

What Happens to the Grass?; It is too Dry to Promote Microbial Decomposition

June October

PhotoDegradation Can Be a Important Pathway for Carbon Loss in Semi-Arid Rangelands (~20-30 gC m-2 season-1)

200 400 600 800 1000-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Rglobal

W m-2

FC

O2

mol

e m

-2 s

-12007

soil CO2 flux-gradienteddy covariance

Rutledge et al 2010 Global Change Biology

Data of S. Ma and D. Baldocchi, unpublished

• Type I pulse is the first pulse occurring right after summer drought;

• Type II pulse is the subsequent pulse.

Forming a Bridge between Soil Physics and Ecology:Refining Sampling and Analytical Measurements Protocols

Use Appropriate and Root-Weighted Soil Moisture, Not Arithmetic Average

0

0

z

z

z dP z

dP z

Root Distribution

Cumulative Distribution

0.0 0.2 0.4 0.6 0.8 1.0 1.2

De

pth

0.0

0.5

1.0

1.5

2.0

B =0.98

0.90

Soil Moisture, arithmetic average

Chen et al, WRR 2009

Soil Moisture, root-weighted

Use of Root-Weighted Soil Moisture Enables a ‘Universal’ relationship between normalized Evaporation and Soil

Moisture to be Observed

Evaporation and Soil Moisture Deficits

GrasslandD70-300, 2001

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/

Eeq

0.00

0.25

0.50

0.75

1.00

1.25

summer rain

Oak Savanna, 2002D105-270

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

Baldocchi et al, 2004AgForMet

Combining Root-Weighted Soil Moisture and Water Retention Produces a Functional Relation between E and Water Potential

Vaira Soil

Volumetric Soil Moisture (cm3 cm-3)

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

Wat

er P

oten

tial,

MP

a

-40

-30

-20

-10

0

a: -0.0178b: -2.0129

soil water potential (MPa)

-5 -4 -3 -2 -1 0 E

/E

eq

0.0

0.2

0.4

0.6

0.8

1.0

predawn water potentialsoil water potential

Water Retention Curve Provides a Good Transfer Function with Pre-Dawn Water Potential

Baldocchi et al. 2004 AgForMet

Day

0 50 100 150 200 250 300 350

Eflo

or/

Eca

no

py

0.0

0.2

0.4

0.6

0.8

1.0

2002Oak Savanna

Understory Latent Heat Exchange Can be a Large Fraction of Total Evaporation:

Baldocchi et al. 2004 AgForMet

Ponderosa pineforest floor

Time (Hour)

0 4 8 12 16 20 24

en

erg

y f

lux d

en

sit

y (

W m

-2)

-50

0

50

100

150

200

250

300

E

H

Rn

Gsoil

Jack pineForest FloorD144-259

Time (hours)

0 4 8 12 16 20 24

En

erg

y F

lux D

en

sit

y (

W m

-2)

-25

0

25

50

75

100

125

Rn

E

H

G

Figure 11

dienjkpp.spw

12/8/99

Overstorey Latent Heat Exchange Partitioning:Homogeneous vs Patchy Pine Forests

Baldocchi et al. 2000 AgForMet

Rn -G: forest floor (W m-2)

-50 0 50 100 150 200

E f

ore

st f

loo

r (W

m-2

)

-10

0

10

20

30

40

50

60

70

ponderosa pine forest

jack pine forest temperate deciduousforest

LE is a Non-Linear Function of Available Energy

Baldocchi et al. 2000 AgForMet

Why Does Understory LE Max out at about 20-30 W m-2 in closed canopies?

( )dE dE t dD

dt dD dt

( ) exp( )[ (0) ]s t s

E t A E As s

t/

0 1 2 3 4 5

E(t

)0

10

20

30

40

50 sA

s Consider Evaporation into the Canopy Volume and feedbacks with vapor pressure deficit, D

8300 8400 8500 8600 8700 8800 8900 9000

14

14.5

15

15.5

16

16.5

T (

C)

Periodic and Coherent Eddies Sweep through the Canopy Frequently, and Prevent Equilibrium Conditions from Being

Reached

t, 10 Hz

Timescale for Equilibrium Evaporation (~1000s) >> Turbulence Timescales (~200s)

Timescale for Evaporation under a Forest

Ga (m s-1)

0.0001 0.001 0.01 0.1 1 10 100

10

100

1000

10000

100000

Gs = 0.001 m s-1 Gs = 0.01 Gs = 0.1

( ( / ))

( )av s

av

h s G G

G s

Modeling Soil Evaporation

4(1 )n g sR R L T E H G

Albedo

LEH

Gsoil

FCO2

Ponderosa PineForest FloorD187-205, 1996

Rn

et (

W m

-2)

-50

0

50

100

150

200

250

300

measured

calculated

E (

W m

-2)

-25

0

25

50

75

H (

W m

-2 )

0

50

100

150

200

Time (hours)

0 4 8 12 16 20 24

G (

W m

-2)

-75-50-25

0255075

100125150

Figure 15

enbmod.spw

12/8/99: laieff=1.8, zlitter=0.08

Below Canopy Energy Fluxes enable Us to Test Model Calculations of Soil Energy

Exchange

Baldocchi et al. 2000 AgForMet

R

zzk ua

(ln( ))( )0

2

2 1

52

gz T T

T us a

a

( )

Lessons Learned:1. Convective/Buoyant Transport Has a Major Impact on Understory

Aerodynamic Resistances

Daamen and Simmons Model (1996)

a sfca p

a

T TH C

R

Rn

(W

m-2 )

-500

50100150200250300

E (

W m

-2 )

010203040506070

Ra=f(stability)

Ra: neutral

H (

W m

-2 )

0255075

100125150

Time (hours)

0 4 8 12 16 20 24

G (

W m

-2 )

-50

0

50

100

150

200

Ponderos PineForest Floor

Figure 16

enmodstb.spw

12/8/99

Ignoring Impact of Thermal Stratification Produces Errors in H AND Rn, LE, & G

Baldocchi et al. 2000 AgForMet

Sandy Soils Contain More Organic Content than May be Visible

Metolius, OR, sand and Ponderosa Pine

Thermal Diffusivity (mm2 s-1)

0.0 0.1 0.2 0.3 0.4 0.5 0.6

de

pth

(m

)

0.01

0.1

1

Rn

(W

m-2 )

-500

50100150200250300

E (

W m

-2 )

0102030405060

Litter depth, 0.01 mlitter depth, 0.02 m

H (

W m

-2 )

0255075

100125150

Time (hours)

0 4 8 12 16 20 24

G (

W m

-2 )

-50

0

50

100

150

Ponderos PineForest Floor

Figure 17

enmodlit.spw

12/8/99

litter depth, 0.05 m

Litter Depth affects Thermal Diffusivity and Energy Fluxes

Baldocchi et al. 2000 AgForMet

Summary• Temperature and Soil Respiration

– Vertical Gradients, Lags and Phase Shift– Hysteresis, a need to match depth of production with temperature

• Photosynthesis and Soil Respiration– Photosynthesis Controls Soil Respiration– But, Lags occur between Soil Respiration and Photosynthesis

• Soil Evaporation & Moisture– Turbulence Sweeps and Ejections Regulate Soil ET– Modeling Soil Energy Exchange requires information on Convection– Spatial scaling of Soil Moisture

• Pre-dawn water potential and root weighted soil moisture– Soil Moisture and ET

• Soil Respiration & Rain and Sun– Stimulation of Respiration by Rain– Proves Photodegradation is assisting grassland Decomposition

• Alternative/’novel’ Measurement Methods– Better Experimental Design for Soil Respiration– Understory Eddy Covariance, an alternative to Chambers– Soil CO2 probes & Fickian Diffusion– Improved Incubation Protocols

Acknowledgments

• Support: US DOE

• Collaborators: Liukang Xu, Siyan Ma, Jianwu Tang, Jorge Curiel-Yuste, Xingyuan Chen, Tilden Meyers, Bev Law, Ted Hehn, Susanna Rutledge

volumetric soil moisture @ 10 cm (cm3 cm-3)

0.0 0.1 0.2 0.3 0.4 0.5

ther

mal

diff

usiv

ity (

W m

-1 K

-1)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Vaira grassland, 2002Verhoef method2 to 16 cm

LNM

OQP2

2 1

1 2

2z z

A Aln( /

Below Canopy Fluxes and Canopy Structure and Function

LAI * Vcmax

0 20 40 60 80 100 120 140 160 180 200

QE

,so

il/QE

0.00

0.05

0.10

0.15

0.20

0.25

0.30

Soil CO2 Diffusion Model

Source flux: 3 mol m-2

s-1

lower boundary condition, dc/dz=0soil moisture: 0.20

[CO2], ppm

0 2000 4000 6000 8000 10000

-Dep

th, m

0.01

0.1

1

10

1 hour24 hr48 hour96 hour192 hours 384 hours 768 hours 1536 hours 3072 hours

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

evaporation

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

Rec

o (g

C m

-2d-1

)

0

2

4

6

8

10

0 2 4 6 8 10 12 140

1

2

3d214 2003 understory

(, 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 ²=0.98

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

teco

0 1 exp( )

Annual Grassland, 2003

0 100 200 300 400 500 600 700 800 900 1000-0.5

0

0.5

1

1.5

2

2.5

3

Rglobal

W m-2

FC

O2

mol

e m

-2 s

-1

soil CO2 flux-gradienteddy covariance