Genesis of the use of RothC to model soil organic carbon

Genesis of the use of RothC to model soil organic carbon

CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008

Outline

• Composition of soil organic carbon – isolating biologically important fractions

• Methodology for quantifying C allocation to fractions

• Why attempt to understand allocation to fractions?

• Modelling soil carbon with RothC

• Substitution of conceptual with measureable C pools in RothC

• MIR prediction of soil carbon fractions


Composition of soil organic matter

Extent of decomposition increases

Rate of decomposition decreases

C/N/P ratio decreases (become nutrient rich)

Dominated by charcoal with variable properties

• Crop residues on the soil surface (SPR)

• Buried crop residues (>2 mm) (BPR)

• Particulate organic matter (2 mm – 0.05 mm) (POC)

• Humus (<0.05 mm) (HumC)

• Resistant organic matter (ROC)


Biologically significant soil organic fractions

Humus(HumC)

Particulate material(POC)

Charcoal(ROC)


Quantifying SOC allocation of SOC to fractions

Recalcitrant Charcoal C

Humus + recalcitrant

HF treatment, UV-PO, & NMR

<53 µm fraction>53 µm fraction

Na saturate, disperse, sieve <53 µm

Total soil organic carbon

Density fractionation

Buried plant residue carbon

Soil sieved to <2mmSoil sieved to >2mm

Surface plant residue carbon

Quadrat collection

Particulateorganic carbon


Humus = <53µm - Recalcitrant


Variation in amount of C associated with soil organic fractions

0

5

10

15

20

25

Average for Hamilton (long term pasture)

Org

anic

car

bon

in 0

-10

cm la

yer

(Mg

C/h

a)

Surface plant residue C (SPR)

Buried plant residue C (BPR)

Particulate organic carbon (POC)

Humus C (HumC)

Recalcitrant C (ROC - charcoal)


Variation in amount of C associated with soil organic fractions

Pasture PastureCropped Mix Mix

0

5

10

15

20

25

30

1P 8P 32P

NoT

ill (M

edN

)

NoT

ill (H

ighN

)

Stra

t (M

edN

)

Stra

t (H

ighN

)

0P 11P

22P

Arb

oret

um

Per

m P

astu

re

W2P

F

Can

ola/

whe

at

Pul

se/w

heat

Pas

ture

/whe

at

Hamilton Hart Yass Urrbrae Waikerie

Org

anic

C in

0-1

0 cm

laye

r(M

g C

/ha)

SPRBPRPOCHumCROC

CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008Years

Soil

orga

nic

carb

on

(g C

kg-1

soi

l)

0

5

10

15

20

25

30

0 10 20 30 40 50 60 70

Total soil organic C

Conversion topermanent

pasture

33

Changes in total soil organic carbon with time

15 43

Initiate wheat/fallow

18 y 10 y

CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008Years

Soil

orga

nic

carb

on

(g C

kg-1

soi

l)

0

5

10

15

20

25

30

0 10 20 30 40 50 60 70

TOC

Conversion topermanent

pasture

33

Importance of allocating C to soil organic fractions

15 43

Humus C

ROCPOC


18 y 10 y

~30% less humus C

~800% more POC


Vulnerability of soil carbon content to variations in management practices

Years

Soil

orga

nic

carb

on

(g C

kg-1

soi

l)

0

5

10

15

20

25

30

0 10 20 30 40 50 60 70

TOC Humus

ROCPOC

Conversion to

wheat/fallow

18 y

Conversion to pasture

10 y

15 4333

9 y

52



Importance of quantifying allocation of C to soil organic fractions

Soi

l Org

anic

Car

bon

(g C

kg-1

soi

l)

Time

0

5

10

25

15

20

Soil 120 g SOC kg-1 soil

Soil 220 g SOC kg-1 soil

Time

0

5

10

25

15

20

Active C

Active CSoi

l Org

anic

Car

bon

(g C

kg-1

soi

l)Inert C

10 g Char-C kg-1soil

Inert C

2.5 g Char-C kg-1soil


Summary SOC fractions

RecalcitrantCharcoal C










Quadrat collection





RothC Model (Version 26.3)

DPM

RPM

PlantInputs

BIO

HUM

CO2Decomposition

DecompositionBIO

HUM

CO2

IOMFire

Decomposition

Original configuration – monthly time step


Roth C data requirements

• Monthly climate data: rainfall (mm), open pan evaporation (mm), average monthly air temperature (°C)

• Soil clay content (% soil OD mass)

• Soil cover (vegetated or bare)

• Monthly plant residue additions (t C ha-1)

• Decomposability of plant residue additions

• Monthly manure additions (t C ha-1)

• Soil depth (cm)

• Initial amount of C contained in each pool


RothC model structure – partitioning residue inputs into decomposable and resistant material

• All plant material entering the soil is partitioned into DPM and RPM via DPM/RPM ratio

Management DPM/RPMGrassland and most agricultural crops 1.44Unimproved grassland and scrub (savannas)

0.67

Deciduous and tropical woodlands 0.25


RothC model structure – amount of each type of carbon decomposed

• The amount of carbon associated with each pool that decomposes follows an exponential decay

0-Y Y 1 e abckt

a = the rate modifying factor for temperatureb = the plant retainment rate modifying factorc = the rate modifying factor for soil waterk = the annual decomposition rate constant for a type of carbont = 0.0833, since k is based on a yearly decomposition rate.

Values of k for each SOC fraction (y-1)

BioF BioS DPM RPM Hum0.66 0.66 10 0.15 0.02


RothC model structure – calculation of rate constant modifying factors

• Temperature modifying factor (a)

106

tm 18.3

47.9

1 e

a

• Plant retainment modifying factor (b)

b = 0.6 if soil is vegetatedb = 1.0 if soil is bare

tm= average monthly temperature01234567

-10 0 10 20 30 40

Monthly average temperature (°C)

Tem

pera

ture

mod

ifyin

g fa

ctor

(a)



• Soil water modifying factor – calculated based on top soil moisture deficit (TSMD)

Wat

er p

rese

nt in

the

soil

(mm

) Saturation

Dry

Lower Limit

Upper Limit

TSMDTotalporosity



• Calculation of maximum TSMD

2 depth in cmMaxTSMD covered (20.0 + 1.3 (%clay) - 0.01 (%clay) )23

5MaxTSMD bare MaxTSMD covered9

TSMD TSMD rain 0.75 PanEvapacc initial

• Calculation of accumulated TSMD over each time step

under the constraint that the accumulated TSMD can only vary between 0 and MaxTSMD



• Calculation of the rate modifying factor (c)

accMaxTSMD TSMD0.2 1.0 0.2MaxTSMD 0.444MaxTSMD

c

if TSMDacc < 0.444 MaxTSMD then c=1.0

otherwise,

1.0

0.2

c

0.444 MaxTSMD MaxTSMD


RothC model structure – amount of each type of carbon decomposed

• The amount of carbon associated with each pool that decomposes follows an exponential decay

0-Y Y 1 e abckt

a = the rate modifying factor for temperatureb = the plant retainment rate modifying factorc = the rate modifying factor for soil waterk = the annual decomposition rate constant for a type of carbont = 0.0833, since k is based on a yearly decomposition rate.

Values of k for each SOC fraction (y-1)

BioF BioS DPM RPM Hum0.66 0.66 10 0.15 0.02


RothC Model (Version 26.3)

DPM

RPM

PlantInputs

BIO

HUM

CO2Decomposition

DecompositionBIO

HUM

CO2

IOMFire

Decomposition


RothC model structure – partitioning of decomposition products

• Fraction decomposing organic matter that goes to CO2, humus and biomass

• Partitioning to CO2 is defined by clay content

2

0.0786 × %ClayCO1.67 1.85 1.6 e

Bio + Hum

0

1

2

3

4

5

6

7

0 50 100Clay content (% by mass)

CO 2

to (B

io+

Hum

) rat

io

Biomass + Humus partitioning46% Bio54% Hum


RothC output under constant inputs and climate – to define equilibrium SOC

0

20

40

60

80

100

120

0 100 200 300 400 500

Years since start of simulation

Am

ount

of s

oil o

rgan

ic c

arbo

n(M

g C

/ha

for 0

-30

cm la

yer)

TOC

DPM

RPM

HUM

IOM

BIOF

BIOS


Modelling the measurable

DPM

RPM

PlantInputs

BIO

HUM

CO2Decomposition

DecompositionBIO

HUM

CO2

IOMFire

DecompositionRPM = POCIOM = ROC (Charcoal C)HUM = TOC – (POC + ROC)


Requirements for calibration

Soil samples Representative composite soil samples collected at the beginning and end of a period >10 years to a soil depth of 30 cm.

Bulk density Measured at time of sampling using soil core weight/volume.

Crop yields Yield of grain and pasture over each year to be modelled and estimates of harvest index and root/shoot ratios

Management Details of individual crops, rotations, fallow periods, stubble burning and incorporation. If grazing occurred, estimates of consumption and return from animals.

Climate Details of average monthly air temperature, rainfall and pan evaporation


Model calibration and verification sites

0 350

Kilometres700

Verification Sites

Brigalow

Tarlee

Calibration Sites


Brigalow calibration site: influence of modifying RPM decomposition constant (k)

RPM k=0.30

0

10

20

30

40

50

60

70

1982 1987 1992 1997Year

Soil

C (M

g C

/ha)

RPM k=0.15

0

10

20

30

40

50

60

70

1982 1987 1992 1997Year

Soil

C (M

g C

/ha)

DPMRPM HUM IOM BIO Soil POCHUMCHARTOC


Tamworth – wheat/fallow

01020304050

1970 1980 1990 2000Year

Soil

C (t

/ha)

Wagga – wheat/pasture

0

20

40

60

1988 1990 1992 1994 1996 1998Year

Soil

C (t

/ha)

Salmon Gums – wheat/wheat

01020304050

1979 1983 1987 1991Year

Soil

C (t

/ha)

Salmon Gums - wheat/ 3 pasture

Year

Soil

C (t

/ha)

01020304050

1979 1983 1987 1991

DPMRPM HUM IOM

BIO Soil

Modeled

POCHUMCHAR

TOC

Measured

Model Verification: (sites with archived soil samples)


Model verification: (paired sites)

• Is this result due poor model performance or poor pairing of the sites?

• Did the sites start off similar or were there significant initial differences in soil/plant/environmental properties?

Kindon - pasture 15 y

0

10

20

30

40

50

Year

Soil

C (t

/ha)

1986 1991 1996 2001

Dunkerry South - crop

0

10

20

30

1967 1977 1987 1997

Year

Soil

C (t

/ha)

DPMRPM

HUM IOM

BIO Soil

ModeledPOCHUM

CHAR

TOC

Measured


Quantifying SOC allocation of SOC to fractions

RecalcitrantCharcoal C










Quadrat collection





Predicting total organic carbon and its allocation to SOC fractions using MIR

1

2

3

4

5000 4500 4000 3500 3000 2500 2000 1500 1000 500

Inte

nsity

Frequency (cm-1)

Fourier Transform Infrared Spectrum • Dependence on soil chemical properties

• Prediction of allocation of carbon to fractions via calibration and PLS


Prediction of total organic carbon (TOC)M

IR p

redi

cted

TO

C (g

C/k

g so

il)

Measured TOC (g C/kg soil)

Janik et al. 2007 Aust J Soil Res 45 73-81

177 Australian soils (all states) from varying depths within the 0-50 cm layer

n = 177Range: 0.8 – 62.0 g C/kgR2 = 0.94


Tasmanian soils project

y = 0.99x + 0.58R2 = 0.99

y = 0.35x + 15.95R2 = 0.86

0

50

100

150

200

250

0 50 100 150 200 250LECO measured C (g/kg)

MIR

pre

dict

ed L

ECO

C (g

/kg) Sample specific calibration

Genericcalibration


MIR prediction of particulate organic carbonM

IR p

redi

cted

PO

C (g

C/k

g so

il)

Measured POC (g C/kg soil)



n = 141Range: 0.2 – 16.8 g C/kgR2 = 0.71

Variability in crop residue type exits


MIR prediction of charcoal CM

IR p

redi

cted

Cha

r C (g

/kg)

Measured Char C (g/kg)



n = 121Range: 0.0 – 11.3 g C/kgR2 = 0.86


Summary

• Methodologies exist to quantify biologically significant pools of carbon

• Understanding the dynamics of the pools allows accurate interpretation of potential changes

• Substitution of measureable fractions for conceptual pools in models is possible

• Rapid methods for predicting soil carbon allocation to pools exist

Thank you

CSIRO Land and WaterJeff BaldockResearch ScientistPhone: +61 8 8303 8537Email: [email protected]: http://www.clw.csiro.au/staff/BaldockJ/

AcknowledgementsJan Skjemstad, Kris Broos, Evelyn Krull, Ryan Farquharson, Steve Szarvas, Leonie Spouncer, Athina Massis

Contact UsPhone: 1300 363 400 or +61 3 9545 2176

Email: [email protected] Web: www.csiro.au

http://www.clw.csiro.au/staff/BaldockJ/


Model Calibration

Brigalow South ws64 (RPM 0.15)

1982 1987 1992 1997Year

0

10

20

30

40

50

60

70

0-30

cm

Soi

l C (t

/ha)

DPMRPM HUM IOM

BIO Soil

Modeled

POCHUMCHAR

TOC

Measured


Defining soil C dynamics at Roseworthy, SA under continuous wheat production

Average growing season (Apr-Oct) rainfall (mm) 338

Water limited potential grain yield (Mg/ha) 4.56

Grain yield used (Mg/ha) (85% water use efficiency) 3.88Harvest index (Mg grain/Mg dry matter) 0.45Total shoot dry matter production (Mg/ha) 8.62

Soil clay content(%)

Amount of C in 0-30cm layer (Mg C/ha)

C content of 0-10 cm layer (%)

5 65 2.3215 78 2.7930 93 3.32

Equilibrium conditions (model for 500 years)


Changes in soil C for different levels of average grain yield

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

0 100 200 300 400 500


Soil

orga

nic

C (0

-10

cm la

yer)

(% o

f tot

al s

oil m

ass) 0.5 T/ha

1 T/ha2 T/ha3 T/ha4 T/ha6 T/ha8 T/ha10 T/ha


Changes in soil C for different levels of average grain yield

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

0 5 10 15 20


Soil

orga

nic

C (0

-10

cm la

yer)

(% o

f tot

al s

oil m

ass) 0.5 T/ha

1 T/ha2 T/ha3 T/ha4 T/ha6 T/ha8 T/ha10 T/ha

Shift yield from 4 to 8 T grain/ha = 1.0 %C increase over 20 yearsShift yield from 4 to 6 T grain/ha = 0.4 %C increase over 20 years


Composition of methodologically defined SOC fractions

Particulate organic carbon (POC)• Fragments of plant residues >53 µm (living and dead) • Molecules sorbed to mineral particles >53 µm• Large pieces of charcoal

Humus (HUM-C)• Fragments <53 µm• Molecules sorbed to particles <53 µm

Recalcitrant (ROC)• Materials <53 µm that survive photo-oxidation• Dominated by material with a charcoal-like chemical structure• NMR to quantify char-C


Spatial variation in soil charcoal and carbon contents (0-10 cm layer)

0.00

0.40

0.80

1.20

1.60

2.00

2.40

0 25 50 75 100Western Boundary (m)

TOC

0

20

40

60

80

100

120

140

160

180

200

Nor

ther

n Bo

unda

ry (m

)

0 1 1 12 2 23 3 3

4 4 45 5 56 6 67 7 78 8 89 9 9

10 10 1011 11 11

12 12 1213 13 1314 14 1415 15 1516 16 1617 17 17

19 19 1920 20 2021 21 2122 22 2223 23 2324 24 2425 25 25

26 26 2627 27 27

29 29 2930 30 3031 31 31

32 32 3233 33 33

34 34 3435 35 35

18 18 18

35 3534333231302928272625242322212019181716151413121110987654321 0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0 25 50 75 100Western Boundary (m)

Inert OC

0

20

40

60

80

100

120

140

160

180

200

Nor

ther

n Bo

unda

ry (m

)

0 1 1 12 2 23 3 34 4 45 5 56 6 67 7 78 8 89 9 9

10 10 10

11 11 1112 12 1213 13 1314 14 1415 15 1516 16 1617 17 17

19 19 1920 20 2021 21 2122 22 2223 23 2324 24 24

25 25 2526 26 2627 27 27

29 29 2930 30 3031 31 3132 32 3233 33 3334 34 34

35 35 35

18 18 18

35 W FW FP P F WP P F WP P F WP P F WPerm. Past.Contour bankW O O(g) FW O O(g) FW O O(g) FW O O(g) FB Pe WB Pe WB Pe WW P P W P P W P P W WW W P P P P PW W P P P P PW W P P P P PW W P P P P PW W P P P P PW W P P P P PW O FW O FW O FW O(g) FW O(g) FW O(g) FW PeW PePerm. PastPerm. Past


Predicting soil organic carbon contents

• Clearing of Brigalow bushland

0

10

20

30

40

50

60

70

1982 1987 1992 1997Year

C (t

/ha)

RPM

HUM

IOM

TOC

TOC

HUMCHAR

POC

Measured fractions

Modelled fractions

0

10

20

30

40

50

60

70

1982 1987 1992 1997Year

C (t

/ha)

RPM

HUM

IOM

TOC

RPM RPM

HUM HUM

IOM IOM

TOCTOC

TOC

HUMCHAR

POCTOCTOC

HUMHUMCHARCHAR

POCPOC

Measured fractions

Modelled fractions


Options for increasing soil carbon content

• Principal: increase inputs of carbon to the soil• Maximise capture of CO2 by photosynthesis and addition of

carbon to soil

• Options• Maximise water use efficiency (kg total dry matter/mm water)• Maximise stubble retention• Introduction of perennial vegetation • Alternative crops - lower harvest index• Alternative pasture species – increased below ground allocation• Addition of offsite organic materials – diversion of waste streams• Green manure crops – legume based for N supply


Options for increasing soil carbon content

• Constraints• Soil type – protection and storage of carbon• Local environmental conditions

– Dryland conditions – amount and distribution of rainfall– Irrigation – maximise water use efficiency

• Economic considerations – alterations to existing systems must remain profitable

• Social

• Options need to be tailored to local conditions and farm business situation


Defining inputs of organic carbon to soil – dryland conditions

• Availability of water – amount and distribution of rainfall imposes constraints on productivity and optionsBeverly, WA

0

15

30

45

60

75

90

Jan

Mar

May Ju

l

Sep Nov

Month of the year

Ave

rage

mon

thly

rain

fall

(mm

)

0

50

100

150

200

250

300

Rain (mm)

Pan Evaporation (mm)

Roseworthy, SA

0

15

30

45

60

75

90

Jan

Mar

May Ju

l

Sep Nov

Month of the year

0

50

100

150

200

250

300

Rain (mm)


Mudgee, NSW

0

15

30

45

60

75

90

Jan

Mar

May Ju

l

Sep Nov

Month of the year

0

50

100

150

200

250

300

Ave

rage

mon

thly

pan

eva

pora

tion

(mm

)

Rain (mm)



Evaluating potential C sequestration in soilS

oil c

arbo

n se

ques

tratio

n si

tuat

ion

Stable soil organic carbon (e.g. t1/2 10 years)

Attainablesequestration

SOCattainable

RainfallTemperatureLight

Limitingfactors

Potential sequestration

SOCpotential

Reactive surfacesDepthBulk density

Definingfactors

Actualsequestration

SOCactual

Soil managementPlant species/crop selectionResidue managementSoil and nutrient lossesInefficient water and nutrient useDisrupted biology/disease

Reducingfactors

Optimise input and reduce losses

Add external sources of carbon


$$ for C sequestration – fact or fiction

• There is no doubt that soils could hold more carbon• Challenge – increase soil C while maintaining economic

viability• Options

• Perennial vegetation• Regions with summer rainfall• Portions of paddocks that give negative returns

• Reduce stocking, rotational grazing, green manure• Optimise farm management to achieve 100% of water limited

potential yield• External sources of carbon

• Under current C trading prices• Difficult to justify managing for soil C on the basis of C trading

alone• Do it for all the other benefits enhanced soil carbon gives


Climate dataClimate data

Crop growth

Incorporation into a decision support framework

MIR Analysis

SOC fractions Clay Soil water limits

Soil C model with N and P dynamics

C sequestration in soils in response to management

Soil fertility and fertiliser addition rate calculators


CO2

Plant production

Photosynthesis

Death/Harvest

Plant residues

Mineralisation

Soil animals and microbes

Recalcitrant organic C

(ROC)

Burning

Options for sequestering carbon

Particulate organic C

Humus organic C

Increasing extent of

decomposition

Carbon sequestration options1) increase C stored in plants – e.g. grow a forest

3) increase C stored in one or all soil components2) move more carbon into the recalcitrant pool


What determines soil organic carbon content?

Soil organic carboncontent

Inputs oforganic carbon

Losses oforganic carbon= ,f

Inputs• Net primary

productivity

• Addition of waste organic materials

Losses• Conversion of

organic C to CO2 by decomposition


Years

Soil

orga

nic

carb

on

(g C

kg-1

soi

l)

0

5

10

15

20

25

30

0 20 40 60 80 100 120 140

Balance between inputs and outputs

Inputs > Outputs

Inputs >> Outputs

Inputs < Outputs

Inputs << Outputs

Inputs = Outputs


Understanding the residue input requirements to change soil carbon content

0

10

20

30

40

50

60

70

80

90

0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7

Bulk density(g/cm3)

Am

ount

of c

arbo

n in

the

0-10

cm

laye

r(M

g C

/ ha) 1% SOC

2% SOC3% SOC4% SOC5% SOC

24

48

Amount of C required: 24 Mg C 50 Mg Dry Matter (DM)

Rate per year (no losses): 10 Mg DM/y 50% allocation below ground equates to 5 Mg shoot DM/y Rate per year (with 50% loss) 20 Mg DM/y (50% loss) 50% allocation below ground 10 Mg shoot DM/y


Nutrients associated with soil carbon

Assumptions: C/N =10 and C/P=120)

0

200

400

600

800

1000

1200

1400

1600

1800

0.0 0.2 0.4 0.6 0.8 1.0

Change in soil carbon(% of soil mass)

Am

ount

of N

(kg

/ha)

BD = 1.0

BD = 1.2

BD = 1.4

BD = 1.6

0

20

40

60

80

100

120

140

0.0 0.2 0.4 0.6 0.8 1.0


Am

ount

of P

(kg

/ha)

BD = 1.0

BD = 1.2

BD = 1.4

BD = 1.6



Variation in C/N ratio of different fractions of soil organic matter

0

20

40

60

80

100

120

SPR BPR POM HumusType of organic matter

C/N

ratio

(wei

ght b

asis

)

Upper boundryLower boundry


Minimum requirements for tracking soil organic carbon for accounting purposes

1. Collection of a representative soil sample to a minimum depth of 30 cm

2. An accurate estimate of the bulk density of the sample

3. An accurate measure of the organic carbon content of a soil sample

For 0-30 cm soil with a bulk density of 1.0 Mg/m3 and a carbon content of 1.0%

=Mass ofCarbon

(Mg C/ha)

Depth(cm)

30 Mg C/haxBulk

density(g/cm3)

xCarboncontent

(%)=


Dynamic nature of SOC and its fractions

0

8

16

24

32

1/6/98 6/2/99 14/10/99 20/6/00 25/2/01

Date of sample collection

Am

ount

of o

rgan

ic C

(M

g C

ha-1

in 0

-10

cm) POC Humus ROCTOC

Irrigated Kikuyu pasture – Waite rotation trial


Dynamic nature of SOC and its fractions

Date of sample collection

Am

ount

of o

rgan

ic C

(M

g C

ha-1

in 0

-10

cm)

048

12162024283236

1/6/98 6/2/99 14/10/99 20/6/00 25/2/01

TOC POC Humus ROC

Dryland Pasture/Wheat/Wheat – Waite rotation trial


New 30 cm depth

Soil bulk density (Mg/m3) 1.1 1.2 1.3 1.4

Management induced compaction

Correcting soil carbon for management induced changes in bulk density

Original soil surface

Original 30 cm depth

Mass Soil 0-30 cm (Mg/ha) 3300 3600 3900 4200

Depth for equivalent mass (cm) 30.0 27.5 25.4 23.6

Organic C loading (Mg/ha)

1% OC, no BD correction 33 36 39 42

1% OC, with BD correction 33 33 33 33


Predicted equilibrium soil organic C contents for 3 regions in SA with different climate type

Clare Roseworthy Waikerie

Growing season rain (mm) 491 338 170

Water limited potential grain yield (T/ha) 6.2 4.6 1.8

Grain yield (T/ha) (85% WUE) 5.3 3.9 1.5

Total shoot dry matter (T/ha) 11.7 8.6 3.4

Equilibrium soil carbon content

Modelled amount of C in 0-30 cm (t C/ha) 98 78 41

Estimated %C in 0-10 cm soil layer 3.5 2.8 1.5


Take home messages

• Organic matter (carbon + other elements) is composed of a variety of materials and improves soil productivity

• Different soils can hold different amounts of carbon• Nature of soil minerals, depth and bulk density• Balance between inputs and losses – goal is to maximise

production per mm available water

• Measuring changes in soil carbon requires careful consideration

• Options to increase carbon must be tailored to the local conditions and economic considerations of the farmer

• Computer models exist to predict the impact of management on soil carbon



• Objective: Prediction of total organic carbon

• Samples• 154 soils collected from 0-10

cm layer of a diverse set of soil x management combinations

• 30 measured values used to derive the calibration

• All other samples predicted from this calibration

• Range of Walkley-black C contents

• 3.7 – 99.9 g C/kg soil

y = 0.60x + 25.90R2 = 0.37

-20

0

20

40

60

80

100

0 50 100 150

Measured carbon content (g/kg)

MIR

pre

dict

ed c

arbo

n co

nten

t (g/

kg)



y = 0.99x + 0.58R2 = 0.99

0

50

100

150

200

250

0 100 200 300

Measured LECO C (g/kg)

MIR

pre

dict

ed L

ECO

(g/k

g)

y = 0.43x + 12.83R2 = 0.61

0

20

40

60

80

100

120

0 100 200 300

Measured LECO C (g/kg)

Mea

sure

d W

alkl

ey-B

lack

C (g

/kg)


Functions of organic matter in soil

Biological functions- energy for biological processes

- reservoir of nutrients

- contributes to resilience

- cation exchange capacity

- buffers changes in pH

- complexes cations

Chemical functionsPhysical functions- improves structural stability

- influences water retention

- alters soil thermal properties

Functions of SOM


Distribution and turnover of organic carbon in soil

0 cm

10 cm

30 cm

100 cm

SOCcontent

High

Low

Verylow

Proportion ofprofile SOC

30-50%

20-30%

10-30%

Relativeresponse time

Rapid

Intermediateto slow

Slow


Variation in soil organic carbon with depth for different soils

0 1 0 1 0 1 0 1 2 3 0 2 4 6

Greyclays

Redbrownearths

Redearths KrasnozemsBlack

earths

0

50

100

150

200

Soi

l Dep

th (c

m)

Soil organic carbon content (% by weight)

2


Significance of carbon in soils

Annual fluxes (1015 g C/yr)Emissions• Fossil fuel burning 6• Land use change 2

Responses• Atmospheric increase 3• Oceanic uptake 2• Other 3

World wide C pools (1015 g C)• Atmosphere (CO2 C) 780• Living Biomass (plants, animals) 550• Soil

0-1 m depth 15000-3 m depth 2300

Houghton (2005)

1330


Potential for soils to sequester C

0 cm

10 cm

30 cm

100 cm

Potential does exist to sequester C in soil• SOC pool size: 1500 Pg• Rapid cycling SOC: 500-750 Pg• 1% increase in stored SOC/yr: 5 - 7.5 Pg/yr

• CO2-C emissions: 8 Pg/yr

Issues• Permanency of increase• Native unmanaged soils• Constraints on C inputs (biophysical,

economic, social)


Take home messages

• Soil organic matter provides many benefits to soil

• Different soils can hold different amounts of carbon

• Soil carbon represents the balance between additions and losses

• Soil carbon is composed of a variety of materials

• Understanding soil carbon composition allows more accurate assessment of management impacts

• Measuring changes in soil carbon requires careful consideration

• Computer models exist to predict the impact of management on soil carbon

• Options to improve soil carbon and productivity need to be tailored to local conditions


Understanding the residue input requirements to change soil carbon content

0

10

20

30

40

50

60

70

80

90

0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7

Bulk density(g/cm3)

Am

ount

of c

arbo

n in

the

0-10

cm

laye

r(M

g C

/ ha) 1% SOC

2% SOC3% SOC4% SOC5% SOC

Amount of C required: 14 Mg C 28 Mg Dry Matter (DM)

Rate per year (no losses): 5.6 Mg DM/y 50% allocation below ground 2.8 Mg shoot DM/y Rate per year (with 50% loss) 11.2 Mg DM/y (50% loss) 50% allocation below ground 5.6 Mg shoot DM/y

14

28


Soil organic carbon content: influence of management

• Defining the influence of management practices on soil organic carbon is difficult

• Different types of organic C respond at different rates• POC - years to decades• Humus – decades to centuries• Charcoal – centuries to millennia

• Other factors may be more influential in some years than management (e.g. rainfall)

• Spatial variability and within year temporal variability

• Use of computer simulation models offers a way to estimate likely outcomes quickly

• example soil carbon model: RothC


Changes in soil C for different climates at a constant wheat grain yield

Average grain yield of 4 T/ha

0.0

1.0

2.0

3.0

4.0

0 100 200 300 400 500


Soil

orga

nic

C (0

-10

cm la

yer)

(% o

f tot

al s

oil m

ass)

ClareRoseworthyWaikerie


Nutrients associated with soil carbon

Assumptions: C/N =10 and C/P=120)

0

200

400

600

800

1000

1200

1400

1600

1800

0.0 0.2 0.4 0.6 0.8 1.0


Am

ount

of N

(kg

/ha)

BD = 1.0

BD = 1.2

BD = 1.4

BD = 1.6

0

20

40

60

80

100

120

140

0.0 0.2 0.4 0.6 0.8 1.0


Am

ount

of P

(kg

/ha)

BD = 1.0

BD = 1.2

BD = 1.4

BD = 1.6



•Annual fluxes (1015 g C/yr)•Emissions• Fossil fuel burning 6• Land use change 2

•Responses• Atmospheric increase 3• Oceanic uptake 2• Other 3

•World wide C pools (1015 g C)• Atmosphere (CO2 C) 780• Living Biomass (plants, animals) 550• Soil

0-1 m depth 15000-3 m depth 2300

Houghton (2005)

1330


Chemical function: Cation exchange capacity

0

100

200

300

400

500

600

4 5 6 7 8 9

Soil pH

Cat

ion

exch

ange

cap

acity

(meq

/100

g C

)

POMHumusRecalitrant


Questions remaining – from an organic matter perspective

• What is the capacity of soils to store organic matter (carbon and nutrients)?

• How much of the carbon and nutrients stored in soil organic matter can be made available to microbes and plants?

• What are the potential effects of alternative and new management options on organic matter levels?

• Further quantification of the role of soil organic fractions is required to extend the range of soil types and environments examined.

• What is the role of external sources of organic matter and do their influences persist?



•World wide C pools (1015 g C)• Soil 1500• Atmosphere (CO2) 720• Living Biomass (plants, animals) 560

Soil in Australia 30

World fluxes (1015 g C/year)FossilFuel

5

OceanUptake

1.6

VegetationDestruction

1.8

AtmosphericIncrease

3

MissingSink2.2

+ = + +

0.1% increase in soil organic C = 1.5


Adding charcoal to soil : the Terra Preta phenomenon

• High soil organic carbon – significant charcoal• High P contents – 200–400 mg P/kg• Higher cation exchange capacity• Higher pH and base saturation

TerraPreta Oxisol

Documents

Genesis of the use of RothC to model soil organic carbon