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Soil Carbon Modelling

Budiman Minasny Alex McBratney Jose Padarian

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Background – Why the interest in soil carbon?

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Soil carbon

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Why Soil Carbon ‘Gold Rush’?

Soil C pool Organic C 1550 Pg Inorganic C 950 Pg

Atmospheric pool 760Pg

Biotic pool 610 Pg

Source: Lal (2006)

1 Pg = 1015 g = 1 billion ton

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Paris Climate Change Conference

–  Soil Carbon 4 per mille

8.9

2400=  4‰2400

Organic  carbon  stored  in  the  soil  globally

(up  to  2  m)

Amount  of  C  stock  increaseneeded  tooffset  CO2emission

8.9

GlobalCO2 emissions  from  fossil  fuels

billion  tonne  C

billion    tonne  C

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Soil C 4 per mille

Agricultural practices that can sequester soil carbon

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Soil C 4 per mille

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–  The need for better and more cost effective measurement of soil C –  Auditing SOC –  Modelling SOC –  Monitoring SOC

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Empirical models

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Climate

Soil observations

DTM DEM

Remote Sensed Images

Existing Soil maps

scorpan layers Organic C: 0-5 cm

C = f(s,c,o,r,p,a,n) Spatial Soil

Prediction Functions

C stock Organic C: 5-15 cm

Organic C: 15-30 cm Organic C: 30-60 cm

Digital soil mapping

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Digital soil mapping

9

0

40

0

Prediction Prediction variance

0 31.5 km

C stock

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Sampling Design for Soil C Auditing

De Gruijter et al., 2016. Farm Scale Soil C Auditing. Geoderma.

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Semi Empirical/Mechanistic models

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Global Soil C Assessment

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Global Soil C Assessment

–  Models based on land cover change

–  dC/dt = A – k. C

15

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16

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Process-based models

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Struc-C

•  There are influences and feedbacks between Soil Organic Carbon and soil structure

(e.g. Edwards and Bremner, 1967; Field, 2000; Kleber et al, 2007; Six et al., 2004) •  Soil structure is rarely considered in soil carbon

models

◊ How does SOC influence the soil aggregation? ◊ Building a better structure (model)

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FOM input Per month

RPM

DPM

CO2

CO2

AC 1

CO2 CO2

NCOC

AC 2

AC 3

CO2

CO2

BIO

HUM BIO

HUM

IOM

CO2

CO2

Decay

Decay

Decay

FOM input Per month

RPM

DPM

Coleman and Jenkinson, 1999

RothC

Struc-C

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Aggregation

–  The smallest aggregates are composed of organo-mineral associations. Strong clay to SOC bonds

–  The clustering of these smaller aggregates forms larger aggregates, which in turn provides physical protection of the SOC between these aggregates from microbial attack.

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Type 3

Type 2

Type 1

Forest to plantation

Plantation to cropland

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100 200 300 400 500 6000

1

2

3

4

5

6

7

Years

SOC

(%) Type-3

Type-2

Type-1

NCOC

Tallgrass prairie Cropped Restored prairie

Simulation

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Years since restoration

0 5 10 15 20 25 30 35 40 45 502

3

4

5

6

7

8

9

10

Years

Tota

l OC

(%)

0 5 10 15 20 25 30 35 40 45 50

0.7

0.8

0.9

1

1.1

1.2

1.3

YearsBu

lk d

ensi

ty (g

/cm

3)

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0 5 10 15 20 25 30 35 40 45 500

10

20

30

40

50

60

Years

Aggregates(%)

0 5 10 15 20 25 30 35 40 45 500

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Years

C Ag

g(%

)Microaggregate C

Micro within macroaggregate C

Macroaggregate C

Microaggregate C

Micro within macroaggregate C

Macroaggregate C

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Other models

–  Carbon, aggregation, and structure turnover (CAST) , Stamati et al. 2013

AggModel, Segoli et al. 2013

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Struc-C Improvement

–  A better definition of Aggregate pools –  Reconciling measured & modelled aggregates –  Distribution with depth

FOM input Per month

RPM

DPM

CO2

CO2

Micro

CO2

NCOC

Macro

CO2

CO2

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Soil C Landscape model

–  3D Soil genesis model, millennial time scale –  C -> Simple 2 Compartment model, NPP production,

erosion, vertical mixing, productivity feedback

A quantitative model for integrating landscape evolution and soil formation T. Vanwalleghem, U. Stockmann, B. Minasny, A.B. McBratney. JGR

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Soil-landscape model

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Conclusions

–  4 per 1000: Soil C is relevant for mitigation of climate change –  To achieve 4 per mille Soil C initiative, we need to be able to

measure it with confidence, model the C change & monitor it. –  Soil C & structure still lacks a quantitative model. –  Opportunities for greater collaboration