Experiences in Linking Experiences in Linking a Soil C and N Module into a Soil C and N Module into

a Dynamic Global Vegetation a Dynamic Global Vegetation Model (DGVM)Model (DGVM)

Jo SmithJo Smith11, Kevin Coleman, Kevin Coleman22, Pete Smith, Pete Smith11

Andy WhitmoreAndy Whitmore22, Pete Falloon, Pete Falloon33

Matt AitkenheadMatt Aitkenhead11, Chris Jones, Chris Jones33

1 2 3

QuestionsQuestions What is the state of the art?What is the state of the art?

What data are required to improve and What data are required to improve and

evaluate the model? evaluate the model?

How could better science improve the model? How could better science improve the model?

What are the key feedbacks to be quantified? What are the key feedbacks to be quantified?

Are other feedbacks expected? Are other feedbacks expected?

What significant improvements in next 5 years? What significant improvements in next 5 years?

Energy supply

0

1

2

3

4

5

6

7GtCO2-eq

Transport Buildings Industry Agriculture Forestry Waste

Non-OECD/EI TEITOECDWorld total

US$/tCO2-eq

Global economic mitigation Global economic mitigation potential for different sectors at potential for different sectors at

different carbon pricesdifferent carbon prices

IPCC WGIII (2007)

Uncertainty inUncertainty inanthropogenic carbon anthropogenic carbon

emissionsemissions

up to 400 ppm

IPCC SRES 2000; Friedlingstein et al. 2006

Vulnerability of the Carbon Cycle Vulnerability of the Carbon Cycle in the 21in the 21stst century century

up to250 ppm

Uncertainty in Uncertainty in biospheric-carbon-biospheric-carbon-

climate climate feedbackfeedback

Slide adapted from Pep Canadell, GCP

ObjectivesObjectives Soil C and N component Soil C and N component

– Fully integratedFully integrated– Had-GEMHad-GEM

Existing modelExisting model– Tested and publishedTested and published– LiveLive– Adapted for general applicationAdapted for general application

Source code available to allSource code available to all– Programming styleProgramming style– ProvenenceProvenence

HadGEM2JULES

UK community land surface model

RothCModel of soil C

SUNDIALModel of soil C and N

- arable soils

ECOSSEModel of soil C and N

- all soil types &all land uses

MOSESSoil water

TRIFFIDPlant model

Soil Carbon Model –Soil Carbon Model –RothC RothC (Jenkinson, 1977)(Jenkinson, 1977)

DPM

RPM

CO2

BIO

HUM

CO2

BIO

HUM

Decomposable plant material

Resistant plant material

Active organic matter

Stabilised organic matter

IOM Inert organic matter

Evaluation of Roth-CEvaluation of Roth-CEG. Smith EG. Smith et alet al (1997) Geoderma, 81, 153-225 (1997) Geoderma, 81, 153-225

`

Bad Lauchstädt - arable No fertiliser

Bad Lauchstädt - arable High fertiliser

Praha-Ruznye - arableNo fertiliser

Praha-Ruznye - arableHigh fertiliser

Tamworth - fallow

Tamworth – clover/lucerne

Waite – wheat / fallow Waite – wheat/oats/pasture

Years

Soil

org

anic

carb

on (

t C

ha

-1)

Evaluation of Roth-CEvaluation of Roth-CEG. Smith EG. Smith et alet al (1997) Geoderma, 81, 153-225 (1997) Geoderma, 81, 153-225

Rothamsted – Park grassNo fertiliser

Calhoun forestryRothamsted – Park grassOrganic manure

Geescroft Wilderness

Years

Soil

org

anic

carb

on (

t C

ha

-1)

Evaluation of Roth-CEvaluation of Roth-CEG. Smith EG. Smith et alet al (1997) Geoderma, 81, 153-225 (1997) Geoderma, 81, 153-225

Comparison of Comparison of 9 major 9 major

soil organic matter soil organic matter modelsmodels

CENTU

RY

ROTH

CCA

NDY

DNDC

DAIS

YSO

MM

ITE

Ver

bern

eNCS

OIL

RMSE

RMSE95%

Evaluation of Roth-CEvaluation of Roth-CEG. Smith EG. Smith et alet al (1997) Geoderma, 81, 153-225 (1997) Geoderma, 81, 153-225

CENTU

RY

ROTH

CCA

NDY

DNDC

DAIS

YSO

MM

ITE

Ver

bern

eNCS

OIL

E

Comparison of Comparison of 9 major 9 major

soil organic matter soil organic matter modelsmodels

E95%

E95%

Evaluation of Roth-CEvaluation of Roth-CEG. Smith EG. Smith et alet al (1997) Geoderma, 81, 153-225 (1997) Geoderma, 81, 153-225

Comparison of Comparison of 9 major 9 major

soil organic matter soil organic matter modelsmodels

CENTU

RY

ROTH

CCA

NDY

DNDC

DAIS

YSO

MM

ITE

Ver

bern

eNCS

OIL

) t(r)

Application of Roth-CApplication of Roth-CSoft link to a DGVMSoft link to a DGVM

Soil C(ROTH-C)

Climate Data

HistoricalLPJ

-DGVMGCM

SoilsData

NPPData

EFISCENLPJ

-DGVM

Land UseData

ATEAMRounsevell

Corine database

TechnologyData

Ewert et al. 2005

Smith et al (2005) GCB, 11, 2141-2152Smith et al (2005) GCB, 11, 2141-2152

Scenarios for future climateScenarios for future climate(IPCC SRES)(IPCC SRES)

Global Local

Economically oriented

Environmentally oriented

A1 – “World Markets”

•very rapid economic growth•low population growth •rapid introduction of technology•personal wealth above environment

A2 – “Provincial Enterprise”

•strengthening regional cultural identities•emphasis on family values and local traditions•high population growth•less concern for rapid economic development

B1 – “Global Sustainability”•rapid change in economic structures•"dematerialization”•introduction of clean technologies•emphasis is on global solutions

B2 – “Local Stewardship”

•emphasis is on local solutions •less rapid, and more diverse technological change•strong emphasis on community initiative•local, rather than global solutions

Nakicenovic et al. (2000), Smith & Powlson (2003)

Climate-only impact on forest SOCClimate-only impact on forest SOC

75

80

85

90

95

100

1990

1997

2004

2011

2018

2025

2032

2039

2046

2053

2060

2067

2074

2081

2088

2095

Year

For

est S

OC

sto

ck (

t C h

a-1)

A1FI B1 B2 A2

(effect of different climate scenarios)(effect of different climate scenarios)

(HadCM3)

Climate-only impact on cropland and Climate-only impact on cropland and grassland SOC - grassland SOC - (effect of different climate scenarios)

75

80

85

90

95

10019

90

2000

2010

2020

2030

2040

2050

2060

2070

2080

Year

SOC

sto

ck (

t C h

a-1)

A1FI B1 B2 A2

Grassland

Cropland

(HadCM3)

Change in forest SOC – climate onlyChange in forest SOC – climate only

Note: 2080 and 1990 are 30 year averages of 2051-2080 and 1961-1990 respectively

Change in forest SOC- climate only

SOC

Temperature

Water balance

Change in grassland SOC – climate Change in grassland SOC – climate onlyonly

Change in cropland SOC – climate Change in cropland SOC – climate onlyonly

Application of Roth-CApplication of Roth-CSoft link to a DGVMSoft link to a DGVM

Soil C(ROTH-C)

Climate Data

HistoricalLPJ

-DGVMGCM

SoilsData

NPPData

EFISCENLPJ

-DGVM

Land UseData

ATEAMRounsevell

Corine database

TechnologyData

Ewert et al. 2005

Smith et al (2005) GCB, 11, 2141-2152Smith et al (2005) GCB, 11, 2141-2152

0

10

20

30

40

50

6020

01

2007

2013

2019

2025

2031

2037

2043

2049

2055

2061

2067

2073

2079

2085

2091

2097

Year

% c

han

ge

fro

m 2

000

fore

st li

tter

in

pu

t

Age class effect only A2 A1FI B1 B2

Change in forest litter inputs 2000-Change in forest litter inputs 2000-21002100

(HadCM3)

80

85

90

95

100

10519

90

1998

2006

2014

2022

2030

2038

2046

2054

2062

2070

2078

2086

2094

Year

For

est

SOC

sto

ck (

t C

ha-1

)

Climate & Litter Climate only

Comparing climate-only Comparing climate-only with climate & litter effects for forestwith climate & litter effects for forest

(HadCM3-A2)

70

75

80

85

90

95

100

105

110

1990 2000 2010 2020 2030 2040 2050 2060 2070 2080

Year

SOC

sto

ck (t

C h

a-1)

Cropland

Grassland

Comparing climate-only with Comparing climate-only with climate&NPP effects for croplands & climate&NPP effects for croplands &

grasslandsgrasslands (HadCM3-A2)

Climate Only Climate and NPP

Effect of technology Effect of technology in croplands & grasslandsin croplands & grasslands

(HadCM3-A2)

70

75

80

85

90

95

100

105

110

1990 2000 2010 2020 2030 2040 2050 2060 2070 2080

Year

SOC

sto

ck (

t C h

a-1

)

Cropland

Grassland

70

75

80

85

90

95

100

105

110

1990 2000 2010 2020 2030 2040 2050 2060 2070 2080

Year

SOC

sto

ck (t

C h

a-1

)

(HadCM3-A2)

Climate Only Climate & NPP Climate & NPP & TechMinimumMaximum

Application of Roth-CApplication of Roth-CSoft link to a DGVMSoft link to a DGVM

Soil C(ROTH-C)

Climate Data

HistoricalLPJ

-DGVMGCM

SoilsData

NPPData

EFISCENLPJ

-DGVM

Land UseData

ATEAMRounsevell

Corine database

TechnologyData

Ewert et al. 2005

Smith et al (2005) GCB, 11, 2141-2152Smith et al (2005) GCB, 11, 2141-2152

Impact on total forest SOCImpact on total forest SOC

16

17

18

19

20

21

2219

90

1997

2004

2011

2018

2025

2032

2039

2046

2053

2060

2067

2074

2081

2088

2095

Year

Tota

l SO

C (P

g)

A1FI A2 B1 B2

No land-use changeNo land-use change

16

17

18

19

20

21

2219

90

1997

2004

2011

2018

2025

2032

2039

2046

2053

2060

2067

2074

2081

2088

2095

Year

Tot

al S

OC

(P

g)

A1FI A2 B1 B2

Including land-use changeIncluding land-use change

Impact on total forest SOCImpact on total forest SOC

1

2

3

4

5

6

7

8

9

1990 2000 2010 2020 2030 2040 2050 2060 2070 2080

Year

Tot

al g

rass

land

SO

C (

Pg)

Including land-use change

No land-use change

Impact on total grassland SOCImpact on total grassland SOCIncluding land-use changeIncluding land-use change

A1FI A2 B1 B2

Impact on total cropland SOCImpact on total cropland SOCIncluding land-use changeIncluding land-use change

5

6

7

8

9

10

11

12

13

1990 2000 2010 2020 2030 2040 2050 2060 2070 2080

Year

Tot

al c

ropl

and

SO

C (

Pg)

No land-use change

Including land-use change

A1FI A2 B1 B2

Overall effect on forest SOC Overall effect on forest SOC • land-use changeland-use change• change in age-class structurechange in age-class structure• climate and COclimate and CO22 driven NPP increase driven NPP increase• direct climate impacts on the soildirect climate impacts on the soil

0.1-0.3

3.34.6

-10

-5

0

5

10

A1FI A2 B1 B2+0.1% -0.3% +27% +19%

Tota

l S

OC

(Pg

)

Overall effect on grassland SOC Overall effect on grassland SOC • land-use changeland-use change• technology improvementtechnology improvement• climate and COclimate and CO22 driven NPP increase driven NPP increase• direct climate impacts on the soildirect climate impacts on the soil

-2.2 -2.7

1.5

-1.2

-10

-5

0

5

10

A1FI A2 B1 B2-35% -44% -20% +25%

Tota

l S

OC

(Pg

)

Overall effect on cropland SOC Overall effect on cropland SOC

-5.9 -5.6-4.3 -4.3

-10

-5

0

5

10

A1FI A2 B1 B2-53% -51% -40% -39%

Tota

l S

OC

(Pg

)• land-use changeland-use change• change in age-class structurechange in age-class structure• technology improvementtechnology improvement• climate and COclimate and CO22 driven NPP increase driven NPP increase• direct climate impacts on the soildirect climate impacts on the soil

Overall effect on total SOCOverall effect on total SOC

-4.1 -4.4

-0.1 -0.9

-10

-5

0

5

10

A1FI A2 B1 B2 -23% -24% -5% -0.5%

Tota

l S

OC

(Pg

)• land-use changeland-use change• technology improvementtechnology improvement• climate and COclimate and CO22 driven NPP increase driven NPP increase• direct climate impacts on the soildirect climate impacts on the soil• includes biofuels and other land usesincludes biofuels and other land uses

Soil C(ROTH-C)

Climate Data

HistoricalLPJ

-DGVMGCM

SoilsData

NPPData

EFISCENLPJ

-DGVM

Land UseData

ATEAMRounsevell

Corine database

TechnologyData

Ewert et al. 2005

Smith et al (2005) GCB, 11, 2141-2152Smith et al (2005) GCB, 11, 2141-2152

FeedbacksFeedbacksPlant

Growth

CO2

CO2

Soil NN2

O

Soillevel

CO2 CO2

MoistureTextureTe

mpera

ture

DecompositionDrivers

WaterModule

Tem

pera

ture

Module

TextureModule

Decomposition

INPUTSYield &manage

DPMRPM

Carbon Componentof SUNDIAL BIO HUM IOM

INPUTSMax.Water

levelRain,PET

INPUTSAir Temp

INPUTSSoil

Parameters

Soil C and N model for arable Soil C and N model for arable landland - SUNDIAL- SUNDIAL

Bradbury et al, 1993Smith et al, 1996

MoistureTextureTe

mpera

ture

DecompositionDriversTe

mpera

ture

Module

TextureModule

Soillevel

INPUTSMax.Water

levelRain,PET

INPUTSAir Temp

INPUTSSoil

Parameters

Decomposition

RPM DPM

WaterModule

N2O

& N2

NH3INPUTSYield &

management

Nitrogen Componentof SUNDIAL

Soil C and N model for arable Soil C and N model for arable landland - SUNDIAL- SUNDIAL

Plant N

Leached N

NO3-

BIO HUM IOM

NH4+

Bradbury et al, 1993Smith et al, 1996

Evaluation of SUNDIALEvaluation of SUNDIAL

SUNDIAL

SUNDIAL MINERVARMSE 52 47t(M) 1.5 (n.s) -

Simulated and Observed Soil Mineral N (0-90 cm) Simulated and Observed Soil Mineral N (0-90 cm) Loam site (Krummbach) - Treatment Without Manure Loam site (Krummbach) - Treatment Without Manure

Evaluation of SUNDIALEvaluation of SUNDIAL

I mproved SUNDI AL Treatment Measure RMSE E

SOC 8.5 4.7 1 – 30 t FYM ha-1 2y-1 + NPK SON 9.0 -8.2

SOC 6.7 -1.3 2 – 30 t FYM ha-1 2y-1 SON 13.1 -13.0 SOC 9.9 4.6 5 – NPK only SON 7.9 -5.7 SOC 6.9 1.1 6 – nil inputs SON 14.3 -13.2

All non-significant

Simulated and Observed Soil Organic C and NSimulated and Observed Soil Organic C and NLoam site (Krummbach) Loam site (Krummbach)

Soillevel

CO2 CO2

MoistureTextureTe

mpera

ture

DecompositionDrivers

WaterModule

Decomposition

INPUTSYield &manage

DPMRPM

Carbon Componentof ECOSSE BIO HUM IOM

INPUTSMax.Water

levelRain,PET

INPUTSAir Temp

INPUTSSoil

Parameters

Soil C and N model for all land Soil C and N model for all land useuse - ECOSSE- ECOSSE

Waterlevel

Oxy

gen

Acidity

Acidity ModuleO

xygen

Mod

ule

Tem

pera

ture

Module

TextureModule

CH4 CH4

MethaneOxidation

Meth.Oxid.

DOC

INPUTSNPP &

LU Type

MoistureTextureTe

mpera

ture

DecompositionDrivers

TextureModule

Soillevel

INPUTSMax.Water

levelRain,PET

INPUTSAir Temp

INPUTSSoil

Parameters

Decomposition

RPM DPM

N2O

& N2

NH3

Nitrogen Componentof ECOSSE

Waterlevel

Soil C and N model for all land Soil C and N model for all land useuse - ECOSSE- ECOSSE INPUTS

NPP & LU Type

Acidity

Acidity Module

Oxy

gen

Mod

ule

Tem

pera

ture

Module

WaterModule

Plant N

BIONO3

-HUM IOM

NH4+

Leached N

DON

Soil with litter and fertiliser

0

10

20

30

40

50

60

70

Soilwith fertiliser

time (days)

0 50 100 150 200 250

Res

pira

tion

(mgC

O2-

C k

g-1

soil)

0

5

10

15

20

Soilwith litter

Soil only

0 50 100 150 200 250

measured simulatred

Respiration rate during laboratory incubation (Foereid et al., 2004)

Independent evaluation – CO2 release

Calculations by B. Foereid, UoACalculations by B. Foereid, UoA

Independent evaluation – soil ammonium and nitrate in a peat in Finland

2D Graph 1

time (weeks)

0 20 40 60 80 100 120 140 160

nitr

ogen

(kg

/ha)

0

20

40

60

80

100

120

simulated NO3-

simulated NH4+

measured NO3-

measured NH4+

fertiliser application

Ammonium and nitrate simulated by ECOSSE for a peat cultivated with spring barley in southern Finland (60o49’N, 23o30’E).

Calculations by B. Foereid, UoACalculations by B. Foereid, UoA

Soil NH4 in a peat cultivated with spring barley in Southern Finland (60o49’N, 23o30’E) (Regina et al, 2004).

Potatoes NH4

0

5

10

15

20

25

30

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101

106

111

116

121

126

131

136

141

146

151

156

161

166

171

176

181

Week

kg/h

a Measured

Modelled

Independent evaluation – soil ammonium in a cultivated peat in Finland

Calculations by M.Aitkenhead, UoACalculations by M.Aitkenhead, UoA

N2O emissions for a peat cultivated with spring barley in Southern Finland (60o49’N, 23o30’E) (Regina et al, 2004).

Barley N2O

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101

106

111

116

121

126

131

136

141

146

151

156

161

Week

kg/h

a Measured

Modelled

Independent evaluation – nitrous oxide emissions from a cultivated peat in Finland

Calculations by M.Aitkenhead, UoACalculations by M.Aitkenhead, UoA

Mass loss from litterbag experiment in Harvard forest, US (Magill & Aber, 1998)

Nitrogen content in remaining material from litterbag experiment in Harvard

forest, US (Magill & Aber, 1998)

Independent evaluation – Mass loss & N from litter bags – more to do

Calculations by B. Foereid, UoACalculations by B. Foereid, UoA

Red pine

0

20

40

60

80

100

120

in pinein hardwoodsimulated

Red maple

time (year)

88 89 90 91 92 93 94 95 96

% m

ass

re

ma

inin

g

0

20

40

60

80

100

Red pine

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

in pinein hardwoodsimulated

Red maple

time (year)

88 89 90 91 92 93 94 95 96

% n

itro

ge

n in

ma

teri

al

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

Nitrate in 50 cmNitrate in 50 cmImplementation of “birch effect”Implementation of “birch effect”

0

20

40

60

80

200 400 600 800 1000

timesteps in days

kg N

per

ha

Simulation

Field data

Growing season

Growing season

Data from Ikerra (1999)

RMS 10.95M -4.64r 0.59LOFIT No - Good

0

20

40

60

80

200 300 400 500 600 700 800 900 1000

timesteps in days

kg N

per

ha

Simulation

Field data

Ammonium in 50 cmAmmonium in 50 cmImplementation of “birch effect”Implementation of “birch effect”

Growing season

Growing season

Data from Ikerra (1999)

RMS 6.52M -3.62r 0.78LOFIT No - Good

Soil Water 0 – 50 cmSoil Water 0 – 50 cm

Data from Hartemink (2000)

Wate

r in

mm

0 – 15 cm

30 - 50 cm

15 - 30 cm

0

10

20

30

0

10

20

30

0

10

20

30

40

200 300 400 500 600 700

RMS 4.89M 2.86r 0.78LOFIT No - Good

RMS 5.22M 3.30r 0.70LOFIT No - Good

RMS 6.82M 4.21r 0.38LOFIT No - Good

Application of ECOSSEApplication of ECOSSE

National simulations…National simulations…

1.Test model at site scale

2.Compare to best current estimates at national scale

-60

-50

-40

-30

-20

-10

0

10

20

30

arab

le

gras

slan

d

fore

stry

sem

i-nat

arab

le

gras

slan

d

fore

stry

sem

i-nat

arab

le

gras

slan

d

fore

stry

sem

i-nat

arab

le

gras

slan

d

fore

stry

sem

i-nat

Cha

nge

in s

oil C

(kt

C (

20km

)-2 (

10yr

s)-1

ECOSSE CEH

to arable to grassland to forestry to semi-natural

R2 = 0.9666

-100

-80

-60

-40

-20

0

20

40

60

80

100

-100 -80

-60

-40

-20 0 20 40 60 80 100

CEH estimates of change in soil C (kt C (20km)-2 (10yrs)-1

EC

OS

SE

sim

ulat

ion

of c

hang

e in

soi

l C

(kt C

(20

km)-2 (

10yr

s)-1

1:1 Line

Application of ECOSSEApplication of ECOSSE

Scotland 2000-2009

National simulations compare well with the CEH inventory…National simulations compare well with the CEH inventory…

Scotland 2000-2009Scotland 2000-2009

TotalTotal Grassland -> ArableGrassland -> Arable Arable -> GrasslandArable -> Grassland

Application of ECOSSEApplication of ECOSSE

Soil C(ROTH-C)

Climate Data

Historical DGVMGCM

SoilsData

NPPData

EFISCENDGVM

Land UseData

ATEAMRounsevell

Corine database

TechnologyData

Ewert et al. 2005

FeedbacksFeedbacksPlant

Growth

CO2

CO2

Soil NN2

O

CO2

& CH4

Soil NN2

O

Soil C(ECOSSE)

HadGEM2JULES

UK community land surface model

State of the artState of the art

RothCModel of soil C

ourour

SUNDIALModel of soil C and N

- arable soils

ECOSSEModel of soil C and N

- all land uses

MOSESSoil water

TRIFFIDPlant model

MoistureTextureTe

mpera

ture

DecompositionDrivers

TextureModule

Soillevel

INPUTSMax.Water

levelRain,PET

INPUTSAir Temp

INPUTSSoil

Parameters

Decomposition

RPM DPM

N2O

& N2

NH3

Nitrogen Componentof Organic Soils Model Water

level

Soil C and N model for all land Soil C and N model for all land useuse - ECOSSE- ECOSSE

Acidity

Acidity Module

Oxy

gen

Mod

ule

Tem

pera

ture

Module

WaterModule

BIONO3

-HUM IOM

NH4+

Leached N

DON

INPUTSNPP &

LU Type

JULESSoil water

Plant N

JULESPlant model

Soil C(ECOSSE)

FeedbacksFeedbacks

CO2

& CH4

Soil NN2

O

Climate Data

Historical DGVMGCM

SoilsData

NPPData

EFISCENDGVM

Land UseData

ATEAMRounsevell

Corine database

TechnologyData

Ewert et al. 2005

PlantGrowth

CO2

Significant improvements Significant improvements over the next 5 years…over the next 5 years…

Nitrogen – a key feedbackNitrogen – a key feedback

Mangani et al (2007) Nature, 447:848-852Mangani et al (2007) Nature, 447:848-852

Significant improvements Significant improvements over the next 5 yearsover the next 5 years

Large scale runs including C and N Large scale runs including C and N feedbacksfeedbacks– on climateon climate– on plant growth (more in next talk?)on plant growth (more in next talk?)

Potential of agricultural Potential of agricultural management for global mitigationmanagement for global mitigation

-200

0

200

400

600

800

1000

1200

1400

1600

Cro

plan

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anag

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t

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er m

anag

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t

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e m

anag

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t

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e, L

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zing

land

man

agem

ent

Res

tore

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c so

ils

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deg

rade

dla

nds

Bio

ener

gy (

soils

com

pone

nt)

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esto

ck

Man

ure

man

agem

ent

Mitigation measure

Glo

bal b

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ysic

al m

itiga

tion

pote

ntia

l (M

t CO 2-

eq. y

r-1)

N2O

CH4

CO2

Smith et al. (2007)

Significant improvements Significant improvements over the next 5 yearsover the next 5 years

Large scale runs including C and N Large scale runs including C and N feedbacksfeedbacks– on climateon climate– on plant growth (more in next talk?)on plant growth (more in next talk?)

Impacts of land managementImpacts of land management

QuestionsQuestions What is the state of the art?What is the state of the art?

What data are required to improve and What data are required to improve and

evaluate the model? evaluate the model?

How could better science improve the model? How could better science improve the model?

What are the key feedbacks to be quantified? What are the key feedbacks to be quantified?

Are other feedbacks expected? Are other feedbacks expected?

What significant improvements in next 5 years? What significant improvements in next 5 years?

Soil C and N model linked and ready to go

More site evaluation

Large scale evaluation?

GHG Climate GHG plant growth

Climate plant growthClimate Soil C & NClimate land use

Plant growth GHGPlant growth Soil C & NPlant growth Land use

Land use GHGLand use Soil C & N

Soil C & N plant growthSoil C & N GHG

Large scale runs including C & N feedbacks

Impacts of land management

Temperature sensitivity

Physical protection

AcknowledgementsAcknowledgements Scottish Executive Scottish Executive

– Development of ECOSSEDevelopment of ECOSSE

EU EU – ATEAM ATEAM – CarboEurope - IPCarboEurope - IP– NitroEurope - IPNitroEurope - IP

DEFRADEFRA– Development of soils module in JULESDevelopment of soils module in JULES

NERC QUESTNERC QUEST– Further development of soils module in JULESFurther development of soils module in JULES

BBSRCBBSRC– Rothamsted Research receives grant aided support from the UK Rothamsted Research receives grant aided support from the UK

Biotechnology and Biological Sciences Research CouncilBiotechnology and Biological Sciences Research Council