Modelling the coupling between carbon turnover and climate variability of terrestrial ecosystems

Modelling the coupling between carbon turnover and climate variability of terrestrial ecosystems

Per-Erik JanssonDepartment of Land and Water Resources EngineeringRoyal Institute of TechnologyKTH, Stockholm

Seminar at ICRAF, Nairobi, 1 December 2010

Outline of presentationOutline of presentationSome general features of the

CoupModel representing coupled ecosystem processes

Examples of how model has been used to describe specific sites with detailed measurements, regional scale with only standared data and climate scenarious

Some implications for future studies

A process oriented A process oriented Ecosystem model - Ecosystem model - CoupModel CoupModel

Coupled heat and mass transfer model for soil-plant-atmosphere systems

Model Availability and FeaturesModel Availability and Features

http://www.lwr.kth.se/Vara%20Datorprogram/CoupModel/index.htm

Includes documentation and tutorials

Water and Heat ProcessesWater and Heat Processes

Interception

Snow

Surface pool

Evaporation Precipitation

SurfaceRunoff

Soilevaporation

Wateruptakebyroots Ground

wateroutflow

Percolation

Groundwaterinflow

Soil surface temperatureor soil heat flow

Externalsources/sinks

Carbon and Nitrogen Carbon and Nitrogen ProcessesProcesses

NH4NH4

NO3NO3

Root

Stem

Leaf

LitterLitter

Humus

Atmosphere

Respiration

Leaching

Photosynthesis

Root

MicrobesMicrobes

C & N

Carbon

NitrogenHarvest

Grain

Process oriented Process oriented modelling platform with modelling platform with many componentsmany components

Heat, including frozen soilsHeat, including frozen soilsWater, liquid, vapour and izeWater, liquid, vapour and izeNitrogen all major processesNitrogen all major processesCarbon all major processesCarbon all major processes

Coupling between different Coupling between different submodelssubmodels

NH4NH4

NO3NO3

Root

Stem

Leaf

LitterLitter

Humus

Atmosphere

Respiration

Leaching

Photosynthesis

Root

MicrobesMicrobes

C & N

Carbon

NitrogenHarvest

Grain

NH4NH4

NO3NO3

Root

Stem

Leaf

LitterLitter

Humus

Atmosphere

Respiration

Leaching

Photosynthesis

Root

MicrobesMicrobes

C & N

Carbon

NitrogenHarvest

Grain

Previous SOIL and SOILN model

New coupled model

Transpiration and Transpiration and PhotosynthesisPhotosynthesisTranspiration is a

function of net radiation and resistances in plant and atmosphere

Photosynthesis is a function of light and the stomata resistance

LAI

Single/Multiple Big Leaf Single/Multiple Big Leaf ModelModel

Reference height

Soil surface

r

r

R LE H

HLE

a

as

r ss

Canopy r s

R

ns s s

qhW upt (i)

na

Emission of NO and N20Emission of NO and N20

Methane emission modelMethane emission model

Modelling of carbon dynamic Modelling of carbon dynamic of Swedish forest soilsof Swedish forest soilsUsing models for interpretation of

data and for upscalingDevelopment of procedures for

calibration and upscaling using Bayesian calibration methods

Producing results for various scales

We have simple data from large regions and detailed data from some few sites

The few sites (Lustra CFS) and regional Forest inventory have been used together

The model has been used as a tool to understand and to make upscaling and downscaling

To start...To start...

x1 yr

(1) estimation of parameters from regional data – 100 years.

(2) site specific data were used to calibrate the model for Flakaliden (dry mesic) and Asa (wet).

(3) climate change scenarios (A2, B2) were used together with parameters from the regional site (1) on a 100 year perspective for dry-mesic sites.

3 steps ...3 steps ...

1 yr

Objective: Estimate trends in soil C storage

Approach: Regional scale with representative sites

Data: Standing tree biomass and soil C and N pools

N

Regional approachRegional approach

Regional input dataRegional input data

N

0 2 4 6 8

Mean air temp. (°C)

0 5 10 15

N dep. (kg N ha-2 yr-1)

0 3 6 9 12

Tree biomass (kg C m-2)

0 3 6 9 12

Soil C (kg C m-2)

Tree Biomass simulation in for four Tree Biomass simulation in for four regionsregions

0

5000

10000

15000

0 20 40 60 80 100

0

5000

10000

15000

0 20 40 60 80 100

0

5000

10000

15000

0 20 40 60 80 100

0

5000

10000

15000

0 20 40 60 80 100

Tre

e bi

omas

s(g

Cm

-2)

Time (yr)

a) b)

c) d)

0

5000

10000

15000

0 20 40 60 80 100

0

5000

10000

15000

0 20 40 60 80 100

0

5000

10000

15000

0 20 40 60 80 100

0

5000

10000

15000

0 20 40 60 80 100

Tre

e bi

omas

s(g

Cm

-2)

Time (yr)

a) b)

c) d)

N

Decomp. rate coeff. (kh)

Organic N uptake

Versus min N Uptake

-5

0

5

10

15

20

25

65°N 61°N 58°N 56°N

Soil C change (g C m-2 yr-1)

Current soil C pools in the south increases whereas central and northern soils are close to steady state

Need for another source of N in addition to mineralised N

Different decomposition rate coeff. along Swedish transect

Tree and Field layer dynamics Tree and Field layer dynamics important for modelling long term important for modelling long term dynamicsdynamics

0

2

4

6

8

0 2 0 4 0 6 0 8 0 1 0 0

T i m e ( y r )

LA

I tr

ee

lay

er

(-)

0

2 0 0

4 0 0

6 0 0

8 0 0

0 2 0 4 0 6 0 8 0 1 0 0

T i m e ( y r )

Fie

ld la

ye

r b

iom

as

s (

gC

m-2

)

a )

b )

South

North

Flakaliden- Flakaliden- calibrationcalibrationObjective: Quantify major

fluxes of C, heat and water including uncertainty estimates

Approach: Bayesian uncertainty theory

Data: Standing tree biomass

and soil C and N pools Internal fluxes i.e.

litterfall, root litter production and DOC

Eddyflux measurements of CO2, heat and water

Soil physical properties

Soil temperature

N

Model performance (mean of Model performance (mean of accepted runs)accepted runs)

- 5

- 3

- 1

1

3

5

7

Jan-0

1

Mar-0

1

May-0

1

Jul-0

1

Sep-0

1

Nov-0

1

Jan-0

2

Mar-0

2

May-0

2

Jul-0

2

Sep-0

2

Nov-0

2

Jan-0

3

NEP (

g C m

-2 da

y -1

)

- 5

- 3

- 1

1

3

5

7

Jan-0

1

Mar-0

1

May-0

1

Jul-0

1

Sep-0

1

Nov-0

1

Jan-0

2

Mar-0

2

May-0

2

Jul-0

2

Sep-0

2

Nov-0

2

Jan-0

3

NEP d

aytim

e (g C

m-2

day

-1)

- 5

- 3

- 1

1

3

5

7

Jan-0

1

Mar-0

1

May-0

1

Jul-0

1

Sep-0

1

Nov-0

1

Jan-0

2

Mar-0

2

May-0

2

Jul-0

2

Sep-0

2

Nov-0

2

Jan-0

3

NEP n

ight-ti

me (g

C m

-2 da

y -1

)

a )

b )

c )

Uncertainty Uncertainty estimatesestimates

Soil Climate

LAI

Flux Effect

Storage Effect variable

W ater

Precipitation Radiation

CO 2

C/N

N Carbon & Nitrogen

644±74

363±43

207±31

-69±18

570±55

138±37

Climate change scenariosClimate change scenarios

Objective: Effects on C-budget and on governing and limiting factors due to climate change

Approach: Climate change of regional approach

Data: IPCC climate change scenarios Hadley A2 and B2

N

Different response on key Different response on key components of ecosystem components of ecosystem environmentenvironment

65°N 61°N 58°N 56°N0

5

10

Air

tem

pe

ratu

re (

°C)

65°N 61°N 58°N 56°N0

500

1000

Pre

cip

itatio

n (

mm

)

65°N 61°N 58°N 56°N0

0.2

0.4

0.6

0.8

Sn

ow

de

pth

(m

)

65°N 61°N 58°N 56°N0

5

10

So

il te

mp

era

ture

(°C

)

65°N 61°N 58°N 56°N

-0.6

-0.4

-0.2

0

Fro

st d

ep

th (

m)

CurrentB2A2

Response for GPP (North and Response for GPP (North and South)South)

0

0.2

0.4

0.6

0.8

1T

-Re

sp

on

se

(-)

65°N 56°N

CurrentB2A2

0

0.2

0.4

0.6

0.8

1

W-R

esp

on

se

(-)

0

0.2

0.4

0.6

0.8

1

J F M A M J J A S O N D

N-R

esp

on

se

(-)

J F M A M J J A S O N DTime (Months)

Seasonal Dynamics Differs (north – Seasonal Dynamics Differs (north – south)south)

0

5

10

15G

PP

65°N 58°N

CurrentB2A2

-20246

NP

P

0

1

Car

bon

Flu

x (g

C m

-2 d

-1)

Het

erot

roph

ic

Res

pira

tion

-2

0

2

4

J F M A M J J A S O N D

NE

E

J F M A M J J A S O N D

Time (Months)

NEP increased in all regions along the Swedish transect.Major part of the increase related to tree growth.

65°N 61°N 58°N 56°N-20

0

20

40

60

80

100

120

140

160

180

200

Ca

rbo

n F

lux

(gC

m-2

yr-1

)

Change SoilOrg C LeachingChange PlantThinning Export

C B2 A2 C B2 A2 C B2 A2 C B2 A2

Climate change effect on tree growth and soil C change

Implications for future Implications for future

Use best uncertainty methods to allow for estimations probabilistic distributions of parameters for specific field investigations

Make simulation experiments to understand uncertainties of coupled models rather than single submodels

Coupled models are Coupled models are necessary to understand long necessary to understand long term behaviour of ecosystemterm behaviour of ecosystemSoil climate is strongly coupled with

vegetation and atmopheric climateSoil physical conditions are a

dynamic forcing for nitrogen and cabon turnover

Dynamic description of plant cover need to include both field and canopy layers for Swedish forest

Carbon, Nitrogen, Water and Heat have to be considered together

Upscaling and downscaling is now possible with flexibility and transparency but...

Uncertainties are still very difficult to express for the regional scale

Site specific data has generated new knowledge but no easy answers for upscaling…

x

xx

Site Region

100 yr

1 yr

Current Climate and Management

Future Climate and Management

Last commentLast comment

An adviser who believes too much in the figures from a mathematical model will be equally poor as the one who fully trusts results from field investigations.

Thanks forThanks for

Thanks for your attention