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