Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Adjusting a global ecosystem model for local performance
– calibration and sensitivity analysis of BIOME-BGC in
Switzerland
N.E. ZimmermannWSL
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Niklaus E. Zimmermann1, Peter. E. Thornton2, Matt Jolly3, Paolo Cherubini4, Felix Kienast1, Norbert Kräuchi4, Otto Wildi1, Matthias Dobbertin4, Werner Schoch1, Marcus
Schaub4, Luzi Bernhard4
1Swiss Federal Research Institute WSL, Division of Landscape, CH-8903 Birmensdorf, Switzerland;
2Climate & Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO, USA; 3NTSG lab, School of Forestry, University of Montana, Missoula, MT, USA;
4Swiss Federal Research Institute WSL, Division of Forest, CH-8903 Birmensdorf, Switzerland
Scaling carbon fluxes from stands to landscapes: calibrating and testing BIOME-BGC along multiple
environmental gradients
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
The Biome-BGC Terrestrial Ecosystem Process Model
Biome = an area characterized by its flora, fauna, and climateBGC = BioGeochemical Cycles
The model uses a daily time-step. Flux (and pools) are estimated for a one-day period. Between days, the program updates its memory of the mass stored in different components of the vegetation, litter, and soil.
Weather is the most important control on vegetation processes. Flux estimates in Biome-BGC depend strongly on daily weather conditions. Model behavior over time depends on the history of these weather conditions, the climate.
• New leaf growth and old leaf litterfall • Sunlight interception by leaves, and penetration to the ground• Precipitation routing to leaves and soil• Snow accumulation and melting• Drainage and runoff of soil water • Evaporation of water from soil and wet leaves• Transpiration of soil water through leaf stomata• Photosynthetic fixation of carbon from CO2 in the air• Uptake of nitrogen from the soil • Distribution of carbon and nitrogen to growing plant parts• Decomposition of fresh plant litter and old soil organic matter• Plant mortality• Fire
Biome-BGC is a computer program that estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. It is a process model because its algorithms represent physical and biological processes that control fluxes of energy and mass. These processes include:
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Biome: required meteorological inputs
• Daily maximum temperature (°C) • Daily minimum temperature (°C)• Daylight average temperature (°C)• Daily total precipitation (cm)• Daylight average partial pressure of water vapor (Pa)• Daylight average shortwave radiant flux density (W/m2)• Daylength (s)
In many cases, the only data available for a particular site are daily Tmin/Tmax and Prec. The model MT-CLIM can then be used to derive estimates of the other required meteorological parameters.
Biome: required soils inputs: % clay, silt, sand
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Site Characteristics• Meteorological inputs
• Maximum temperature• Minimum temperature• Precipitation• Radiation• Humidity/ VPD
• Soil characteristics
Ecophysiological Parameters• Biome properties• Leaf/Litter/Wood chemistry & characteristics (C:N, SLA, lignin,
cellulose, etc.)• Photosynthetic characteristics• Allocation rules• Turnover rates• etc.
BIOME-BGC
BIOME-BGC inputBIOME-BGC input
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
1:(flag) 1 = WOODY 0 = NON-WOODY 2:(flag) 1 = EVERGREEN 0 = DECIDUOUS 3:(flag) 1 = C3 PSN 0 = C4 PSN 4:(flag) 1 = MODEL PHENOLOGY 0 = USER-SPECIFIED PHENOLOGY 5:(yday) yearday to start new growth (when phenology flag = 0) 6:(yday) yearday to end litterfall (when phenology flag = 0) 7:(prop.) transfer growth period as fraction of growing season 8:(prop.) litterfall as fraction of growing season 9:(1/yr) annual leaf and fine root turnover fraction 10:(1/yr) annual live wood turnover fraction 11:(1/yr) annual whole-plant mortality fraction 12:(1/yr) annual fire mortality fraction 13:(ratio) (ALLOCATION) new fine root C : new leaf C 14:(ratio) (ALLOCATION) new stem C : new leaf C 15:(ratio) (ALLOCATION) new live wood C : new total wood C 16:(ratio) (ALLOCATION) new croot C : new stem C 17:(prop.) (ALLOCATION) current growth proportion 18:(kgC/kgN) C:N of leaves 19:(kgC/kgN) C:N of leaf litter, after retranslocation 20:(kgC/kgN) C:N of fine roots 21:(kgC/kgN) C:N of live wood 22:(kgC/kgN) C:N of dead wood 23:(DIM) leaf litter labile proportion 24:(DIM) leaf litter cellulose proportion 25:(DIM) leaf litter lignin proportion 26:(DIM) fine root labile proportion 27:(DIM) fine root cellulose proportion 28:(DIM) fine root lignin proportion 29:(DIM) dead wood cellulose proportion 30:(DIM) dead wood lignin proportion 31:(1/LAI/d) canopy water interception coefficient 32:(DIM) canopy light extinction coefficient 33:(DIM) all-sided to projected leaf area ratio 34:(m2/kgC) canopy average specific leaf area (projected area basis) 35:(DIM) ratio of shaded SLA:sunlit SLA 36:(DIM) fraction of leaf N in Rubisco 37:(m/s) maximum stomatal conductance (projected area basis) 38:(m/s) cuticular conductance (projected area basis) 39:(m/s) boundary layer conductance (projected area basis) 40:(MPa) leaf water potential: start of conductance reduction 41:(MPa) leaf water potential: complete conductance reduction 42:(Pa) vapor pressure deficit: start of conductance reduction 43:(Pa) vapor pressure deficit: complete conductance reduction
Biome propertiesPhenology info
Turnover infoMortality info
Allocation rules
C:N ratios
Decomposition info
Canopy/leaf info
Leaf physiology
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
BIOME-BGC outputBIOME-BGC output
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
NP
P
[kgC
/m2 ]
Net Primary Productivity for Othmarsingen, 1931-2001
<
BIOME-BGC outputBIOME-BGC output
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
NP
P
[kgC
/m2]
Net Primary Productivity for Othmarsingen, 1931-2001
Net
Pri
mar
y P
rodu
ctiv
ity (
NP
P)
[kg
C/m
2 ]
Net Primary Productivity for Missoula, Montana 1994
BIOME-BGC outputBIOME-BGC output
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
<
BIOME-BGC outputBIOME-BGC output
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Net Primary Productivity for Othmarsingen, 1998
kgC
/m2
<
BIOME-BGC outputBIOME-BGC output
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Net Ecosystem Exchange for Othmarsingen, 1998
kgC
/m2
Concept & state of the Swiss Biome-BGC projectConcept & state of the Swiss Biome-BGC project
Calibrate and thoroughly test the Biome-BGC model for Swiss forests along multiple environmental gradients
A
Test the hypothesis of increased tree growth in Central European forests in the decade of 1991 to 2000 compared to earlier decades.
B
Testing MODIS-MOD17 (NPP/GPP) data on the same test sites (calculated using the Biome-BGC logic, but based on RS inputs, partly)
C
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Calibration and test sitesCalibration and test sites
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Project work flow and progressProject work flow and progress
Test dataLWF sites
• stand level data, structure, mass• leaf chemistry, mass• intra-annual growth rates• soils & roots data
Calibrationdata
• C:N of leafs, roots, wood• leaf-level physiology• C-partitioning• decay rates, etc.
Test model • testing against field data• sensitivity analyses
Run simulations
• past 4 decades, test w| tree rings• test set of hypotheses• test effect of scale & resolution
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
prog
ress
Project work flow and progressProject work flow and progress
Test dataLWF sites
• stand level data, structure, mass• leaf chemistry, mass• intra-annual growth rates• soils & roots data
Calibrationdata
• C:N of leafs, roots, wood• leaf-level physiology• C-partitioning• decay rates, etc.
Test model • testing against field data• sensitivity analyses
Run simulations
• past 4 decades, test w| tree rings• test set of hypotheses• test effect of scale & resolution
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Calibration & test data preparationCalibration & test data preparation
The following data were primarily collected in the field
• C:N of sunlit/shaded leafs & stem wood• A/Ci curves of sunlit (some shaded) leafs• Sunlit and Shaded leafs SLA• Leaf phenology (flush, drop) of deciduous trees• Number of needle years (needle turnover fraction)• Wood/tree cores for inter-/intraannual growth and density
People involved: Matt Jolly, Theo Forster, Stéphanie Schmid, Markus Schaub, Dani Nievergelt, Paolo Cherubini, Peter Suter, Werner Schoch, Matthias Dobbertin, Norbert Kräuchi, Felix Kienast, Dmitry Golikov, Lorenz Waltert, Stefan Zimmermann, Gustav Schneiter, Peter Jakob, etc. etc.
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Vcmaxactfnrflnrlnc
sm
CO mol
sRubg
CO mol
N g
Rub g
N g
N g
m
N g2
222
Rubleaf
Rubleaf
Vcmax: Maximum carboxylation rate (=PS-rate)lnc: Leaf nitrogen content (from C:N and SLA)flnr: Fraction of leaf nitrogen in Rubiscofnr: Rubisco nitrogen fraction (enzyme structure)act: enzyme activity of Rubisco
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
valid if stomatal resistance is minimal
Calibration & test data preparationCalibration & test data preparation
Leaf physiology
(lnc) x (flnr) x (fnr) x (act) = (Vcmax)
Area-based leaf N concentration = 1/ (SLA C:Nleaf)
Rubisco activity = f(Tleaf)
Maximum rate of photosynthesis(determined from fit to ACi curves)
Determined from protein structure
Leaf physiology
sm
CO mol
sRubg
CO mol
N g
Rub g
N g
N g
m
N g2
222
Rubleaf
Rubleaf
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Calibration & test data preparationCalibration & test data preparation
leafRubRub NfractNfractact
VcFLNR
..max
Calibration & test data preparationCalibration & test data preparation
Leaf physiology
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
constant constant 1/ (SLA C:Nleaf)
ACi curves
Beauty and pain of field work - Vcmax
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Calibration & test data preparationCalibration & test data preparation
Beauty and pain of field work – SLA / C:N
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Calibration & test data preparationCalibration & test data preparation
Leaf physiologyA/Ci curve Pinus sylvestris
-20
-10
0
10
20
30
40
50
60
70
80
0 200 400 600 800 1000 1200 1400
Internal CO2 concentration
Ass
imil
atio
n
LapseRate
Vcmax
Plateau Jmax &/or
TPU
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Calibration & test data preparationCalibration & test data preparation
A-Ci curve Quercus pubescens
-1
-0.5
0
0.5
1
1.5
2
2.5
3
0 50 100 150 200 250 300 350 400
Internal CO2 concentration
Ass
imil
atio
n
uselessdata ....
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Calibration & test data preparationCalibration & test data preparation
Leaf physiology
Wc = Vcmax; Maximum rate of carboxylation by RuBisCO (CO2 limitation)
Wj = Jmax; RuBP-Regeneration (electron transport limitation)Wp = Regeneration of inorganic phosphate; (TPU-limitation)
A/Ci curves are analyzed using the Photosyn Assistant software [Dundee Scientific, UK]
Param Est. SEResp 1.53 3.38E-01Vcmax 57.5 1.12E+00Jmax 189 4.38E+00TPU 12.2 1.83E-01CO2 comp. est. (from Wc) = 5.13Sy.x = 6.10E-01 DF= 8Iteration count 2014SSqs 2.98
Example output:
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Calibration & test data preparationCalibration & test data preparation
Leaf physiology
Modified Farquhar (1980) photosynthesis eqn.:
dayi
RWpWjWcC
OA
,,min
5.01
Where, e.g.:
KoOKcCi
CiVcWc
1
max
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Calibration & test data preparationCalibration & test data preparation
Leaf physiology
internal CO2
concentrationinternal O2
concentration
Michaelis-Menten constants of Rubisco for CO2 and O2
respiration other than
photorespiration
Calibration of C:N for Fagus sylvatica
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Calibration & test data preparationCalibration & test data preparation
Calibration of SLA for Fagus sylvatica
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Calibration & test data preparationCalibration & test data preparation
Calibration of FLNR for Fagus sylvatica
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Calibration & test data preparationCalibration & test data preparation
Vcmax seasonal pattern: Fagus sylvatica
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Calibration & test data preparationCalibration & test data preparation
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
How much do simulations differ with locally optimized parameters compared to the global DBF parameter set?
1
How sensitive is the model with respect to the accuracy of the measured parameters?
2
These questions are mostly analyzed by evaluating effects on carbon and nitrogen pools (not so much fluxes).
Most variables varied 5-15% between sites.
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Set up for sensitivity analyses
A annual whole plant mortality fractionB C:N of leavesC C:N of live woodD C:N of dead woodE dead wood lignin/cellulose proportionF canopy light extinction coefficientG canopy average SLAH ratio of shd:sun SLAI fraction of leaf N in RubiscoJ B & G & H at the same timeK B & G & H & I at the same timeL soil depthM sand proportion in soil
each variable was increased by 5% and by 15% respectively
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Simulation results Othmarsingen (C-Pool)
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Simulation results Othmarsingen (N-Pool)
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Simulation results Othmarsingen (C-Pool, change)
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Simulation results Othmarsingen (N-Pool, change)
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Simulation results Lausanne (C-Pool, change)
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Summary-1
The accuracy of the measured parameter has a clear impact on the model simulations.
1
C:N ratio’s have a higher impact in Othmarsingen, where soils are shallow(er) and less rich.
2
Mortality and soil parameters are additionally important.
3
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
How does the sensitivity of parameters change across environmental gradients?
1
Do different parameters behave differently?2
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Distribution of F. sylvatica in the environmental space
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Set up for 2nd sensitivity analyses
A annual whole plant mortality fractionB C:N of leavesG canopy average SLAI fraction of leaf N in Rubisco
each variable was increased by 15% on each plotand compared to the standard calibration
Soil parameters (sand, silt, clay, soil depth) are kept constant
The climate of Othmarsingen is linearly adjusted for temperature and/or precipitation for each lattice point in order to exclude the effect of climate seasonality
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
BBGC Sensitivity G07085
-15.00%
-10.00%
-5.00%
0.00%
5.00%
+15
%M
ort
+15
%le
afC
:N
+15
%ca
nopy
avg.
SLA
+15
%F
LNR
Tested variables
Res
ult
ing
C-P
ool
size
VEG-C
LITTER-C
SOIL-C
Simulation results for Tave=7.0; Prcp=850mm
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Climate effects on Veg-C
Simulated Fagus Veg-C across env. gradients
Prcp [cm]
Tave
[de
g. C
]
100 120 140 160
89
10
11
46 48
50 52 54
54
56
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Simulated Fagus Soil-C across env. gradients
Prcp [cm]
Tave
[de
g. C
]
100 120 140 160
89
10
11
12
12
12
12
14161818
Climate effects on Soil-C
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Effects of 15% C:N parameter error on Veg-C
Prcp [cm]
Tave
[de
g. C
]
100 120 140 160
89
10
11
-3.5-3 -3
-2.5
-2.5
-2
Sensitivity along env. gradients (C:NVeg-C)
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Sensitivity along env. gradients (SLAVeg-C)
Effects of 15% SLA parameter error on Veg-C
Prcp [cm]
Tave
[de
g. C
]
100 120 140 160
89
10
11
-2 -1.5
-1
-1
-0.5
-0.5
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Sensitivity along env. gradients (FLNRVeg-C)
Effects of 15% FLNR parameter error on Veg-C
Prcp [cm]
Tave
[de
g. C
]
100 120 140 160
89
10
11
0.450.45
0.450.45
0.5
0.5
0.5
0.550.60.65
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Sensitivity along env. gradients (MortVeg-C)
Effects of 15% Mortality parameter error on Veg-C
Prcp [cm]
Tave
[de
g. C
]
100 120 140 160
89
10
11
-13.4 -13.4-13.4 -13.4-13.3 -13.3-13.3 -13.3
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Summary-2
The model reacts non-linear to changes in the model parameters along environmental gradients.
1
Different parameters show differing patterns along environmental gradients
2
Mortality and leaf level chemistry parameters are highly sensitive to ecosystem simulations.
3
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Outlook – next steps
Finish this sensitivity analysis for enlarged gradients.
1
Include other major tree species that are now calibrated.
2
Test model on LWF and WSI sites.3
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Evaluate hypotheses of increased/decrease NPP along environmental gradients using single point and spatial Biome-BGC simulations.
1
Different parameters show differing patterns along environmental gradients
2
Mortality and leaf level chemistry parameters are highly sensitive to ecosystem simulations.
3
Outlook – and thereafter
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Requirements – 1: daily climate maps
Daily Tmin simulations (L. Bernhard & N.Zimmermann)
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Requirements – 1: daily climate maps
Daily Tmax simulations (L. Bernhard & N.Zimmermann)
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Model runs and sensitivity analysesModel runs and sensitivity analyses
Requirements – 2: fractional covers
Daily Tmax simulations (M. Schwarz, L. Mathys & N.Zimmermann)
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Thank you for your attention
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Some more stuff / results
Progress report on test data & -simulationsProgress report on test data & -simulations
Examples of preliminary LWF site simulations
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Simulated NPP vs. Ring width
400
500
600
700
800
900
1000
1100
1200
1300
1400
1932
1934
1936
1938
1940
1942
1944
1946
1948
1950
1952
1954
1956
1958
1960
1962
1964
1966
1968
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
Year
NP
P (
gC
/m^2
/yr)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
Sta
nd
ard
ized
Rin
g w
idth
BGC_NPP
Ringwidth
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Progress report on test data & -simulationsProgress report on test data & -simulations
Examples of preliminary LWF site simulations
Othmarsingen
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Simulated Max. LAI and Evapotranspiration
3456789
1930 1940 1950 1960 1970 1980 1990 2000Year
max
. L
AI
500
700
900
1100
1300
1500
ET
max LAIann ET
Simulated NPP
0
200
400
600
800
1000
1200
1400
1930 1940 1950 1960 1970 1980 1990 2000
Year
% d
aily
wo
od
fo
rmat
ion
Avg
. d
aily
NP
P (kg C/m
2 /day)
simulated NPP (mass+storage) vs. stemwood production (mass)OthmarsingenOthmarsingen (Fagus sylvatica)
Leaves
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
-0.200
0.000
0.200
0.400
0.600
0.800
1.000
1.200
1.400
1.600
1.800
80 100 120 140 160 180 200 220 240 260 280 300 3200.000
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0.008
0.009
0.010
simulated NPP (mass+storage) vs. stemwood production (mass)VordemwaldVordemwald (Abies alba & Picea abies)
Needles
% d
aily
wo
od
fo
rmat
ion
Avg
. d
aily
NP
P (kg C/m
2 /day)
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
80 100 120 140 160 180 200 220 240 260 280 300 320
-0.002
-0.001
0
0.001
0.002
0.003
0.004
0.005
0.006
0.007
ΔDBH
Counts
Avg_core
BBGC_NPP
Next tasks (loose list)Next tasks (loose list)
• Stand structural data (3-4 year colume increments per size class)
• Densitometry and Ring width of individual years, sizes• Calibrate for 3-4 year period per LWF plot• Reconstruct NPPa for last few decades
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Next tasks (loose list)Next tasks (loose list)
Finish additional calibration data (roots, LWF, …)• Mostly root turnover, C:N, allocation is not well
included yet• Lots of C:N (leafs, needles, wood) is in the analyses lab• Leaf litter data from LWF is currently under analysis
Finish preparation for spatial simulations• Prepare input maps for dominant forest types• Using a combination of RS and GIS/Statistical modelling
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Next tasks (loose list)Next tasks (loose list)
Finish preparation for spatial simulations (ctnd.)
Developed by M. Schwarz & N. ZimmermannMountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Progress report on calibrationProgress report on calibration
Intra-annual Growth
Sampling:• every 2 weeks (later 4 weeks)• 6 sites (LWF)• dominant spp., 3 size classes, 2 cores per tree
Analysis• # of cells added since last date• diameter increment (1/100mm) since last date• % daily average growth per period• average per species (size).
Intraannual growth dynamics
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
100 120 140 160 180 200 220 240 260 280 300
Yearday
% d
aily
gro
wth
Fagus sylvatica
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Progress report on calibrationProgress report on calibration
Intra-annual Growth some results
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
100 120 140 160 180 200 220 240 260 280 300
Yearday
% d
aily
gro
wth
Fagus sylvatica
Climate and Soils
-500
-450
-400
-350
-300
-250
-200
-150
-100
-50
0
100 120 140 160 180 200 220 240 260 280 300
Yearday
Wat
er t
ensi
on
(h
Pa)
0
5
10
15
20
25
Tem
par
atu
re (
°C)
15cm30cm45cm80cm130cmTave
Othmarsingen
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
Progress report on calibrationProgress report on calibration
Intra-annual Growth some results
Vordemwald
Climate and Soils
-100.0
-50.0
0.0
50.0
100.0
150.0
200.0
250.0
300.0
100 120 140 160 180 200 220 240 260 280 300
Yearday
Glo
bal
Rad
& W
ater
Ten
sio
n
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
18.0
20.0
Tav
e
GlobRadSW15SW30SW45SW80SW130Tave
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
100 120 140 160 180 200 220 240 260 280 300
Yearday
% d
ail
y g
row
th
Counts
Increment
Conifers
Mountain Forest Ecology Seminar; Jan. 22nd 2004 Niklaus E. ZimmermannBiome-BGC: Calibration and Sensitivity Analyses
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