biome-bgc estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and...

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BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms represent physical and biological processes that control fluxes of energy and mass: New leaf growth and old leaf litterfall Sunlight interception by leaves, and penetration to the ground Precipitation routing to leaves and soil Snow (SWE) 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 CO 2 in the air N uptake from the soil Distribution of C and N to growing plant parts Decomposition of fresh plant litter and old soil organic matter Plant mortality Plant phenology Fire/disturbance The BIOME-BGC Terrestrial Ecosystem Process Model

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Page 1: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms

BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems.

Model algorithms represent physical and biological processes that control fluxes of energy and mass:

• New leaf growth and old leaf litterfall • Sunlight interception by leaves, and penetration to the ground • Precipitation routing to leaves and soil • Snow (SWE) 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 • N uptake from the soil • Distribution of C and N to growing plant parts • Decomposition of fresh plant litter and old soil organic matter • Plant mortality• Plant phenology • Fire/disturbance

The model uses a daily time-step with daily updating of vegetation, litter, and soil components.

The BIOME-BGC Terrestrial Ecosystem Process Model

Page 2: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms

• Daily time step (day/night partitioning based on daily information);

• Single, uniform soil layer hydrology (bucket model);

• 1 uniform snow layer of SWE (no canopy snow interception/losses);

• 1 canopy layer (sunlit/shaded leaf partitioning);

• Dynamic phenology and C/N allocation (e.g. LAI, biomass, soil and litter)

• Disturbance (fire) and mortality functions

• Variable litter and soil C decomposition rates (3 litter and 4 soil C pools)

Major Features:

BIOME-BGC

Page 3: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms
Page 4: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms
Page 5: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms
Page 6: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms
Page 7: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms

BIOME-BGC Eco-physiological Parameters

Biome-BGC uses a list of 43 parameters to differentiate biomes. These parameters define the general ecophysiological characteristics of the dominant vegetation type and must be specified prior to each model simulation. These parameters can be measured in the field, obtained from the literature or derived from other measurements.

Default Biome types with defined parameters

•Deciduous Broadleaf Forest (temperate)

•Deciduous Needleleaf forest (larch)

•Evergreen Broadleaf Forest (subtropical/tropical)

•Evergreen Needleleaf Forest

•C3 Grassland

•C4 Grassland

•Evergreen Shrubland

Page 8: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms

Biome-BGC Default Eco-physiological Parameters:

Evergreen Needle-leaf Forest

value units description 1 (flag) 1 = WOODY 0 = NON-WOODY 1 (flag) 1 = EVERGREEN 0 = DECIDUOUS 1 (flag) 1 = C3 PSN 0 = C4 PSN 1 (flag) 1 = MODEL PHENOLOGY 0 = USER-SPECIFIED --- (yday) yearday to start new growth (when phenology flag = 0) --- (yday) yearday to end litterfall (when phenology flag = 0) 0.2 (prop.) transfer growth period as fraction of growing season 0.2 (prop.) litterfall as fraction of growing season 0.26 (1/yr) annual leaf and fine root turnover fraction 0.7 (1/yr) annual live wood turnover fraction 0.005 (1/yr) annual whole-plant mortality fraction 0.005 (1/yr) annual fire mortality fraction 1.4 (ratio) (ALLOCATION) new fine root C : new leaf C 2.2 (ratio) (ALLOCATION) new stem C : new leaf C 0.071 (ratio) (ALLOCATION) new live wood C : new total wood C 0.29 (ratio) (ALLOCATION) new croot C : new stem C 0.5 (prop.) (ALLOCATION) current growth proportion 42.0 (kgC/kgN) C:N of leaves 93.0 (kgC/kgN) C:N of leaf litter, after retranslocation 58.0 (kgC/kgN) C:N of fine roots 50.0 (kgC/kgN) C:N of live wood 730.0 (kgC/kgN) C:N of dead wood 0.31 (DIM) leaf litter labile proportion 0.45 (DIM) leaf litter cellulose proportion 0.24 (DIM) leaf litter lignin proportion 0.34 (DIM) fine root labile proportion 0.44 (DIM) fine root cellulose proportion 0.22 (DIM) fine root lignin proportion 0.71 (DIM) dead wood cellulose proportion 0.29 (DIM) dead wood lignin proportion 0.01 (1/LAI/d) canopy water interception coefficient 0.51 (DIM) canopy light extinction coefficient 2.6 (DIM) all-sided to projected leaf area ratio 8.2 (m2/kgC) canopy average specific leaf area (projected area basis) 2.0 (DIM) ratio of shaded SLA to sunlit SLA 0.033 (DIM) fraction of leaf N in Rubisco 0.004 (m/s) maximum stomatal conductance (projected area basis)

0.00004(m/s) cuticular conductance (projected area basis)

Page 9: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms

BIOME-BGC Environmental Controls on Canopy Conductance (Walker Branch Site)

M_total,sun,shade = (MPPFD,sun,shade * MTmin * MVPD * MPSI)

where multipliers range from 0 (full Gs reduction) to 1 (no effect)

Gs, sun,shade = Gs,max * M_total, sun,shade

M_PSI

0

0.2

0.4

0.6

0.8

1

-0.5 -0.7 -0.8 -1 -1.1 -1.3 -1.4 -1.6 -1.7 -1.9 -2 -2.2 -2.3

PSI (MPa)

M_TMIN

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-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1

TMIN (degC)

M_VPD

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1

900 1200 15001800 2100 24002700 3000 33003600 39004200

VPD (Pa)

M_PPFD

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0 150 300 450 600 750 900 10501200135015001650

PPFD (umol/m2/s)

Page 10: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms

MET_INPUT (keyword) start of meteorology file control block metdata/TDE.mtc41 meteorology input filename 4 (int) header lines in met file RESTART (keyword) start of restart control block 1 (flag) 1 = read restart file 0 = don't read restart file 0 (flag) 1 = write restart file 0 = don't write restart file 0 (flag) 1 = use restart metyear 0 = reset metyear restart/TDE_n.endpoint input restart filename restart/TDE.endpoint output restart filename TIME_DEFINE (keyword - do not remove) 8 (int) number of meteorological data years 8 (int) number of simulation years 1993 (int) first simulation year 0 (flag) 1 = spinup simulation 0 = normal simulation 6000 (int) maximum number of spinup years (if spinup simulation) CLIM_CHANGE (keyword - do not remove) 0.0 (deg C) offset for Tmax 0.0 (deg C) offset for Tmin 1.0 (DIM) multiplier for Prcp 1.0 (DIM) multiplier for VPD 1.0 (DIM) multiplier for shortwave radiation CO2_CONTROL (keyword - do not remove) 1 (flag) 0=constant 1=vary with file 2=constant, file for Ndep 356.0 (ppm) constant atmospheric CO2 concentration TDE_co2.txt (file) annual variable CO2 filename SITE (keyword) start of site physical constants block 0.765 (m) effective soil depth (corrected for rock fraction) 28.0 (%) sand percentage by volume in rock-free soil 64.0 (%) silt percentage by volume in rock-free soil 8.0 (%) clay percentage by volume in rock-free soil 290.0 (m) site elevation 35.95 (degrees) site latitude (- for S.Hem.) 0.2 (DIM) site shortwave albedo 0.0005 (kgN/m2/yr) wet+dry atmospheric deposition of N 0.0004 (kgN/m2/yr) symbiotic+asymbiotic fixation of N

BIOME-BGCExample Initialization File

Page 11: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms

RAMP_NDEP (keyword - do not remove) 0 (flag) do a ramped N-deposition run? 0=no, 1=yes 2099 (int) reference year for industrial N deposition 0.0001 (kgN/m2/yr) industrial N deposition value EPC_FILE (keyword - do not remove) dbf.epc (file) TDE DBF ecophysiological constants W_STATE (keyword) start of water state variable initialization block 0.0 (kg/m2) water stored in snowpack 0.5 (DIM) initial soil water as a proportion of saturation C_STATE (keyword) start of carbon state variable initialization block 0.001 (kgC/m2) first-year maximum leaf carbon 0.0 (kgC/m2) first-year maximum stem carbon 0.0 (kgC/m2) coarse woody debris carbon 0.0 (kgC/m2) litter carbon, labile pool 0.0 (kgC/m2) litter carbon, unshielded cellulose pool 0.0 (kgC/m2) litter carbon, shielded cellulose pool 0.0 (kgC/m2) litter carbon, lignin pool 0.0 (kgC/m2) soil carbon, fast microbial recycling pool 0.0 (kgC/m2) soil carbon, medium microbial recycling pool 0.0 (kgC/m2) soil carbon, slow microbial recycling pool 0.0 (kgC/m2) soil carbon, recalcitrant SOM (slowest) N_STATE (keyword) start of nitrogen state variable initialization block 0.0 (kgN/m2) litter nitrogen, labile pool 0.0 (kgN/m2) soil nitrogen, mineral pool OUTPUT_CONTROL (keyword - do not remove) outputs/TDE_out (text) prefix for output files 1 (flag) 1 = write daily output 0 = no daily output 0 (flag) 1 = monthly avg of daily variables 0 = no monthly avg 0 (flag) 1 = annual avg of daily variables 0 = no annual avg 1 (flag) 1 = write annual output 0 = no annual output 1 (flag) for on-screen progress indicator DAILY_OUTPUT (keyword) 3 (int) number of daily variables to output 516 0 epv.vwc (%) 43 1 wf.soilw_trans (kg m^-2) 38 2 wf.canopyw_evap (kg m^-2) ANNUAL_OUTPUT (keyword) 2 (int) number of annual output variables 545 0 annual maximum projected LAI 636 1 vegetation C END_INIT (keyword) indicates the end of the initialization file

BIOME-BGCExample Initialization File

Cont.

Page 12: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms

-5

-4.5

-4

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-3

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soilw

PS

I

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soilw

PS

I

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soilw

PS

I

(%)

(MP

a)

Soil Class Silt loam Silt Loamβ-value -4.625 -3.84 -5.275VWC_sat 0.48 0.48 0.41PSI_sat -0.0073 -0.0078 -0.0013

BIOME-BGC 1Soil Water – Soil Water Potential Curves

1after Cosby et al., 1984

Page 13: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms
Page 14: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms
Page 15: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms

MODIS LAI vs BIOME BGC LAI Walker Branch, TN 2001 (Mixed Deciduous Hardwood Forest)

0

1

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1 31 61 91 121 151 181 211 241 271 301 331 361

DOY

LA

I (m

2/m

2)

MODIS LAI BGC Proj LAI

Page 16: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms

0

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Date

mm

d-1

BIOME-BGC Tower Flux

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Date

mm

d-1

Tower Flux BIOME-BGC

-0.004

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0.004

Jan-94

Mar-94

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Jul-94

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Date

kg C

m-2

d-1

BIOME-BGC Tower Flux

-0.01

-0.005

0

0.005

0.01

Jan-94

Mar-94

May-94

Jul-94

Sep-94

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Jan-95

Mar-95

May-95

Jul-95

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Date

Kg

C m

-2 d

-1

BIOME-BGC Tower Flux

Mature Black Spruce Stand (NSA-OBS Ameriflux site) Mature Aspen Stand (SSA-OA BERMS site)

Verification of BIOME-BGC Daily and Seasonal Dynamics: Comparisons with Tower Eddy-flux Measurements

NEPNEP

ET ET

Kimball et al., 1997a,b

Page 17: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms

LANDCOVER

GIS Input Layers

Measurements

Modeling

Regional Extrapolation through remote sensing, field measurements and ecological models (BOREAS SSA)

NPP ( Mg C ha-1)

Water0.2

3.0

0

4000

8000

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16000

5000 5100 5200 5300 5400

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14.4

10.8

7.2

3.6

0.0

Are

a (k

m2 )

1994 (mean = 2.2) 1995 (mean = 1.8) 1996 (mean = 1.7)

NPP Distributions (Mg C ha -1 yr-1)

Kimball et al., 00.

0

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10.8

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3.6

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Are

a (k

m2 )

1994 (mean = 2.2) 1995 (mean = 1.8) 1996 (mean = 1.7)

NPP Distributions (Mg C ha -1 yr-1)

Kimball et al., 00.

Kimball et al., 2000

Page 18: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms
Page 19: BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms

MODEL LOGIC:Thornton, P. E. (1998). Description of a numerical simulation model for predicting the dynamics of energy, water, carbon, and nitrogen in a terrestrial ecosystem. Ph.D. dissertation, University of Montana, Missoula, MT, 280pp. [Available from Mansfield Library, University of Montana, Missoula, MT 59812].

Thornton, P. E., B. E. Law, et al. (2002) Modeling the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests. Agricultural and Forest Meteorology (in press).

BIOME ECOPHYSIOLOGICAL PARAMETERIZATION:White, M. A., P. E. Thornton, and S. W. Running (2000). Parameterization and sensitivity analysis of the BIOME-BGC terrestrial ecosystem model: Net primary production controls. Earth Interactions 4(3): 1-85.

PHENOLOGY:White, M.A., P.E. Thornton, and S.W. Running (1997). A continental phenology model for monitoring vegetation responses to inter-annual climatic variability. Global Biogeochemical Cycles 11(2): 217-234 [Available online at NTSG website].

Documentation of BIOME-BGC Updates