1. Introduction to Biome-BGC
Ryan Anderson*
September 23, 2009
*With thanks to Jordan Golinkoff, Faith Ann Heinsch, Matt Jolly, and anybody else whose slides or work made it into this document

2. “All models are wrong, but some are useful” -G.E. Box
Models are an abstraction of reality
Goal is to represent the relevant processes in sufficient detail to answer research or management questions
Simplifying assumptions need to be made
Making a model more detailed or complicated does not necessarily make it better

3. Biome-BGC
Biome = A major regional or global community, characterized chiefly by the dominant forms of vegetation and the prevailing climate
BGC = BioGeoChemical
Bio = living organisms (plant responses)
Geo = Earth (soils)
Chemical = chemical reactions, specifically carbon, nitrogen, and water
Biome-BGC is a process-based model that tracks Carbon, Water, Nitrogen, and Energy Fluxes through terrestrial ecosystems.

4. Process based vs. Empirical Models
Data-driven, or driven by understanding of processes? Biome-BGC is both, but primarily process based.

5. The BIOME-BGC Terrestrial Ecosystem Process Model
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.
Energy, Carbon, Water, Noitrogen have imprtant interactions

6. Not an individual Species Model
The BIOME-BGC Terrestrial Ecosystem Process Model
Not an individual Species Model
Most Biological Process represented at the Canopy Level (i.e. a ‘Big Leaf’ or ‘Green Sponge’ Model)
Daily Time Step
No Defined Spatial Scale (pools and fluxes are represented on a per unit area basis)
Not a Spatial Model (no linkages between gridcells)
Prognostic Model

7. BIOME-BGC General Concepts
Growth (Uptake CO2 for photosynthesis)
F(temp,humidity,radiation,soil water deficits)
Farquhar photosynthesis equation
Differentiated by sunlit and shaded leaves
Reduced by environmental constraints
Allocation
Once photosynthesis takes place, the model must allocate fixed carbon to different places (I.e. roots, leaves, stems, etc…,)
Respiration
Both for maintaining current biomass and growing new biomass. Net loss of CO2 to the atmosphere.

8. Digging Deeper: How does Biome BGC represent important biological and physical processes?
Pools and Fluxes
Photosynthesis
Stomatal Conductance
Radiation interception and transmission
Transpiration and Evaporation
Links to Photosynthesis – Stomatal Conductance, energy balance
Routing of Precipitation
Growth and Maintenance Respiration
Decomposition – Heterotrophic Resipration
Carbon Allocation
Nutrient Availability

9. Biome-BGC’s Carbon and Nitrogen Pools

10. Biome-BGC’s Carbon and Nitrogen Fluxes

11. Rubisco catalyzes both the carboxylation and oxygenation of RuBP!
Photosynthesis
6 CO2 + 6H20  C6H12O6 + 6O2
Rubisco catalyzes both the carboxylation and oxygenation of RuBP!

12. Michaelis-Menten Enzyme Kinetics
Reaction rate depends on the maximum reaction rate , the concentration of the substrate (CO2), and the MM constant (Km).
Rubisco reacts with both CO2 and oxygen, so it has an MM constant for each.
CO2
concentration
MM constant, adjusted for effect
of competition with oxygen

13. Factors controlling VcMax
(lnc) x (flnr) x (fnr) x (act) = (Vcmax)
Rubisco activity = f(Tleaf)
Determined from protein structure (constant 7.16 gR/gN – Rubisco is approximately 14% nitrogen by mass)
Fraction of leaf N in Rubisco
Area-based leaf N concentration = 1/ (SLA C:Nleaf)

14. Regeneration of RUBP can also limit photosynthesis
Light is required to produce ATP required to regenerate RUBP
Plants have evolved such that light harvesting capacity is closely linked to maximum carboxylation rates (Jmax = 2.1 * Vmax, Wullschleger 1993)
Realized Rate(J) of RUBP regeneration is related to light intensity(ppfd) according to a quadratic function:
0.7J2 – (Jmax + (ppfd/2))J + Jmax(ppfd/2) = 0

15. Regeneration of RUBP can also limit photosynthesis
Apply some stoichiometry and we get the radiation (RUBP) limited rate of photosynthesis:
This equation is based on the energy requirements of the Calvin Cycle and the relationship between rubisco carboxylation and oxygenation as expressed through the CO2 compensation point. Don’t worry about the details.

16. Biome-BGC’s Energy Balance

17. CO2 must diffuse through stomates in order for photosynthesis to take place
Tradeoff-CO2 gain leads to water loss  feedback between carbon and water cycles

18. Stomatal aperture is controlled by many variables
Cold temperatures
Hot temperatures
Low soil water availability
Supply
High atmospheric demand for water
–Demand
Changes in the gradient of CO2
Any of these will reduce photosynthesis
–Weather drives ecological processes
Modeling plant ecosystem processes requires that we treat the most important components

19. Gs = gsmax * mppfd * mt * msoil * mVPD

20. Photosynthesis in Biome-BGC
A= g * (Ca – Ci)
Stomatal Conductance limit
Carboxylation Limit
Substrate Regeneration limit
Variables impacting photosynthetic rate:
-CO2 concentration (and an assumed oxygen concentration)
-Temperature
-Stomatal Conductance
-Solar Radiation
-Leaf Nitrogen
-Leaf Respiration rate (which, as we will see, is a function of leaf nitrogen and temperature)

21. Vertical Gradient of Leaf Traits with Canopy Depth
Differing light environments of leaves are important for modeling canopy scale photosynthesis
Vertical Gradient of Leaf Traits with Canopy Depth
High light = high leaf N, thick, short lived leaves with large maintenance respiration costs
Low Light = Lower leaf N, thinner, longer lived leaves with lower respiration costs

22. Two Layer Canopy in Biome-BGC
User specifies a ratio of sunlit to shaded leaves
User specifies a ratio of sunlit SLA to shaded SLA
Biome-BGC calculates leaf area for each based on total leaf C
Stomatal Conductance, Transpiration, and VcMax are calculated
Seperately for each layer
Photosynthesis Routine is run separately for each layer

23. Biome-BGC’s Water Balance

24. Penman-Monteith Equation provides
Basis for ET estimates
sA+ρCp(esat – e)/ra
λE=
s+γ(1+rs/ra)
λ = latent heat of evaporation (J/kg – a function of temperature)
ρ = air density (kg/m3 _ function of temperature)
s = slope of the saturated VP vs. Temp curve (at right)
γ = A constant (Pa/K)
A = Net Radiation (W/m2)
Cp = Specific Heat of Air (J/Kg/K)
e = Vapor Pressure
Esat = Saturated Vapor Pressure
Ra = aerodynamic resistance (s/m)
Rs = surface resistance (s/m)
Evaporation is driven by:
1) available Energy
2) Vapor Pressure Deficit
3) Resistance terms

25. Soil Water Potential Curves
BIOME-BGC 1Soil Water –
Soil Water Potential Curves
(%)
(MPa)
Soil Class Silt loam Silt Loam
β-value
VWC_sat
PSI_sat
1after Cosby et al., 1984

26. Autotrophic Respiration
Maintenance Respiration:
Empirical relationship with tissue nitrogen
Computed separately for each live tissue pool
Scaled to temperature using a Q10 formula
Q10 represents the change in respiration rate that occurs with a 10 degree change in temperature
MR = kg C / kg N day * N * 2.0(T – 20)/10

27. Autotrophic Respiration
Growth Respiration:
30% of all carbon allocated to new tissue is respired.

28. Decomposition

29. Decomposition
Cellulose
Labile
Lignin

30. Decomposition

32. Biome-BGC’s Carbon and Nitrogen Fluxes

33. Carbon Allocation User specified, constant allometric ratios:
Percent of storage
New fine root : new leaf
New stem : new leaf
New live wood : new total wood
New coarse root : new stem
Each compartment has a C:N ratio
Used to calculate Nitrogen demand of potential new growth
If soil mineral nitrogen is insufficient, the day’s production is reduced
Allocation ratios are difficult to parameterize from the literature, but have important impacts on production, respiration rates, and pool sizes

34. Disturbance in Biome-BGC

35. The problem of initial conditions

36. Summary - Carbon Photosynthesis Rates are determined by leaf nitrogen
Needs water from the soil
Reduced by water supply/demand, carbon supply/demand
Respiration
Loss of carbon from the system
Maintenance and growth
Autotrophic
Heterotrophic

37. Summary - Water Transpiration
Water lost by stomata which also control CO2 uptake
Canopy interception of precipitation
Determined by the amount of carbon fixed by photosynthesis that is allocated to leaf
Soil water evaporation
Driven by the weather
Outflow Determined by excess water not taken up by the plant

38. Summary - Nitrogen Nitrogen in the leaves
Determine maximum photosynthetic rate
Atmospheric N deposition (pollution)
Additional inputs to the system
Soil N limitations
Plants compete with soil microbes for nitrogen to incorporate into plant tissue

39. Running Biome-BGC – what is required?
Site Physical Description (part of ini file)
Vegetation Ecophysiological Parameters (epc file)
Meteorology (met file)
Model run instructions (part of ini file)

41. Meteorological Parameters Required by Biome-BGC
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)

42. Example Met. Data Input (Generated from MT-CLIM)
Missoula, : Sample input for MTCLIM v4.1
MTCLIM v4.1 OUTPUT FILE : Tue Aug 25 10:15:
year yday Tmax Tmin Tday prcp VPD srad daylen
(deg C) (deg C) (deg C) (cm) (Pa) (W m-2) (s)

43. Biome-BGC Initialization file
Biome-BGC v4.1.2 example : (normal simulation, Missoula, evergreen needleleaf)
MET_INPUT (keyword) start of meteorology file control block
metdata/miss5093.mtc41 meteorology input filename
(int) header lines in met file
RESTART (keyword) start of restart control block
(flag) 1 = read restart file = don't read restart file
(flag) 1 = write restart file 0 = don't write restart file
(flag) 1 = use restart metyear 0 = reset metyear
restart/enf_test1.endpoint input restart filename
restart/enf_test1.endpoint output restart filename
TIME_DEFINE (keyword - do not remove)
(int) number of meteorological data years
(int) number of simulation years
(int) first simulation year
(flag) = spinup simulation 0 = normal simulation
(int) maximum number of spinup years (if spinup simulation)
CLIM_CHANGE (keyword - do not remove)
(deg C) offset for Tmax
(deg C) offset for Tmin
(DIM) multiplier for Prcp
(DIM) multiplier for VPD
(DIM) multiplier for shortwave radiation

44. Biome-BGC Initialization file, continued
CO2_CONTROL (keyword - do not remove)
(flag) 0=constant 1=vary with file 2=constant, file for Ndep
(ppm) constant atmospheric CO2 concentration
xxxxxxxxxxx (file) annual variable CO2 filename
SITE (keyword) start of site physical constants block
(m) effective soil depth (corrected for rock fraction)
(%) sand percentage by volume in rock-free soil
(%) silt percentage by volume in rock-free soil
(%) clay percentage by volume in rock-free soil
(m) site elevation
(degrees) site latitude (- for S.Hem.)
(DIM) site shortwave albedo
(kgN/m2/yr) wet+dry atmospheric deposition of N
(kgN/m2/yr) symbiotic+asymbiotic fixation of N
RAMP_NDEP (keyword - do not remove)
(flag) do a ramped N-deposition run? 0o, 1=yes
(int) reference year for industrial N deposition
(kgN/m2/yr) industrial N deposition value
EPC_FILE (keyword - do not remove)
epc/enf.epc (file) evergreen needleleaf forest ecophysiological constants

45. Biome-BGC Initialization file, continued
W_STATE (keyword) start of water state variable initialization block
(kg/m2) water stored in snowpack
(DIM) initial soil water as a proportion of saturation
C_STATE (keyword) start of carbon state variable initialization block
(kgC/m2) first-year maximum leaf carbon
(kgC/m2) first-year maximum stem carbon
(kgC/m2) coarse woody debris carbon
(kgC/m2) litter carbon, labile pool
(kgC/m2) litter carbon, unshielded cellulose pool
(kgC/m2) litter carbon, shielded cellulose pool
(kgC/m2) litter carbon, lignin pool
(kgC/m2) soil carbon, fast microbial recycling pool
(kgC/m2) soil carbon, medium microbial recycling pool
(kgC/m2) soil carbon, slow microbial recycling pool
(kgC/m2) soil carbon, recalcitrant SOM (slowest)
N_STATE (keyword) start of nitrogen state variable initialization block
(kgN/m2) litter nitrogen, labile pool
(kgN/m2) soil nitrogen, mineral pool

46. Biome-BGC Initialization file, continued
OUTPUT_CONTROL (keyword - do not remove)
outputs/oth (text) prefix for output files
1 (flag) 1 = write daily output 0 = no daily output
1 (flag) 1 = monthly avg of daily variables 0 = no monthly avg
1 (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)
(int) number of daily variables to output
summary.daily_gpp
summary.daily_mr
summary.daily_gr
summary.daily_hr
summary.daily_fire
summary.vegc
summary.litrc
summary.soilc
21 summary.totalc
ANNUAL_OUTPUT (keyword)
(int) number of annual output variables
annual maximum projected LAI
1 vegetation C
END_INIT (keyword) indicates the end of the initialization file

47. Verification of BIOME-BGC Daily and Seasonal Dynamics: Comparisons with Tower Eddy-flux Measurements
Mature Black Spruce Stand (NSA-OBS Ameriflux site)
Mature Aspen Stand (SSA-OA BERMS site)
NEP ET
Kimball et al., 1997a,b
validating bgc with boreal sites