FOREST-BGC (FOREST BioGeoChemical process model)

FOREST-BGC treats canopy interception and evaporation, transpiration, photosynthesis, growth and maintenance respiration, carbon allocation above and below-ground, litterfall, decomposition and nitrogen mineralization.

canopyinterceptionevaporationtranspirationphotosynthesisgrowth
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Classification(s)

Application-focused categoriesNatural-perspectiveLand regions
Application-focused categoriesNatural-perspectiveAtmospheric regions

Model Description

English {{currentDetailLanguage}} English

Quoted from: https://www.bgc-jena.mpg.de/TEE/software/bgc-md/vegetation/Running1988EcologicalModelling-V0001/Report.html 

The model depicted in this document considers carbon allocation with a process based approach. It was originally described by S. W. Running & Coughlan (1988).

Abstract

An ecosystem process model is described that calculates the carbon, water and nitrogen cycles through a forest ecosystem. The model, FOREST-BGC, treats canopy interception and evaporation, transpiration, photosynthesis, growth and maintenance respiration, carbon allocation above and below-ground, litterfall, decomposition and nitrogen mineralization. The model uses leaf area index (LAI) to quantify the forest structure important for energy and mass exchange, and this represents a key simplification for regional scale applications. FOREST-BGC requires daily incoming short-wave radiation, air temperature, dew point, and precipitation as driving variables. The model was used to simulate the annual hydrologic balance and net primary production of a hypothetical forest stand in seven contrasting environments across North America for the year 1984. Hydrologic partitioning ranged from 14/86/0% for evaporation, transpiration and outflow, respectively, in Fairbanks, AK (annual precipitation of 313 mm) to 10/27/66% in Jacksonville, FL (annual ppt of 1244 mm), and these balances changed as LAI was increased from 3 to 9 in successive simulations. Net primary production (npp) ranged from 0.0 t C ha-1 year-1 at Tucson, AZ, to 14.1 t C ha-1 year-1 at Knoxville, TN and corresponded reasonably with observed values at each site. The sensitivity of ecosystem processes to varying LAI in different climates was substantial, and underscores the utility of parameterizing this model at regional scales in the future with forest LAI measurements derived from satellite imagery. ?? 1988.

Space Scale

site

Available parameter values

Information on given parameter sets
Abbreviation Source
Original dataset of the publication S. W. Running & Coughlan (1988)
Additional set 1 Hunt Jr, Martin, & Running (1991)
Additional set 2 Korol, Running, Milner, & Hunt (1991)

State Variables

The following table contains the available information regarding this section:

Information on State Variables
Name Description
CfCf Carbon in foliage
CrCr Carbon in roots
CwCw Carbon in woody tissue

Allocation Coefficients

The following table contains the available information regarding this section:

Information on Allocation Coefficients
Name Type Values

Original dataset of the publication
Additional set 1 Additional set 2
ηfηf parameter 1414 1515 12251225
ηrηr parameter 2525 11201120 3710037100
ηwηw parameter 720720 1414 320320

Cycling Rates

The following table contains the available information regarding this section:

Information on Cycling Rates
Name Entry Author Orcid Type Values

Original dataset of the publication
Additional set 1 Additional set 2
γfγf 0000-0002-0046-1160 parameter 3310033100 - -
γrγr 0000-0002-0046-1160 parameter 2525 3434 3434
γwγw 0000-0002-0046-1160 parameter 00 - -

Components

The following table contains the available information regarding this section:

Information on Components
Name Description Expressions
xx vector of states for vegetation x=⎡⎣⎢CfCrCw⎤⎦⎥x=[CfCrCw]
uu scalar function of photosynthetic inputs -
bb vector of partitioning coefficients of photosynthetically fixed carbon b=⎡⎣⎢ηfηrηw⎤⎦⎥b=[ηfηrηw]
AA matrix of turnover (cycling) rates A=⎡⎣⎢γf000γr000γw⎤⎦⎥A=[−γf000−γr000−γw]
fvfv the righthandside of the ode fv=ub+Axfv=ub+Ax

Pool model representation

  Flux description

Figure 1
Figure 1: Pool model representation

Input fluxes

Cf:ηfuCf:ηf⋅u
Cr:ηruCr:ηr⋅u
Cw:ηwuCw:ηw⋅u

Output fluxes

Cf:CfγfCf:Cf⋅γf
Cr:CrγrCr:Cr⋅γr
Cw:CwγwCw:Cw⋅γw

The right hand side of the ODE

⎡⎣⎢Cfγf+ηfuCrγr+ηruCwγw+ηwu⎤⎦⎥[−Cf⋅γf+ηf⋅u−Cr⋅γr+ηr⋅u−Cw⋅γw+ηw⋅u]

The Jacobian (derivative of the ODE w.r.t. state variables)

⎡⎣⎢γf000γr000γw⎤⎦⎥[−γf000−γr000−γw]

Steady state formulas

Cf=ηfγfuCf=ηfγf⋅u
Cr=ηrγruCr=ηrγr⋅u
Cw=ηwγwuCw=ηwγw⋅u

Steady states (potentially incomplete), according jacobian eigenvalues, damping ratio

Parameter set: Original dataset of the publication

Cf:2533uCf:2533⋅uCr:uCr:uCw:CwCw:Cw

λ1:0.000λ1:0.000
λ2:0.400λ2:−0.400
λ3:0.330λ3:−0.330

Parameter set: Additional set 1

Cf:u5γfCf:u5⋅γfCr:1115uCr:1115⋅uCw:u4γwCw:u4⋅γw

λ1:γwλ1:−γw
λ2:0.75λ2:−0.75
λ3:γfλ3:−γf

Parameter set: Additional set 2

Cf:12u25γfCf:12⋅u25⋅γfCr:3775uCr:3775⋅uCw:3u20γwCw:3⋅u20⋅γw

λ1:γwλ1:−γw
λ2:0.75λ2:−0.75
λ3:γfλ3:−γf

References

Hunt Jr, E. R., Martin, F. C., & Running, S. W. (1991). Simulating the effects of climatic variation on stem carbon accumulation of a ponderosa pine stand: Comparison with annual growth increment data. Tree Physiology, 9(1_2), 161–171. http://doi.org/10.1093/treephys/9.1-2.161

Korol, R. L., Running, S. W., Milner, K. S., & Hunt, E. R. (1991). TESTING a mECHANISTIC cARBON bALANCE mODEL aGAINST oBSERVED tREE gROWTH. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere, 21(7), 1098–1105. http://doi.org/10.1139/x91-151

Running, S. W., & Coughlan, J. C. (1988). A general model of forest ecosystem processes for regional applications i. hydrologic balance, canopy gas exchange and primary production processes. Ecological Modelling, 42(2), 125–154. http://doi.org/10.1016/0304-3800(88)90112-3

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How to Cite

FOREST-BGC team (2020). FOREST-BGC (FOREST BioGeoChemical process model), Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/e0ce4b0e-06ef-4dd8-b0dc-71e7f67ed9eb
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