General Overview


Logo

This report is the result of the use of the Python 3.4 package Sympy (for symbolic mathematics), as means to translate published models to a common language. It was created by Verónika Ceballos-Núñez (Orcid ID: 0000-0002-0046-1160) on 17/7/2015, and was last modified on lm.

About the model

The model depicted in this document considers carbon allocation with a process based approach. It was originally described by C. S. C. Potter & Randerson (1993).

Abstract

This paper presents a modeling approach aimed at seasonal resolution of global climatic and edaphic controls on patterns of terrestrial ecosystem production and soil microbial respiration. We use satellite imagery (Advanced Very High Resolution Radiometer and International Satellite Cloud Climatology Project solar radiation), along with historical climate (monthly temperature and precipitation) and soil attributes (texture, C and N contents) from global (1°) data sets as model inputs. The Carnegie-Ames-Stanford approach (CASA) Biosphere model runs on a monthly time interval to simulate seasonal patterns in net plant carbon fixation, biomass and nutrient allocation, litterfall, soil nitrogen mineralization, and microbial CO\(_2\) production. The model estimate of global terrestrial net primary production is 48 Pg C yr\(^{-1}\) with a maximum light use efficiency of 0.39 g C MJ\(^{-1}\) PAR. Over 70% of terrestrial net production takes place between 30°N and 30°S latitude. Seasonal variations in atmospheric CO\(_2\) concentrations from three stations in the Geophysical Monitoring for Climate Change Flask Sampling Network correlate significantly with estimated net ecosystem production values by latitude. -from Authors

Space Scale

global

Available parameter values

Information on given parameter sets
Abbreviation Source
Original dataset of the publication C. S. C. Potter & Randerson (1993)
Tundra C. S. Potter (1999)
High-latitude forest C. S. Potter (1999)
Boreal coniferous forest C. S. Potter (1999)
Temperate grassland C. S. Potter (1999)
Mixed coniferous forest C. S. Potter (1999)
Temperate deciduous forest C. S. Potter (1999)
Desert and bare ground C. S. Potter (1999)
Semi-arid shrubland C. S. Potter (1999)
Savanna and woody grassland C. S. Potter (1999)
Tropical evergreen rain forest C. S. Potter (1999)

State Variables

The following table contains the available information regarding this section:

Information on State Variables
Name Description
\(C_{f}\) Carbon in foliage
\(C_{r}\) Carbon in roots
\(C_{w}\) Carbon in woody tissue

Photosynthetic Parameters

The following table contains the available information regarding this section:

Information on Photosynthetic Parameters
Name Description Expressions Type Values

Original dataset of the publication
Tundra High-latitude forest Boreal coniferous forest Temperate grassland Mixed coniferous forest Temperate deciduous forest Desert and bare ground Semi-arid shrubland Savanna and woody grassland Tropical evergreen rain forest
\(SOL\) Total solar radiation (SOL(x,t)) - variable - - - - - - - - - - -
\(FPAR\) Fraction of incoming PAR intercerpted by green vegetation (FPAR(x,t)) - variable - - - - - - - - - - -
\(IPAR\) Intercepted photosynthetically active radiation(IPAR(x,t)). The factor of 0.5 accounts for the fact that approx. half of SOL is in PAR waveband (0.4-0.7 \(\mu\)m) \(IPAR=0.5\,SOL\,FPAR\) variable - - - - - - - - - - -
\(\epsilon\) PAR use efficiency (\(\epsilon(x,t)\)). Function that depends on effects of temperature and water stress - variable - - - - - - - - - - -
\(NPP\) New production of plant biomass (NPP(x,t)) at a grid cell (\(x\)) in month \(t\) \(NPP=IPAR\,\epsilon\) variable - - - - - - - - - - -

Allocation Coefficients

The following table contains the available information regarding this section:

Information on Allocation Coefficients
Name Description Type Values

Original dataset of the publication
Tundra High-latitude forest Boreal coniferous forest Temperate grassland Mixed coniferous forest Temperate deciduous forest Desert and bare ground Semi-arid shrubland Savanna and woody grassland Tropical evergreen rain forest
\(\alpha_{f}\) Proportional allocation constant of available carbon allocated to foliage parameter \(\frac{1}{3}\) \(0.25\) \(0.3\) \(0.25\) \(0.45\) \(0.25\) \(0.3\) \(0.25\) \(0.25\) \(0.3\) \(0.25\)
\(\alpha_{r}\) Proportional allocation constant of available carbon allocated to roots parameter \(\frac{1}{3}\) \(0.25\) \(0.25\) \(0.25\) \(0.55\) \(0.25\) \(0.25\) \(0.25\) \(0.25\) \(0.25\) \(0.25\)
\(\alpha_{w}\) Proportional allocation constant of available carbon allocated to wood parameter \(\frac{1}{3}\) \(0.5\) \(0.45\) \(0.5\) - \(0.5\) \(0.45\) \(0.5\) \(0.5\) \(0.45\) \(0.5\)

Cycling Rates

The following table contains the available information regarding this section:

Information on Cycling Rates
Name Description Type Units Values

Original dataset of the publication
Tundra High-latitude forest Boreal coniferous forest Temperate grassland Mixed coniferous forest Temperate deciduous forest Desert and bare ground Semi-arid shrubland Savanna and woody grassland Tropical evergreen rain forest
\(\tau_{f}\) Residence time of carbon in foliage parameter \(years\) - \(1.5\) \(1\) \(2.5\) \(1.5\) \(1.5\) \(1\) \(1.5\) \(1.5\) \(1\) \(1.5\)
\(\tau_{r}\) Residence time of carbon in roots parameter \(years\) - \(3\) \(3\) \(3\) \(5\) \(3\) \(3\) \(3\) \(3\) \(5\) \(2\)
\(\tau_{w}\) Residence time of carbon in wood parameter \(years\) - \(50\) \(50\) \(50\) - \(40\) \(40\) \(50\) \(50\) \(25\) \(25\)

Components

The following table contains the available information regarding this section:

Information on Components
Name Description Expressions
\(x\) vector of states for vegetation \(x=\left[\begin{matrix}C_{f}\\C_{r}\\C_{w}\end{matrix}\right]\)
\(u\) scalar function of photosynthetic inputs \(u=NPP\)
\(b\) vector of partitioning coefficients of photosynthetically fixed carbon \(b=\left[\begin{matrix}\alpha_{f}\\\alpha_{r}\\\alpha_{w}\end{matrix}\right]\)
\(A\) matrix of turnover (cycling) rates \(A=\left[\begin{matrix}-\tau_{f} & 0 & 0\\0 & -\tau_{r} & 0\\0 & 0 & -\tau_{w}\end{matrix}\right]\)
\(f_{v}\) the righthandside of the ode \(f_{v}=u\,b+A\,x\)

Pool model representation

Flux description

Figure 1
Figure 1: Pool model representation

Input fluxes

\(C_{f}: 0.5\cdot FPAR\cdot SOL\cdot\alpha_{f}\cdot\epsilon\)
\(C_{r}: 0.5\cdot FPAR\cdot SOL\cdot\alpha_{r}\cdot\epsilon\)
\(C_{w}: 0.5\cdot FPAR\cdot SOL\cdot\alpha_{w}\cdot\epsilon\)

Output fluxes

\(C_{f}: C_{f}\cdot\tau_{f}\)
\(C_{r}: C_{r}\cdot\tau_{r}\)
\(C_{w}: C_{w}\cdot\tau_{w}\)

The right hand side of the ODE

\(\left[\begin{matrix}- C_{f}\cdot\tau_{f} + 0.5\cdot FPAR\cdot SOL\cdot\alpha_{f}\cdot\epsilon\\- C_{r}\cdot\tau_{r} + 0.5\cdot FPAR\cdot SOL\cdot\alpha_{r}\cdot\epsilon\\- C_{w}\cdot\tau_{w} + 0.5\cdot FPAR\cdot SOL\cdot\alpha_{w}\cdot\epsilon\end{matrix}\right]\)

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

\(\left[\begin{matrix}-\tau_{f} & 0 & 0\\0 & -\tau_{r} & 0\\0 & 0 & -\tau_{w}\end{matrix}\right]\)

Steady state formulas

\(C_{f} = \frac{0.5}{\tau_{f}}\cdot FPAR\cdot SOL\cdot\alpha_{f}\cdot\epsilon\)
\(C_{r} = \frac{0.5}{\tau_{r}}\cdot FPAR\cdot SOL\cdot\alpha_{r}\cdot\epsilon\)
\(C_{w} = \frac{0.5}{\tau_{w}}\cdot FPAR\cdot SOL\cdot\alpha_{w}\cdot\epsilon\)

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

Parameter set: Original dataset of the publication

\(C_f: \frac{0.166666666666667}{\tau_{f}}\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_r: \frac{0.166666666666667}{\tau_{r}}\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_w: \frac{0.166666666666667}{\tau_{w}}\cdot FPAR\cdot SOL\cdot\epsilon\)

\(\lambda_{1}: -\tau_{w}\)
\(\lambda_{2}: -\tau_{r}\)
\(\lambda_{3}: -\tau_{f}\)

Parameter set: Tundra

\(C_f: 0.0833333333333333\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_r: 0.0416666666666667\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_w: 0.005\cdot FPAR\cdot SOL\cdot\epsilon\)

\(\lambda_{1}: -1.500\)
\(\lambda_{2}: -3.000\)
\(\lambda_{3}: -50.000\)

Parameter set: High-latitude forest

\(C_f: 0.15\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_r: 0.0416666666666667\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_w: 0.0045\cdot FPAR\cdot SOL\cdot\epsilon\)

\(\lambda_{1}: -50.000\)
\(\lambda_{2}: -3.000\)
\(\lambda_{3}: -1.000\)

Parameter set: Boreal coniferous forest

\(C_f: 0.05\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_r: 0.0416666666666667\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_w: 0.005\cdot FPAR\cdot SOL\cdot\epsilon\)

\(\lambda_{1}: -3.000\)
\(\lambda_{2}: -50.000\)
\(\lambda_{3}: -2.500\)

Parameter set: Temperate grassland

\(C_f: 0.15\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_r: 0.055\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_w: \frac{0.5}{\tau_{w}}\cdot FPAR\cdot SOL\cdot\alpha_{w}\cdot\epsilon\)

\(\lambda_{1}: -\tau_{w}\)
\(\lambda_{2}: -5.0\)
\(\lambda_{3}: -1.5\)

Parameter set: Mixed coniferous forest

\(C_f: 0.0833333333333333\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_r: 0.0416666666666667\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_w: 0.00625\cdot FPAR\cdot SOL\cdot\epsilon\)

\(\lambda_{1}: -40.000\)
\(\lambda_{2}: -1.500\)
\(\lambda_{3}: -3.000\)

Parameter set: Temperate deciduous forest

\(C_f: 0.15\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_r: 0.0416666666666667\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_w: 0.005625\cdot FPAR\cdot SOL\cdot\epsilon\)

\(\lambda_{1}: -40.000\)
\(\lambda_{2}: -3.000\)
\(\lambda_{3}: -1.000\)

Parameter set: Desert and bare ground

\(C_f: 0.0833333333333333\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_r: 0.0416666666666667\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_w: 0.005\cdot FPAR\cdot SOL\cdot\epsilon\)

\(\lambda_{1}: -1.500\)
\(\lambda_{2}: -3.000\)
\(\lambda_{3}: -50.000\)

Parameter set: Semi-arid shrubland

\(C_f: 0.0833333333333333\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_r: 0.0416666666666667\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_w: 0.005\cdot FPAR\cdot SOL\cdot\epsilon\)

\(\lambda_{1}: -1.500\)
\(\lambda_{2}: -3.000\)
\(\lambda_{3}: -50.000\)

Parameter set: Savanna and woody grassland

\(C_f: 0.15\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_r: 0.025\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_w: 0.009\cdot FPAR\cdot SOL\cdot\epsilon\)

\(\lambda_{1}: -5.000\)
\(\lambda_{2}: -1.000\)
\(\lambda_{3}: -25.000\)

Parameter set: Tropical evergreen rain forest

\(C_f: 0.0833333333333333\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_r: 0.0625\cdot FPAR\cdot SOL\cdot\epsilon\), \(C_w: 0.01\cdot FPAR\cdot SOL\cdot\epsilon\)

\(\lambda_{1}: -1.500\)
\(\lambda_{2}: -2.000\)
\(\lambda_{3}: -25.000\)

References

Potter, C. S. (1999). Terrestrial biomass and the effects of deforestation on the global carbon cycle satellite observations. BioScience, 49(10), 769–778. http://doi.org/10.2307/1313568

Potter, C. S. C., & Randerson, J. (1993). Terrestrial ecosystem production: A process model based on global satellite and surface data. Global Biogeochemical Cycles, 7(4), 811–841. http://doi.org/10.1029/93GB02725