FREddyPro (version 1.0)

lue_model: Light use efficiency model

Description

A simple light use efficiency model for fitting NEE data.

Usage

lue_model(temp, par, vpd, swc, Topt, Tmin, Tmax, StandAge, fullCanAge,
k, lai, gamma, kappa, thetaWP, thetaFC, alpha, v, A, epsilon)

Arguments

temp

Air temperature (K)

par

Photosynthetic active radiation (umol/m2/s)

vpd

Vapour pressure deficit (Pa)

swc

Soil water content (unitless)

Topt

Optimal temperature for growth (oC)

Tmin

Minimum temperature for growth (oC)

Tmax

Maximum temperature for growth (oC)

StandAge

Age of the stand (years)

fullCanAge

Age at full canopy coluser (years)

k

Light extinction coefficient (unitless)

lai

Leaf area index (unitless)

gamma

Empirical parameter for light modifiers

kappa

Empirical parameter for vapour pressure modifiers

thetaWP

Volumetric water content at wilting point

thetaFC

Volumetric water content at field capacity

alpha

Empirical parameter for soil water

v

Empirical parameter for soil water

A

Empirical parameters for ecosystem respiration

epsilon

Empirical potential light use efficiency

Value

The output of the function is a list with three elements including gross primary production (GPP), ecosystem respiration (Re) and net ecosystem exchange (NEE).

Details

The model is based on the simple LUE model by Makela et al. 2008 with some small modification including functions for light interception, temperature modifier, and ecosystem respiration. Light interception and temperature modifiers are thosed used in the popular ecophysiological model 3-PG by Landsberg and Sands 1997. Light interception is based on Beer's law using a light extinction coefficient, leaf area index and canopy cover. Canopy cover is calculated from current stand age, and the age at full canopy cover. Ecosystem respiration is estimated using Arrhenius type function (Lloyd and Taylor, 1994) dependent on temperature.

References

Landsberg, J.J. and Waring, R.H. (1997). A generalised model of forest productivity using simplified concepts of radiationuse efficiency, carbon balance and partitioning. Forest Ecology and Management. 95, 209-228 Lloyd, J. and Taylor, A. (1994). On the temperature dependence of soil respiration. Function Ecology. 8, 315-323. Makela, A., Pulkkinen, M., Kolari, P., Lagergren, F., Berbigier, P., Lindroth, A., Loustau, D., Nikinmaa, E., Vesala, T. and Hari, P. (2008). Developing an empirical model of stand GPP with the LUE approach: analysis of eddy covariance data at five ontrasting conifer sites in Europe. Global Change Biology. 14, 92-108.

Examples

## Close any previously open graphic devices
graphics.off()

## Load the data
data(fluxes)

## Clean the fluxes
fluxes=cleanFluxes(fluxes,sdCor=TRUE,sdTimes=3,timesList=3,distCor=TRUE,
thresholdList=list(H=c(-100,1000),LE=c(-100,1000)))

## Input
PPFD=2500
swc=0.35

## Parameters
k = 0.5
Topt = 12
Tmin = -2
Tmax = 35
lai = 6
StandAge = 41
fullCanAge = 15

gamma = 0.0003
kappa = -0.0006
alpha = 0.3
v = 0.5
thetaWP = 0.4
thetaFC = 0.7
A = 200
epsilon = 0.0164 ## umol C / umol APAR

model<-lue_model( fluxes$air_temperature, 2500, fluxes$VPD, swc=0.35,
Topt, Tmin, Tmax, StandAge, fullCanAge, k, lai, gamma, kappa, thetaWP,
thetaFC, alpha, v, A, epsilon )

par(mfrow=c(3,1))
plot(model$NEE,type='l')
plot(model$GPP,type='l')
plot(model$Re,type='l')