Description Usage Arguments Details Value References Examples
Simulation of C4 photosynthesis based on the equations proposed by von Caemmerer (2000). At this point assimilation and stomatal conductance are not coupled and although, for example a lower relative humidity will lower stomatal conductance it will not affect assimilation. Hopefully, this will be improved in the future.
1 | eC4photo(Qp, airtemp, rh, ca, oa, vcmax, vpmax, vpr, jmax)
|
Qp |
quantum flux (micro mol m-2 s-1). |
airtemp |
air temperature (Celsius). |
rh |
relative humidity in proportion (e.g. 0.7). |
ca |
atmospheric carbon dioxide concentration (ppm or microbar) (e.g. 380). |
oa |
atmospheric oxygen concentration (mbar) (e.g. 210). |
vcmax |
Maximum rubisco activity (micro mol m-2 s-1). |
vpmax |
Maximum PEP carboxylase activity (micro mol m-2 s-1). |
vpr |
PEP regeneration rate (micro mol m-2 s-1). |
jmax |
Maximal electron transport rate (micromol electrons m-2 s-1). |
The equations are taken from von Caemmerer (2000) for the assimilation part and stomatal conductance is based on FORTRAN code by Joe Berry (translated to C).
a list
structure with components
Assim |
net assimilation rate (micro mol m-2 s-1). |
Gs |
stomatal conductance rate (micro mol m-2 s-1). |
Ci |
CO2 concentration in the bundle-sheath (microbar). |
Os |
oxygen evolution (mbar). |
Susanne von Caemmerer (2000) Biochemical Models of Leaf Photosynthesis. CSIRO Publishing. (In particular chapter 4).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | ## Not run:
## A simple example for the use of eC4photo
## This is the model based on von Caemmerer
## First we can compare the effect of varying
## Jmax. Notice that this is different from
## varying alpha in the Collatz model
Qps <- seq(0,2000,10)
Tls <- seq(0,55,5)
rhs <- c(0.7)
dat1 <- data.frame(expand.grid(Qp=Qps,Tl=Tls,RH=rhs))
res1 <- eC4photo(dat1$Qp,dat1$Tl,dat1$RH)
res2 <- eC4photo(dat1$Qp,dat1$Tl,dat1$RH,jmax=700)
## Plot comparing Jmax 400 vs. 700 for a range of conditions
xyplot(res1$Assim + res2$Assim ~ Qp | factor(Tl) , data = dat1,
type="l",col=c("blue","green"),lwd=2,
ylab=expression(paste("Assimilation (",
mu,mol," ",m^-2," ",s^-1,")")),
xlab=expression(paste("Quantum flux (",
mu,mol," ",m^-2," ",s^-1,")")),
key=list(text=list(c("Jmax 400","Jmax 700")),
lines=TRUE,col=c("blue","green"),lwd=2))
## Second example is the effect of varying Vcmax
Qps <- seq(0,2000,10)
Tls <- seq(0,35,5)
rhs <- 0.7
vcmax <- seq(0,40,5)
dat1 <- data.frame(expand.grid(Qp=Qps,Tl=Tls,RH=rhs,vcmax=vcmax))
res1 <- numeric(nrow(dat1))
for(i in 1:nrow(dat1)){
res1[i] <- eC4photo(dat1$Qp[i],dat1$Tl[i],dat1$RH[i],vcmax=dat1$vcmax[i])$Assim
}
## Plot comparing different Vcmax
cols <- rev(heat.colors(9))
xyplot(res1 ~ Qp | factor(Tl) , data = dat1,col=cols,
groups=vcmax,
type="l",lwd=2,
ylab=expression(paste("Assimilation (",
mu,mol," ",m^-2," ",s^-1,")")),
xlab=expression(paste("Quantum flux (",
mu,mol," ",m^-2," ",s^-1,")")),
key=list(text=list(as.character(vcmax)),
lines=TRUE,col=cols,lwd=2))
## End(Not run)
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