| ThreepFeedbackModel {SoilR} | R Documentation |
This function creates a model for three pools connected with feedback. It is
a wrapper for the more general function GeneralModel.
ThreepFeedbackModel( t, ks, a21, a12, a32, a23, C0, In, xi = 1, solver = deSolve.lsoda.wrapper, pass = FALSE )
t |
A vector containing the points in time where the solution is sought. |
ks |
A vector of length 3 containing the values of the decomposition rates for pools 1, 2, and 3. |
a21 |
A scalar with the value of the transfer rate from pool 1 to pool 2. |
a12 |
A scalar with the value of the transfer rate from pool 2 to pool 1. |
a32 |
A scalar with the value of the transfer rate from pool 2 to pool 3. |
a23 |
A scalar with the value of the transfer rate from pool 3 to pool 2. |
C0 |
A vector containing the initial concentrations for the 3 pools. The length of this vector is 3 |
In |
A data.frame object specifying the amount of litter inputs by time. |
xi |
A scalar or data.frame object specifying the external (environmental and/or edaphic) effects on decomposition rates. |
solver |
A function that solves the system of ODEs. This can be
|
pass |
if TRUE forces the constructor to create the model even if it is invalid |
Sierra, C.A., M. Mueller, S.E. Trumbore. 2012. Models of soil organic matter decomposition: the SoilR package version 1.0. Geoscientific Model Development 5, 1045-1060.
There are other predefinedModels and also more
general functions like Model.
t_start=0
t_end=10
tn=50
timestep=(t_end-t_start)/tn
t=seq(t_start,t_end,timestep)
ks=c(k1=0.8,k2=0.4,k3=0.2)
C0=c(C10=100,C20=150, C30=50)
In = 60
Temp=rnorm(t,15,1)
TempEffect=data.frame(t,fT.Daycent1(Temp))
Ex1=ThreepFeedbackModel(t=t,ks=ks,a21=0.5,a12=0.1,a32=0.2,a23=0.1,C0=C0,In=In,xi=TempEffect)
Ct=getC(Ex1)
Rt=getReleaseFlux(Ex1)
plot(
t,
rowSums(Ct),
type="l",
ylab="Carbon stocks (arbitrary units)",
xlab="Time (arbitrary units)",
lwd=2,
ylim=c(0,sum(Ct[51,]))
)
lines(t,Ct[,1],col=2)
lines(t,Ct[,2],col=4)
lines(t,Ct[,3],col=3)
legend(
"topleft",
c("Total C","C in pool 1", "C in pool 2","C in pool 3"),
lty=c(1,1,1,1),
col=c(1,2,4,3),
lwd=c(2,1,1,1),
bty="n"
)
plot(
t,
rowSums(Rt),
type="l",
ylab="Carbon released (arbitrary units)",
xlab="Time (arbitrary units)",
lwd=2,
ylim=c(0,sum(Rt[51,]))
)
lines(t,Rt[,1],col=2)
lines(t,Rt[,2],col=4)
lines(t,Rt[,3],col=3)
legend(
"topleft",
c("Total C release",
"C release from pool 1",
"C release from pool 2",
"C release from pool 3"),
lty=c(1,1,1,1),
col=c(1,2,4,3),
lwd=c(2,1,1,1),
bty="n"
)
Inr=data.frame(t,Random.inputs=rnorm(length(t),50,10))
plot(Inr,type="l")
Ex2=ThreepFeedbackModel(t=t,ks=ks,a21=0.5,a12=0.1,a32=0.2,a23=0.1,C0=C0,In=Inr)
Ctr=getC(Ex2)
Rtr=getReleaseFlux(Ex2)
plot(
t,
rowSums(Ctr),
type="l",
ylab="Carbon stocks (arbitrary units)",
xlab="Time (arbitrary units)",
lwd=2,
ylim=c(0,sum(Ctr[51,]))
)
lines(t,Ctr[,1],col=2)
lines(t,Ctr[,2],col=4)
lines(t,Ctr[,3],col=3)
legend("topright",c("Total C","C in pool 1", "C in pool 2","C in pool 3"),
lty=c(1,1,1,1),col=c(1,2,4,3),lwd=c(2,1,1,1),bty="n")
plot(t,rowSums(Rtr),type="l",ylab="Carbon released (arbitrary units)",
xlab="Time (arbitrary units)",lwd=2,ylim=c(0,sum(Rtr[51,])))
lines(t,Rtr[,1],col=2)
lines(t,Rtr[,2],col=4)
lines(t,Rtr[,3],col=3)
legend(
"topright",
c("Total C release",
"C release from pool 1",
"C release from pool 2",
"C release from pool 3"
),
lty=c(1,1,1,1),
col=c(1,2,4,3),
lwd=c(2,1,1,1),
bty="n")