SoilR (version 1.2.107)

ThreepFeedbackModel: Implementation of a three pool model with feedback structure

Description

This function creates a model for three pools connected with feedback. It is a wrapper for the more general function GeneralModel.

Usage

ThreepFeedbackModel(
  t,
  ks,
  a21,
  a12,
  a32,
  a23,
  C0,
  In,
  xi = 1,
  solver = deSolve.lsoda.wrapper,
  pass = FALSE
)

Arguments

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 euler or deSolve.lsoda.wrapper or any other user provided function with the same interface.

pass

if TRUE forces the constructor to create the model even if it is invalid

References

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.

See Also

There are other predefinedModels and also more general functions like Model.

Examples

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")