SoilR (version 1.0-0)

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)

Arguments

t

A vector containing the points in time where the solution is sought.

ks

A vector of lenght 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 ode or any other user provided function with the same interface.

Value

• A Model Object that can be further queried

See Also

ThreepParallelModel, ThreepSeriesModel

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")