Nothing
#
# vim:set ff=unix expandtab ts=2 sw=2:
ThreepParallelModel=structure(
function #Implementation of a three pool model with parallel structure
### The function creates a model for three independent (parallel) pools. It is a wrapper for the more general function
### \code{\link{ParallelModel}} that can handle an arbitrary number of pools.
##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.
(
t, ##<< A vector containing the points in time where the solution is sought.
ks, ##<< A vector of length 3 containing the decomposition rates for the 3 pools.
C0, ##<< A vector of length 3 containing the initial amount of carbon for the 3 pools.
In, ##<< A scalar or a data.frame object specifying the amount of litter inputs by time.
gam1, ##<< A scalar representing the partitioning coefficient, i.e. the proportion from the total amount of inputs that goes to pool 1.
gam2, ##<< A scalar representing the partitioning coefficient, i.e. the proportion from the total amount of inputs that goes to pool 2.
xi=1, ##<< A scalar or a data.frame specifying the external (environmental and/or edaphic) effects on decomposition rates.
solver=deSolve.lsoda.wrapper, ##<< A function that solves the system of ODEs. This can be \code{\link{euler}} or \code{\link{ode}} or any other user provided function with the same interface.
pass=FALSE
)
{
t_start=min(t)
t_end=max(t)
if(length(ks)!=3) stop("ks must be of length = 3")
if(length(C0)!=3) stop("the vector with initial conditions must be of length = 3")
if((gam1+gam2)^2 > 1) stop("The sum of the partitioning coefficients gam is outside the interval [0,1]")
if(gam1 < 0 | gam2 < 0) stop("Partitioning coefficients gam must be positive")
if(length(In)==1) inputrates_tm=BoundInFlux(
function(t){matrix(nrow=3,ncol=1,c(gam1*In,gam2*In,(1-gam1-gam2)*In))},
t_start,
t_end
)
if(class(In)=="data.frame"){
x=In[,1]
y=In[,2]
inputrate=function(t0){as.numeric(spline(x,y,xout=t0)[2])}
inputrates_tm=BoundInFlux(
function(t){matrix(nrow=3,ncol=1,c(gam1*inputrate(t),gam2*inputrate(t),(1-gam1-gam2)*inputrate(t)))},
min(x),
max(x)
)
}
if(length(xi)==1) fX=function(t){xi}
if(class(xi)=="data.frame"){
X=xi[,1]
Y=xi[,2]
fX=function(t){as.numeric(spline(X,Y,xout=t)[2])}
}
coeffs_tm=TimeMap(
function(times){fX(t)*(-1*abs(ks))},
min(t),
max(t)
)
res=ParallelModel(t,coeffs_tm,startvalues=C0,inputrates_tm,solver,pass=pass)
### A Model Object that can be further queried
##seealso<< \code{\link{TwopParallelModel}} and \code{\link{ParallelModel}}
}
,
ex=function(){
t_start=0
t_end=10
tn=50
timestep=(t_end-t_start)/tn
t=seq(t_start,t_end,timestep)
Ex=ThreepParallelModel(t,ks=c(k1=0.5,k2=0.2,k3=0.1),
C0=c(c10=100, c20=150,c30=50),In=20,gam1=0.7,gam2=0.1,xi=0.5)
Ct=getC(Ex)
plot(t,rowSums(Ct),type="l",lwd=2,
ylab="Carbon stocks (arbitrary units)",xlab="Time",ylim=c(0,sum(Ct[1,])))
lines(t,Ct[,1],col=2)
lines(t,Ct[,2],col=4)
lines(t,Ct[,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")
Rt=getReleaseFlux(Ex)
plot(t,rowSums(Rt),type="l",ylab="Carbon released (arbitrary units)",
xlab="Time",lwd=2,ylim=c(0,sum(Rt[1,])))
lines(t,Rt[,1],col=2)
lines(t,Rt[,2],col=4)
lines(t,Rt[,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")
}
)
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