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MIMICS2_testing_reverse_modfPHYS_Sept7_2016.R
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MIMICS2_testing_reverse_modfPHYS_Sept7_2016.R
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# Will Wieder
# Oct 23, 2013
# Modified Aug, 2015; April 2016
# March 2017, added litter removal, 70% clay,50 y simulation
# Solve a system of non-linear equations for enzyme SOC solution
# uses packages deSolve / rootSolve
rm(list=ls())
dir <- "/Users/wwieder/Desktop/Working_files/soilCN/enzyme/Theory_2/Sulman_microbialModels/"
setwd(dir)
library(rootSolve)
library(boot)
#----------------analytical solutin using stode function-----------------------
#REVERSE MODEL
RXEQ <- function(t, y, pars) {
with (as.list(c(y, pars)),{
#Flows to and from MIC_1
LITmin[1] = MIC_1 * VMAX[1] * LIT_1 / (KM[1] + MIC_1) #MIC_1 decomp of MET lit
LITmin[2] = MIC_1 * VMAX[2] * LIT_2 / (KM[2] + MIC_1) #MIC_1 decomp of STRUC lit
MICtrn[1] = MIC_1 * tau[1] * fPHYS[1] #MIC_1 turnover to PHYSICAL SOM
MICtrn[2] = MIC_1 * tau[1] * fCHEM[1] #MIC_1 turnover to CHEMICAL SOM
MICtrn[3] = MIC_1 * tau[1] * fAVAI[1] #MIC_1 turnover to AVAILABLE SOM
SOMmin[1] = MIC_1 * VMAX[3] * SOM_3 / (KM[3] + MIC_1) #decomp of SOMa by MIC_1
#Flows to and from MIC_2
LITmin[3] = MIC_2 * VMAX[4] * LIT_1 / (KM[4] + MIC_2) #decomp of MET litter
LITmin[4] = MIC_2 * VMAX[5] * LIT_2 / (KM[5] + MIC_2) #decomp of SRUCTURAL litter
MICtrn[4] = MIC_2 * tau[2] * fPHYS[2] #MIC_2 turnover to PHYSICAL SOM
MICtrn[5] = MIC_2 * tau[2] * fCHEM[2] #MIC_2 turnover to CHEMICAL SOM
MICtrn[6] = MIC_2 * tau[2] * fAVAI[2] #MIC_2 turnover to AVAILABLE SOM
SOMmin[2] = MIC_2 * VMAX[6] * SOM_3 / (KM[6] + MIC_2) #decomp of SOMa by MIC_2
DEsorb = SOM_1 * desorb #* (MIC_1 + MIC_2) #desorbtion of PHYS to AVAIL (function of fCLAY)
OXIDAT = ((MIC_2 * VMAX[5] * SOM_2 / (KO[2]*KM[5] + MIC_2)) +
(MIC_1 * VMAX[2] * SOM_2 / (KO[1]*KM[2] + MIC_1))) #oxidation of C to A
dLIT_1 = I[1]*(1-FI[1]) - LITmin[1] - LITmin[3]
dMIC_1 = CUE[1]*(LITmin[1]+ SOMmin[1]) + CUE[2]*(LITmin[2]) - sum(MICtrn[1:3])
dSOM_1 = I[1]*FI[1] + MICtrn[1] + MICtrn[4]- DEsorb
dLIT_2 = I[2] * (1-FI[2]) - LITmin[2] - LITmin[4]
dMIC_2 = CUE[3]*(LITmin[3]+ SOMmin[2]) + CUE[4]*(LITmin[4]) - sum(MICtrn[4:6])
dSOM_2 = I[2]*FI[2] + MICtrn[2] + MICtrn[5] - OXIDAT
dSOM_3 = MICtrn[3] + MICtrn[6] + DEsorb + OXIDAT - SOMmin[1] - SOMmin[2]
list(c(dLIT_1, dLIT_2, dMIC_1, dMIC_2, dSOM_1, dSOM_2, dSOM_3))
})
}
#---------------------------------------------------------
# (A) Read in parameters and site level data
#---------------------------------------------------------
para_file <- paste("parameters_LIDET-MIM-REV_test_lowKm.csv", sep = "")
parameters <- read.csv(para_file)
names(parameters)
attach(parameters)
data <- read.csv("Test_SITES_1.csv", sep = ",") #site level forcing variables
names(data)
attach(data)
ANPP <- ANPP # if needed, convert to gC/m2/y from g/m2/y
clay <- CLAY/100 # if needed, convert from % clay to fraction
tsoi <- MAT
nsites <- length(Site)
FI <- FI * 0.1 #reduce FI by fraction of 10, as fPHYS
lig <- LIG
Nnew <- N #N in litter additions
fMET1 <- fmet_p[1] * (fmet_p[2] - fmet_p[3] * lig / Nnew) #as partitioned in Daycent
MIMLIT <- rep(NA, nsites) #Vector for results
MIMMIC <- rep(NA, nsites)
MIM_CO <- rep(NA, nsites)
MIMSOC <- rep(NA, nsites)
strSite <- as.character(data$Site) #convert site names to string
pools <- c('site','LITm', 'LITs', 'MICr', 'MICK', 'SOMp', 'SOMc', 'SOMa')
POOLS <- c("LIT","MIC","SOC")
exper <- c("Control","Warm2","Warm5", "1.3xLitter","2.0xLitter",
"Prime_1.3","Warm2_1.3xLitter",'Warm2_1.3xprime',"Prime_1.3_fMET",
"0xLitter","0xLitter_lowMicTurn")
npools <- length(POOLS)
nexper <- length(exper)
nday <- 365 * 60 #SPEEDS up exploration, ultimately want to be 50 years
LITpool<- c('LITm', 'LITs')
MICpool<- c('MICr', 'MICk')
SOMpool<- c('SOMp', 'SOMa','SOMc')
ALLpools <- c(LITpool, MICpool, SOMpool,'CO2','INPUTS')
LIT <- array(NA, dim = c(nsites,nexper,2,nday), dimnames = list(strSite,exper,LITpool,rep(NA, nday)))
MIC <- array(NA, dim = c(nsites,nexper,2,nday), dimnames = list(strSite,exper,MICpool,rep(NA, nday)))
SOM <- array(NA, dim = c(nsites,nexper,3,nday), dimnames = list(strSite,exper,SOMpool,rep(NA, nday)))
dim(LIT)
#---------------------------------------------------------
#---------------------------------------------------------
# (B) RXEQ for site using STODE function
# (C) Generate times series w/o inputs
#---------------------------------------------------------
#---------------------------------------------------------
#for (i in 1:nsites) { #speeds up debugging
for (i in 1:2) { #speeds up debugging
fMET <- fMET1[i]
fCLAY <- clay[i]
TSOI <- tsoi[i]
EST_LIT_in <- ANPP[i] / (365*24) # gC/m2/h (from gC/m2/y)
depth <- parameters$Depth[1]
h2y <- 24*365
MICROtoECO <- depth * 1e4 * 1e-3 #mgC/cm3 to g/m2
EST_LIT <- EST_LIT_in * 1e3 / 1e4 #mgC/cm2/h(from gC/m2/h)
#-----------------caclulate parameters---------------------------
Vmax <- exp(TSOI * Vslope + Vint) * aV
Km <- exp(Kslope * TSOI + Kint) * aK
#ANPP strongly correlated with MAP
Tau_MOD1 <- sqrt(ANPP[i]/Tau_MOD[1]) # basicaily standardize against NWT
Tau_MOD2 <- Tau_MOD[4] # increased 3-fold for SS SOC pools
Tau_MOD1[Tau_MOD1 < Tau_MOD[2]] <- Tau_MOD[2] # correction not used in LIDET resutls
Tau_MOD1[Tau_MOD1 > Tau_MOD[3]] <- Tau_MOD[3]
tau <- c(tau_r[1]*exp(tau_r[2]*fMET),
tau_K[1]*exp(tau_K[2]*fMET))
tau <- tau * Tau_MOD1 * Tau_MOD2
#------NEW Parameters--------------
fPHYS <- c(fPHYS_r[1] * exp(fPHYS_r[2]*fCLAY),
fPHYS_K[1] * exp(fPHYS_K[2]*fCLAY)) #fraction to SOMp
fPHYS <- fPHYS * 0.1 #reduce fraction to fPHYS
fCHEM <- c(fCHEM_r[1] * exp(fCHEM_r[2]*fMET) * fCHEM_r[3],
fCHEM_K[1] * exp(fCHEM_K[2]*fMET) * fCHEM_K[3]) #fraction to SOMc
fAVAI <- 1- (fPHYS + fCHEM)
desorb <- fSOM_p[1] * exp(fSOM_p[2]*(fCLAY)) #CHANGED FOR GLOBAL RUN!!!
pSCALAR <- PHYS_scalar[1] * exp(PHYS_scalar[2]*(sqrt(fCLAY))) #Scalar for texture effects on SOMp
desorb <- desorb * 0.1
#------------MODIFY fluxes from SOM pools as function of clay content---------
v_MOD <- vMOD
k_MOD <- kMOD # to avoid writing over orig. parameters
k_MOD[3] <- k_MOD[3] * pSCALAR
k_MOD[6] <- k_MOD[6] * pSCALAR
VMAX <- Vmax * v_MOD
KM <- Km / k_MOD
I <- array(NA, dim=2) #Litter inputs to MET/STR
I[1] <- (EST_LIT / depth) * fMET #partitioned to layers
I[2] <- (EST_LIT / depth) * (1-fMET)
#initialize pools
lit <- I # * 1e3
mic <- I # * 1e2
som <- rep(NA, 3)
som[1] <- I[1]
som[2] <- I[2]
som[3] <- I[1]
LITmin <- rep(NA, dim=4)
MICtrn <- rep(NA, dim=6)
SOMmin <- rep(NA, dim=2)
DEsorb <- rep(NA, dim=1)
OXIDAT <- rep(NA, dim=1)
#Calculate RXEQ pools
Tpars <- c( I = I, VMAX = VMAX, KM = KM, CUE = CUE,
fPHYS = fPHYS, fCHEM = fCHEM, fAVAI = fAVAI, FI = FI,
tau = tau, LITmin = LITmin, SOMmin = SOMmin, MICtrn = MICtrn,
desorb = desorb, DEsorb = DEsorb, OXIDAT = OXIDAT, KO = KO)
Ty <- c( LIT_1 = lit[1], LIT_2 = lit[2],
MIC_1 = mic[1], MIC_2 = mic[2],
SOM_1 = som[1], SOM_2 = som[2], SOM_3 = som[3])
test <- stode(y = Ty, time = 1e6, fun = RXEQ, parms = Tpars, positive = TRUE)
remove(lit, mic, som, I)
# ----------------------------------------------------------
# Generate plots of transient results
# ----------------------------------------------------------
#initialize arrays to store daily output data
day <- seq(1,nday,1)
year <- day/365
for (j in 1:nexper) {
# for (j in 10:10) { #speeds up debugging
dataOUT <- array(NA, dim =c(nday,length(ALLpools)), dimnames = list(seq(1,nday,1),ALLpools))
doy <- 1
LIT_1 <- test[[1]][[1]] #initialize pools
LIT_2 <- test[[1]][[2]]
MIC_1 <- test[[1]][[3]]
MIC_2 <- test[[1]][[4]]
SOM_1 <- test[[1]][[5]]
SOM_2 <- test[[1]][[6]]
SOM_3 <- test[[1]][[7]]
TSOI <- tsoi[i]
for (d in 1:nday) {
I <- array(NA, dim=2) #Litter inputs to MET/STR
I[1] <- (EST_LIT / depth) * fMET
I[2] <- (EST_LIT / depth) * (1-fMET)
fMET <- fMET1[i]
# define each manipulation (j) here
if (d > 3650) { #speed up simulation
if (j == 2) { TSOI = tsoi[i] + 2 }
if (j == 3) { TSOI = tsoi[i] + 5 }
if (j == 4) { I = I * 1.3 }
if (j == 5) { I = I * 2. }
if (j == 6) { I[1] = I[1] * 1.3 }
if (j == 7) { TSOI = tsoi[i] + 2
I = I * 1.3 }
if (j == 8) { TSOI = tsoi[i] + 2
I[1] = I[1] * 1.3 }
if (j == 9) { I[1] = I[1] * 1.3
fMET = I[1] / sum(I) }
if (j == 10){ I = I * 0. }
if (j == 11){ I = I * 0.
Tau_MOD1 <- sqrt(ANPP[i]*0/Tau_MOD[1]) # modify tau accordingly
Tau_MOD2 <- Tau_MOD[4]
Tau_MOD1[Tau_MOD1 < Tau_MOD[2]] <- Tau_MOD[2]
Tau_MOD1[Tau_MOD1 > Tau_MOD[3]] <- Tau_MOD[3]
tau <- c(tau_r[1]*exp(tau_r[2]*fMET),
tau_K[1]*exp(tau_K[2]*fMET))
tau <- tau * Tau_MOD1 * Tau_MOD2
}
} # close manipulation loop
# re-calculate parameters
Vmax <- exp(Vslope * TSOI + Vint) * aV
Km <- exp(Kslope * TSOI + Kint) * aK
VMAX <- Vmax * v_MOD
KM <- Km / k_MOD
tau <- c(tau_r[1]*exp(tau_r[2]*fMET),
tau_K[1]*exp(tau_K[2]*fMET))
tau <- tau * Tau_MOD1 * Tau_MOD2
fCHEM <- c(fCHEM_r[1] * exp(fCHEM_r[2]*fMET) * fCHEM_r[3],
fCHEM_K[1] * exp(fCHEM_K[2]*fMET) * fCHEM_K[3]) #fraction to SOMc
fAVAI <- 1- (fPHYS + fCHEM)
for (h in 1:24) {
UPpars <- c( I = I, VMAX = VMAX, KM = KM, CUE = CUE,
fPHYS = fPHYS, fCHEM = fCHEM, fAVAI = fAVAI, FI = FI,
tau = tau, LITmin = LITmin, SOMmin = SOMmin, MICtrn = MICtrn,
desorb= desorb, DEsorb = DEsorb, OXIDAT = OXIDAT, KO = KO)
UPy <- c( LIT_1 = LIT_1, LIT_2 = LIT_2,
MIC_1 = MIC_1, MIC_2 = MIC_2,
SOM_1 = SOM_1, SOM_2 = SOM_2, SOM_3 = SOM_3 )
# seperately calculate CO2 fluxes
LITmin1 = MIC_1 * VMAX[1] * LIT_1 / (KM[1] + MIC_1) #MIC_1 decomp of MET lit
LITmin2 = MIC_1 * VMAX[2] * LIT_2 / (KM[2] + MIC_1) #MIC_1 decomp of STRUC lit
SOMmin1 = MIC_1 * VMAX[3] * SOM_3 / (KM[3] + MIC_1) #decomp of SOMa by MIC_1
LITmin3 = MIC_2 * VMAX[4] * LIT_1 / (KM[4] + MIC_2) #decomp of MET litter
LITmin4 = MIC_2 * VMAX[5] * LIT_2 / (KM[5] + MIC_2) #decomp of SRUCTURAL litter
SOMmin2 = MIC_2 * VMAX[6] * SOM_3 / (KM[6] + MIC_2) #decomp of SOMa by MIC_2
CO2 = (1-CUE[1])*(LITmin1+ SOMmin1) + (1-CUE[2])*(LITmin2) +
(1-CUE[3])*(LITmin3+ SOMmin2) + (1-CUE[4])*(LITmin4) #mgC/cm3/h
update <- RXEQ(y = UPy, pars = UPpars)
LIT_1 <- LIT_1 + update[[1]][1]
LIT_2 <- LIT_2 + update[[1]][2]
MIC_1 <- MIC_1 + update[[1]][3]
MIC_2 <- MIC_2 + update[[1]][4]
SOM_1 <- SOM_1 + update[[1]][5]
SOM_2 <- SOM_2 + update[[1]][6]
SOM_3 <- SOM_3 + update[[1]][7]
if (h == 24) { #write out daily results
LIT[i,j,1,d] <- LIT_1
LIT[i,j,2,d] <- LIT_2
MIC[i,j,1,d] <- MIC_1
MIC[i,j,2,d] <- MIC_2
SOM[i,j,1,d] <- SOM_1
SOM[i,j,2,d] <- SOM_2
SOM[i,j,3,d] <- SOM_3
dataOUT[d,1] <- LIT_1
dataOUT[d,2] <- LIT_2
dataOUT[d,3] <- MIC_1
dataOUT[d,4] <- MIC_2
dataOUT[d,5] <- SOM_1
dataOUT[d,6] <- SOM_2
dataOUT[d,7] <- SOM_3
dataOUT[d,8] <- CO2 # mgC/cm3/h
dataOUT[d,9] <- sum(I)
if (doy == 365) { #advancy day of year counter
doy <- 1
print(paste(strSite[i], " ",exper[j], " finished year ", year[d],sep=""))
} else {
doy <- doy + 1
} #close day of year counter
remove(UPpars, UPy, update)
} #close daily results counter
} #close hour loop
} #close daily loop
# write out results for each experiment
dout <- paste('Time_series/data/MIMICS_',exper[j],"_CLAY",CLAY[i],"_LIG",lig[i],'.csv', sep='')
write.csv(dataOUT, file=dout)
# plot change in stocks over time
fout <- paste("Time_series/MOD_fPHYS",exper[j],"_",strSite[i],"_Reverse.pdf", sep="")
pdf(fout)
par(mfrow=c(3,1), mar=c(4,4,1,1))
plot(year, LIT[i,j,1,], lwd=3,
main = paste(strSite[i]," ",exper[j]),
ylim = c(min(LIT, na.rm=T)*0.7, max(LIT,na.rm=T))*1.15,
type ="l", xlab="" )
lines(year, LIT[i,j,2,], lwd=3, col = 2)
abline(h=test[[1]][[1]], col=1, lty=2)
abline(h=test[[1]][[2]], col=2, lty=2)
legend("topright", legend=c("Met","Struc"), col=c(1,2), lty = 1,
lwd = 3, cex=1.3, bty="n")
plot(year, MIC[i,j,1,], lwd=3, type ="l", xlab="",
ylim=c(min(MIC, na.rm=T)*0.7, max(MIC, na.rm=T))*1.15)
lines(year, MIC[i,j,2,], lwd=3, col = 2)
abline(h=test[[1]][[3]], col=1, lty=2)
abline(h=test[[1]][[4]], col=2, lty=2)
legend("topright", legend=c("Mic_r","Mic_K"), col=c(1,2), lty = 1,
lwd = 3, cex=1.3, bty="n")
plot(year, SOM[i,j,1,], lwd=3, type ="l",
ylim=c(min(SOM, na.rm=T)*0.7, max(SOM, na.rm=T))*1.15)
lines(year, SOM[i,j,2,], lwd=3, col = 2)
lines(year, SOM[i,j,3,], lwd=3, col = 4)
abline(h=test[[1]][[5]], col=1, lty=2)
abline(h=test[[1]][[6]], col=2, lty=2)
abline(h=test[[1]][[7]], col=4, lty=2)
legend("topright", legend=c("Phys","Chem","Avail"), col=c(1,2,4), lty = 1,
lwd = 3, cex=1.3, bty="n")
dev.next()
# -- changes w/ perturbations --
if (j > 1) {
LITdiff_m <- 100 * (LIT[i,j,,] / LIT[i,1,,] - 1)
MICdiff_m <- 100 * (MIC[i,j,,] / MIC[i,1,,] - 1)
SOMdiff_m <- 100 * (SOM[i,j,,] / SOM[i,1,,] - 1)
plot( year, LITdiff_m[1,], col=1, type ="l", lwd = 3,
ylim = c(min(LITdiff_m, na.rm=T)*0.85, max(LITdiff_m, na.rm=T))*1.15,
xlab="",
main = paste(strSite[i]," ",exper[j]))
lines(year, LITdiff_m[2,], col=2,lwd = 3)
abline(h=0, col=1, lty=2)
legend("topleft", legend=c("Met","Struc"), col=c(1,2), lty = 1,
lwd = 3, cex=1.3, bty="n")
plot( year, MICdiff_m[1,], col=1, type ="l", lwd = 3,
xlab="",
ylim=c(min(MICdiff_m, na.rm=T)*0.85, max(MICdiff_m, na.rm=T))*1.15)
lines(year, MICdiff_m[2,], col=2, lwd = 3)
abline(h=0, col=1, lty=2)
legend("topleft", legend=c("Mic_r","Mic_K"), col=c(1,2), lty = 1,
lwd = 3, cex=1.3, bty="n")
plot( year, SOMdiff_m[1,], col=1, type ="l", lwd = 3,
ylim=c(min(SOMdiff_m, na.rm=T)*0.85, max(SOMdiff_m, na.rm=T))*1.15)
lines(year, SOMdiff_m[2,], col=2, lwd = 3)
lines(year, SOMdiff_m[3,], col=4, lwd = 3)
abline(h=0, col=1, lty=2)
legend("topleft", legend=c("Phys","Chem","Avail"), col=c(1,2,4), lty = 1,
lwd = 3, cex=1.3, bty="n")
dev.next()
} #close difference plots
plot(year, dataOUT[,8], lwd=3, type ="l",
main = paste(strSite[i]," ",exper[j]))
lines(year, dataOUT[,9], lwd=3, col=3)
legend("topright", legend=c("CO2","Inputs"), col=c(1,3), lty = 1,
lwd = 3, cex=1.3, bty="n")
dev.off()
print(paste('wrote ',fout))
} # close j loop (for each experiment)
remove(test, Ty, Tpars, fout,dout, fMET, I)
remove(LITmin, MICtrn, SOMmin)
} # close i loop (sites)
#------------ FINISHED MAIN LOOP------------------------
LITall <- (LIT[,,1,] + LIT[,,2,]) * MICROtoECO / 1e3 #kg/m2
MICall <- (MIC[,,2,] + MIC[,,2,]) * MICROtoECO / 1e3
SOMall <- (SOM[,,1,] + SOM[,,2,] + SOM[,,3,]) * MICROtoECO / 1e3
# change for sandy soils, low fmet
dLIT <- array(NA, dim = c(nsites,nexper,nday), dimnames = list(strSite,exper,rep(NA, nday)))
dMIC <- array(NA, dim = c(nsites,nexper,nday), dimnames = list(strSite,exper,rep(NA, nday)))
dSOM <- array(NA, dim = c(nsites,nexper,nday), dimnames = list(strSite,exper,rep(NA, nday)))
for (j in 1:nexper) {
dLIT[,j,] <- 100 * (LITall[,j,] / LITall[,1,] - 1)
dMIC[,j,] <- 100 * (MICall[,j,] / MICall[,1,] - 1)
dSOM[,j,] <- 100 * (SOMall[,j,] / SOMall[,1,] - 1)
}
dim(dLIT)
Site
fout <- ('Time_series/MOD_fPHYS_MIMICS_summary.pdf')
pdf(fout)
par(mfrow=c(2,2), mar=c(1,5,2,0), cex = 1.3)
plot( year, SOMall[1,1,], col = 1, lwd = 3, type='l',
main= "Clayey soils", xaxt="n",
ylim=c(min(SOMall[c(1,3),,], na.rm=T),max(SOMall[c(1,3),,], na.rm=T)),
ylab=expression(paste('SOM (kg C ',m^-2,')')))
for (i in 1:8) {
lines(year, SOMall[1,i,], col=i, lwd = 3, lty=1 )
lines(year, SOMall[3,i,], col=i, lwd = 2, lty=2 )
}
par(mar=c(1,3,2,2))
plot( year, SOMall[2,1,], col = 1, lwd = 3, type='l',
main = 'Sandy soils', xaxt="n",
ylim=c(min(SOMall[c(2,4),,], na.rm=T),max(SOMall[c(2,4),,], na.rm=T)))
for (i in 1:8) {
lines(year, SOMall[2,i,], col=i, lwd = 3, lty=1 )
lines(year, SOMall[4,i,], col=i, lwd = 2, lty=2 )
}
# -------------relative chagnes----------------------
par(mar=c(2,5,1,0))
plot( year, dSOM[1,1,], col = 1, lwd = 3, type='l',
ylim=c(-15,15),
ylab=expression(paste(Delta,' SOM (%)')))
for (i in 1:8) {
lines(year, dSOM[1,i,], col=i, lwd = 3, lty=1 )
lines(year, dSOM[3,i,], col=i, lwd = 2, lty=2 )
}
par(mar=c(2,3,1,2))
plot( year, dSOM[2,1,], col = 1, lwd = 3, type='l',
ylim=c(-15,15))
for (i in 1:8) {
lines(year, dSOM[2,i,], col=i, lwd = 3, lty=1 )
lines(year, dSOM[4,i,], col=i, lwd = 2, lty=2 )
}
dev.off()