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RealTime_plot_evolpheno.R
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RealTime_plot_evolpheno.R
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##############################################################################/
##############################################################################/
#Plot the map of the RealTime experiment
##############################################################################/
##############################################################################/
source("RealTime_load.R")
##############################################################################/
#yearly evolution of the survival rate####
##############################################################################/
#limiting the data set to useful data
evolsurv<-dispo[dispo$family_simp!="CC" & dispo$family_simp!="hd" &
!is.na(dispo$an_mort) & dispo$an_mort!="g",
c("Sample_ID","bloc","PU","treat","an_mort","family_simp")]
evolsurv$grpbloc<-paste(evolsurv$bloc,evolsurv$PU,evolsurv$treat,sep="")
#defining a color vector
colovec<-c(brewer.pal(12,"Paired")[4],brewer.pal(12,"Paired")[2])
survEv<-t(apply(table(evolsurv$grpbloc,evolsurv$an_mort),1,cumsum))
survEv<-100*(survEv[,10]-survEv)/survEv[,10]
survEv<-survEv[,-10]
survEv.bloc<-factor(substr(rownames(survEv),1,2))
survEv.treat<-factor(substr(rownames(survEv),3,5))
matplot(t(survEv),type="b",ylim=c(0,100),las=1,
col=colovec[as.numeric(survEv.treat)],lwd=2,
lty=as.numeric(survEv.treat),
pch=c(0,15,1,2,3,16,17,5,6),
xaxt="n",yaxt="n",bty="n",
ylab="Percentage of survival",xlab="Year",
font.lab=2,cex.lab=1.5)
axis(1,lwd=2,cex.axis=1,at=c(1:dim(survEv)[2]),
lab=colnames(survEv),las=1,font=2)
axis(2,lwd=2,las=1,font=2)
box(lwd=2)
legend(1,55,legend=rep(NA,6),title="Natural\nexposure",title.adj=0,
col=colovec[1],lty=1,pch=c(22,21,24,3,23,25),pt.bg="white",
bty="n",cex=1.3,title.cex=1,y.intersp=1.5,x.intersp=0.5,lwd=2)
legend(3,55,legend=rep(NA,3),title="Protected\nexposure",title.adj=0,
col=colovec[2],lty=2,pch=c(15,16,17),pt.bg="white",
bty="n",cex=1.3,title.cex=1,y.intersp=1.5,x.intersp=0.5,lwd=2)
#export to .pdf 6 x 6 inches
##############################################################################/
#yearly level of infection####
##############################################################################/
#limiting the data set to useful data
evolMild<-dispo[dispo$family_simp!="CC" & dispo$family_simp!="hd" &
!is.na(dispo$an_mort) & dispo$an_mort!="g",
c("Sample_ID","bloc","PU","treat","family_simp",
"oid4_09","oid5_10","oid5_11","oid4_12","oid2_13",
"oid_16","oid_17","oid_moy")]
evolMild$oid_14<-0
evolMild$oid_15<-0
evolMild<-evolMild[,c("Sample_ID","bloc","PU","treat","family_simp",
"oid4_09","oid5_10","oid5_11","oid4_12","oid2_13",
"oid_14","oid_15","oid_16","oid_17","oid_moy")]
evolMild$grpbloc<-paste(evolMild$bloc,evolMild$PU,evolMild$treat,sep="")
colnames(evolMild)<-c("Sample_ID","bloc","PU","treat","family_simp",
"m2009","m2010","m2011","m2012","m2013",
"m2014","m2015","m2016","m2017","oid_moy","grpbloc")
#defining a color vector
colovec<-c(brewer.pal(12,"Paired")[4],brewer.pal(12,"Paired")[2])
infectM<-data.frame("expmean"=as.numeric(),"lowmean"=as.numeric(),
"expsd"=as.numeric(),"lowsd"=as.numeric())
for (i in 6:14) {
infectM<-rbind(infectM,
c(tapply(evolMild[,i],evolMild$treat,FUN=mean,na.rm=TRUE),
tapply(evolMild[,i],evolMild$treat,FUN=sd,na.rm=TRUE)))
}
colnames(infectM)<-c("expmean","lowmean","expsd","lowsd")
rownames(infectM)<-c(2009:2017)
temp1<-pivot_longer(infectM,cols=1:2,names_to="treat",values_to="mean")
graf<-barplot(temp1$mean,density=c(-1,20),angle=c(0,60),border=NA,
col=colovec,ylim=c(-1,105),ylab="Percentage of infection",
cex.axis=1,cex.lab=1.5,las=1,yaxt="n",bty="n",
space=c(0,0.25,rep(c(1,0.25),times=8)),font.lab=2)
axis(1,at=graf[seq(1,17,2)]+0.625,labels=rownames(infectM),
lwd=2,font=2,cex.axis=0.9)
axis(2,at=seq(0,100,20),labels=seq(0,100,20),lwd=2,las=1,
font=2,cex.axis=1)
box(bty="o",lwd=2)
#adding standard deviation
temp2<-pivot_longer(infectM,cols=3:4,names_to="treat",values_to="sd")
plotCI(x=graf,y=temp1$mean,
ui=temp1$mean+temp2$sd,
li=temp1$mean,
pch=NA,lwd=1.5,add=TRUE)
#for cosmetic reason, we superimpose again the barplot
par(lwd=2)
barplot(temp1$mean,density=c(-1,20),angle=c(0,60),border=colovec,
col=colovec,ylim=c(-1,105),ylab="Percentage of infection",
cex.axis=1,cex.lab=1.5,las=1,yaxt="n",bty="n",
space=c(0,0.25,rep(c(1,0.25),times=8)),font.lab=2,add=TRUE)
legend(-1,103,legend=c("Natural exposure","Protected exposure"),
fill=colovec,density=c(-1,20),angle=c(0,60),bty="n",border=colovec,
cex=1.3,y.intersp=1.5,x.intersp=0.5)
par(lwd=1)
#export to .pdf 6 x 6 inches
##############################################################################/
#yearly evolution of seedlings height####
##############################################################################/
#limiting the data set to useful data
evolHeight<-dispo[dispo$family_simp!="CC" & dispo$family_simp!="hd" &
!is.na(dispo$an_mort) & dispo$an_mort!="g",
c("Sample_ID","bloc","PU","treat","family_simp","H09v",
"H10v","H11v","H12v","H14v","H15v","H16v","H17v")]
evolHeight$grpbloc<-paste(evolHeight$bloc,evolHeight$PU,
evolHeight$treat,sep="")
#defining a color vector
colovec<-c(brewer.pal(12,"Paired")[4],brewer.pal(12,"Paired")[2])
HeighTr<-data.frame("expmean"=as.numeric(),"lowmean"=as.numeric(),
"expsd"=as.numeric(),"lowsd"=as.numeric())
for (i in 6:13) {
HeighTr<-rbind(HeighTr,
c(tapply(evolHeight[,i],evolHeight$treat,
FUN=mean,na.rm=TRUE),
tapply(evolHeight[,i],evolHeight$treat,
FUN=sd,na.rm=TRUE)))
}
colnames(HeighTr)<-c("expmean","lowmean","expsd","lowsd")
HeighTr$year<-c(2009:2012,2014:2017)
plot(HeighTr$expmean~HeighTr$year,ylim=c(0,70),type="b",las=1,
xaxt="n",yaxt="n",bty="n",col=colovec[1],
ylab="Seedling height (cm)",xlab="Year",
font.lab=2,cex.lab=1.5,lwd=2,pch=22,bg="white")
plotCI(x=HeighTr$year,y=HeighTr$expmean,
ui=HeighTr$expmean,
li=HeighTr$expmean-HeighTr$expsd,
pch=NA,lwd=1.5,add=TRUE)
plotCI(x=HeighTr$year,y=HeighTr$lowmean,
ui=HeighTr$lowmean+HeighTr$lowsd,
li=HeighTr$lowmean,
pch=NA,lwd=1.5,add=TRUE)
points(HeighTr$expmean~HeighTr$year,type="b",
col=colovec[1],lwd=2.5,pch=22,bg="white",cex=1.5)
points(HeighTr$lowmean~HeighTr$year,type="b",lty=2,
col=colovec[2],lwd=2.5,pch=19,cex=1.5)
axis(1,lwd=2,cex.axis=1,at=c(2009:2017),
lab=colnames(survEv),las=1,font=2)
axis(2,lwd=2,las=1,font=2)
box(lwd=2)
legend(2009.5,10,legend=c("Natural exposure","Protected exposure"),
col=colovec,lty=c(1,2),pch=c(22,19),pt.bg="white",
bty="n",cex=1.1,title.cex=1.5,y.intersp=1.8,x.intersp=0.5,lwd=2)
#export to .pdf 6 x 6 inches
##############################################################################/
#Figure 2: combining the 3 plot of phenotypic traits evolution####
##############################################################################/
pdf(file="output/Figure_2_phenevol.pdf",width=18,height=6)
op<-par(mfrow=c(1,3),mar=c(4.1,5.1,2.1,1.1))
#Figure A
matplot(t(survEv),type="b",ylim=c(0,100),las=1,
col=colovec[as.numeric(survEv.treat)],lwd=2,
lty=as.numeric(survEv.treat),bg="white",
pch=c(22,19,22,22,22,19,19,22,22),
xaxt="n",yaxt="n",bty="n",
ylab="Percentage of survival",xlab="Year",
font.lab=2,cex.lab=2,cex=1.8)
axis(1,lwd=2,cex.axis=1.5,at=c(1:dim(survEv)[2]),
lab=colnames(survEv),las=1,font=2)
axis(2,lwd=2,las=1,font=2,cex.axis=1.5)
box(lwd=2)
legend(1.5,30,legend=c("Natural exposure","Protected exposure"),
col=colovec,lty=c(1,2),pch=c(22,19),pt.bg="white",
bty="n",cex=2,y.intersp=1.3,x.intersp=0.8,lwd=2,seg.len=2)
mtext(text="A",side=3,cex=2,at=0.1,font=2,las=0,adj=1,line=-0.1)
#Figure B
graf<-barplot(temp1$mean,density=c(-1,20),angle=c(0,60),border=NA,
col=colovec,ylim=c(-1,105),ylab="Percentage of infection",
xlab="Year",cex.axis=1,cex.lab=2,las=1,yaxt="n",bty="n",
space=c(0,0.25,rep(c(1,0.25),times=8)),font.lab=2)
axis(1,at=graf[seq(1,17,2)]+0.625,labels=rownames(infectM),
lwd=2,font=2,cex.axis=1.5)
axis(2,at=seq(0,100,20),labels=seq(0,100,20),lwd=2,las=1,
font=2,cex.axis=1.5)
box(bty="o",lwd=2)
#adding standard deviation
temp2<-pivot_longer(infectM,cols=3:4,names_to="treat",values_to="sd")
plotCI(x=graf,y=temp1$mean,
ui=temp1$mean+temp2$sd,
li=temp1$mean,
pch=NA,lwd=1.5,add=TRUE)
#for cosmetic reason, we superimpose again the barplot
par(lwd=2)
barplot(temp1$mean,density=c(-1,20),angle=c(0,60),border=colovec,
col=colovec,ylim=c(-1,105),ylab="Percentage of infection",
cex.axis=1,cex.lab=1.5,las=1,yaxt="n",bty="n",
space=c(0,0.25,rep(c(1,0.25),times=8)),font.lab=2,add=TRUE)
legend(0,98,legend=c("Natural exposure","Protected exposure"),
fill=colovec,density=c(-1,20),angle=c(0,60),bty="n",border=colovec,
cex=2,y.intersp=1.3,x.intersp=0.8)
par(lwd=1)
mtext(text="B",side=3,cex=2,at=-3,font=2,las=0,adj=1,line=-0.1)
#Figure C
plot(HeighTr$expmean~HeighTr$year,ylim=c(0,70),type="b",las=1,
xaxt="n",yaxt="n",bty="n",col=colovec[1],
ylab="Seedling height (cm)",xlab="Year",
font.lab=2,cex.lab=2,lwd=2,pch=22,bg="white")
plotCI(x=HeighTr$year,y=HeighTr$expmean,
ui=HeighTr$expmean,
li=HeighTr$expmean-HeighTr$expsd,
pch=NA,lwd=1.5,add=TRUE)
plotCI(x=HeighTr$year,y=HeighTr$lowmean,
ui=HeighTr$lowmean+HeighTr$lowsd,
li=HeighTr$lowmean,
pch=NA,lwd=1.5,add=TRUE)
points(HeighTr$expmean~HeighTr$year,type="b",
col=colovec[1],lwd=2.5,pch=22,bg="white",cex=2)
points(HeighTr$lowmean~HeighTr$year,type="b",lty=2,
col=colovec[2],lwd=2.5,pch=19,cex=2)
axis(1,lwd=2,cex.axis=1.5,at=c(2009:2017),
lab=colnames(survEv),las=1,font=2)
axis(2,lwd=2,las=1,font=2,cex.axis=1.5)
box(lwd=2)
legend(2009.5,11,legend=c("Natural exposure","Protected exposure"),
col=colovec,lty=c(1,2),pch=c(22,19),pt.bg="white",
bty="n",cex=2,y.intersp=1.3,x.intersp=0.8,lwd=2,seg.len=2)
mtext(text="C",side=3,cex=2,at=2008.1,font=2,las=0,adj=1,line=-0.1)
par(op)
#export to .pdf 6 x 18 landscape
dev.off()
##############################################################################/
#Figure 6: distribution of height at the end of the experiment####
##############################################################################/
distriHeight<-dispo[dispo$family_simp!="CC" & dispo$family_simp!="hd" &
!is.na(dispo$an_mort) & dispo$an_mort!="g" &
dispo$family_simp!="26",
c("Sample_ID","bloc","PU","treat","family_simp","H09v",
"H10v","H11v","H12v","H14v","H15v","H16v","H17v")]
distriHeight$family_simp<-drop.levels(distriHeight$family_simp)
levels(distriHeight$family_simp)[1:2]<-c("01","09")
#spliting the data set by exposure
disHeigNat<-distriHeight[distriHeight$treat=="exp",]
disHeigPro<-distriHeight[distriHeight$treat=="low",]
#defining a color vector
colovec<-c(brewer.pal(12,"Paired")[1:2],brewer.pal(12,"Paired")[3:4],
brewer.pal(11,"RdYlGn")[1])
pdf(file="output/Figure_6_compHeight.pdf",width=14,height=7)
op<-par(mfrow=c(1,2),mar=c(4,4,3,0.1))
boxplot(disHeigNat$H17v~disHeigNat$family_simp,col=colovec[4],boxwex=0.6,
las=1,main="Natural exposure",xlab="Families",ylab="Height (cm)",
ylim=c(0,165),cex.main=2)
points(tapply(disHeigNat$H17v,disHeigNat$family_simp,
FUN=mean,na.rm=TRUE),
pch=18,cex=2,col=colovec[3])
abline(h=mean(disHeigNat$H17v,na.rm=TRUE),col=colovec[5],lwd=3,lty=2)
boxplot(disHeigPro$H17v~disHeigPro$family_simp,col=colovec[2],boxwex=0.6,
las=1,main="Protected exposure",xlab="Families",ylab="",
ylim=c(0,165),cex.main=2)
points(tapply(disHeigPro$H17v,disHeigPro$family_simp,
FUN=mean,na.rm=TRUE),
pch=18,cex=2,col=colovec[1])
abline(h=mean(disHeigPro$H17v,na.rm=TRUE),col=colovec[5],lwd=3,lty=2)
par(op)
dev.off()
#export to .pdf 14 x 7 inches
##############################################################################/
#END
##############################################################################/