Thanks to all,
I did eventually come up with a solution which involved sub-setting
the data first into categories, making an empty plot, and then
plotting rectangles. I really like the ggplot2 and I will use that
next time.
My ugly script is below
Thanks,
Daisy
plot(1, xlim=c(5,45),ylim=c(0,10),xlab="Year",ylab="+/- 1 \u03c3 Mean
Patch Size (ha)",axes=F,type="n")
title(main = list("Patch Size Agreement", cex=1.4))
axis(2)
box()
mtext(c(2010,2030,2050,2070),side=1,line = 1, at=c(10,20,30,40))
position<-seq(10, 40, length.out=4 )
xlef<-position-2.5
xrig <-position+2.5
for(i in 1:nrow(sub00)){
min_y<-sub00$minsd_ha[i]
max_y<-sub00$maxsd_ha[i]
xleft<-xlef[1]
xrigh<-xrig[1]
rect(xleft, min_y, xrigh, max_y,border = NA,col=rgb(0,
0, 0, alpha=0.03))
}
for(i in 1:nrow(sub01)){
min_y<-sub01$minsd_ha[i]
max_y<-sub01$maxsd_ha[i]
xleft<-xlef[2]
xrigh<-xrig[2]
rect(xleft, min_y, xrigh, max_y,border = NA,col=rgb(0,
0, 0, alpha=0.03))
}
for(i in 1:nrow(sub02)){
min_y<-sub02$minsd_ha[i]
max_y<-sub02$maxsd_ha[i]
xleft<-xlef[3]
xrigh<-xrig[3]
rect(xleft, min_y, xrigh, max_y,border = NA,col=rgb(0,
0, 0, alpha=0.03))
}
for(i in 1:nrow(sub03)){
min_y<-sub03$minsd_ha[i]
max_y<-sub03$maxsd_ha[i]
xleft<-xlef[4]
xrigh<-xrig[4]
rect(xleft, min_y, xrigh, max_y,border = NA,col=rgb(0,
1, 0, alpha=0.03))
}
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