[R-sig-eco] horizontal lines in stacked bargraph ggplot
Mitchell, Kendra
kendrami at mail.ubc.ca
Wed Aug 20 21:03:19 CEST 2014
OF course, aggregate first. that worked, thanks!
FIY-ggsave doesn't preserve text as text, it converts text to vectors (and has the same horizontal lines issue). color=NULL didn't seem to do anything
--
Kendra Maas, Ph.D.
Post Doctoral Research Fellow
University of British Columbia
________________________________
From: Philippi, Tom [tom_philippi at nps.gov]
Sent: Wednesday, August 20, 2014 11:42 AM
To: Mitchell, Kendra
Subject: Re: [R-sig-eco] horizontal lines in stacked bargraph ggplot
Not a definitive answer, but 3 suggestions.
1) try ggsave() for your .svg
2) try color=NULL in your aes to get rid of the line around each bar segment
aes( y=value, x=factor(hor.om<http://hor.om/>), color=NULL, fill=factor(variable), order=-as.numeric(variable)))
3) aggregate your data so you have 1 block per hor.om<http://hor.om> x variable combination:
b.p2 <- aggregate(value ~ variable + hor.om<http://hor.om>, data=b.p, FUN=sum)
On Wed, Aug 20, 2014 at 11:02 AM, Mitchell, Kendra <kendrami at mail.ubc.ca<mailto:kendrami at mail.ubc.ca>> wrote:
Hi All
I posted this question in the ggplot user group but realized that it's not super active and I'm on a deadline for presenting this graph, so sorry about the cross-posting.
I'm making stacked bargraphs to show distribution of major taxonomic groups across a treatment regime (using ggplot 0.9.3.1 and R 3.0.2 in RStudio, running in Ubuntu). within RStudio the plots look beautiful, however when I export an SVG (or PNG) the bars are filled with horizontal lines rather than solid colors. If I export the figure as a PDF, it appears lined in Ubuntu but solid in Windows so there is clearly some OS graphics issues going on too. Plus PDFs look horrible in powerpoint which I need to use, I really want to make this a pretty SVG.
I think the issue is that instead of there being one object for each phyla for each bar, there are actually hundreds of small rectangles being exported for each color. It seems that the value for every sample is being preserved in the SVG? Other than going into Inkscape and selecting thousands of little boxes and merging them, how can I fix this so the svg looks like the output in RStudio?
Here's my code and the link to the screen shots of the pretty figure in RStudio,the lined svg, and a close up of the svg (https://plus.google.com/u/0/109376008011832363348/posts/bG5R3CrAhK5?pid=6049706007202609858&oid=109376008011832363348).
> b.phy <- read.table(file="../bac.phyla.
env", header=T, row.names=1) #
> str(b.phy)
'data.frame': 719 obs. of 23 variables:
$ zone : Factor w/ 6 levels "bIDF","bSBS",..: 4 4 4 4 4 4 4 4 4 4 ...
$ om : int 2 2 3 3 1 2 2 3 3 1 ...
$ horizon : int 1 2 1 2 2 1 2 1 2 1 ...
$ site : Factor w/ 18 levels "A7","A8","A9",..: 1 1 1 1 1 1 1 1 1 1 ...
$ erick : int 0 0 0 0 0 0 0 0 0 0 ...
$ Alphaproteobacteria: num 0.31 0.19 0.29 0.21 0.22 0.33 0.26 0.29 0.3 0.27 ...
$ Betaproteobacteria : num 0.06 0.14 0.07 0.1 0.08 0.02 0.09 0.02 0.08 0.03 ...
$ Deltaproteobacteria: num 0.02 0.04 0.04 0.04 0.04 0.02 0.03 0.02 0.03 0.02 ...
$ Gammaproteobacteria: num 0.07 0.02 0.06 0.02 0.04 0.05 0.05 0.05 0.04 0.05 ...
$ Proteobacteria : num 0 0.01 0.01 0.01 0.01 0 0 0 0 0 ...
$ Actinobacteria : num 0.16 0.07 0.14 0.12 0.08 0.23 0.09 0.22 0.07 0.27 ...
$ Acidobacteria : num 0.21 0.2 0.19 0.15 0.16 0.17 0.14 0.22 0.15 0.19 ...
$ Bacteroidetes : num 0.03 0.02 0.03 0.01 0.01 0.03 0.01 0.02 0.02 0.03 ...
$ Firmicutes : num 0 0.01 0 0.04 0.02 0 0.02 0 0.03 0 ...
$ Chloroflexi : num 0 0.05 0.01 0.04 0.03 0 0.01 0 0.01 0 ...
$ Cyanobacteria : num 0.01 0 0 0 0.01 0.03 0.02 0.04 0.01 0.03 ...
$ Gemmatimonadetes : num 0 0.03 0 0.03 0.02 0 0.02 0 0.02 0 ...
$ Planctomycetes : num 0.03 0.02 0.02 0.02 0.03 0.02 0.03 0.04 0.02 0.03 ...
$ Verrucomicrobia : num 0 0 0.01 0 0.01 0 0 0.01 0.01 0.01 ...
$ Nitrospirae : num 0 0 0 0 0 0 0 0 0 0 ...
$ unclassified : num 0.08 0.2 0.1 0.2 0.25 0.07 0.23 0.06 0.2 0.06 ...
$ other : num 0.009 0.013 0.011 0.011 0.011 0.015 0.006 0.017 0.007 0.012 ...
$ hor.om<http://hor.om><http://hor.om> : chr "1.2" "2.2" "1.3" "2.3" ...
>
> b.p<- melt(b.phy, id.vars=c("zone", "om", "horizon", "site", "erick", "hor.om<http://hor.om><http://hor.om>"))
> str(b.p)
'data.frame': 12223 obs. of 8 variables:
$ zone : Factor w/ 6 levels "bIDF","bSBS",..: 4 4 4 4 4 4 4 4 4 4 ...
$ om : int 2 2 3 3 1 2 2 3 3 1 ...
$ horizon : int 1 2 1 2 2 1 2 1 2 1 ...
$ site : Factor w/ 18 levels "A7","A8","A9",..: 1 1 1 1 1 1 1 1 1 1 ...
$ erick : int 0 0 0 0 0 0 0 0 0 0 ...
$ hor.om<http://hor.om><http://hor.om> : chr "1.2" "2.2" "1.3" "2.3" ...
$ variable: Factor w/ 17 levels "Alphaproteobacteria",..: 1 1 1 1 1 1 1 1 1 1 ...
$ value : num 0.31 0.19 0.29 0.21 0.22 0.33 0.26 0.29 0.3 0.27 ...
>
> bac.phyla.color<-c("#A6CEE3","#7DB4D5", "#5C9FC9","#3A89BD", "#1F78B4", "#B2DF8A","#79C360", "#33A02C", "#FB9A99", "#E31A1C", "#FDBF6F", "#FF7F00", "#CAB2D6", "#6A3D9A", "#FFFF99","#ededed", "#000000")
>
> devSVG(file="b.phyla.svg", width=8, height=10)
>
> b.plot <- ggplot(b.p, aes( y=value, x=factor(hor.om<http://hor.om><http://hor.om>), fill=factor(variable), order=-as.numeric(variable)))+ #order=- makes the stack the same order as the legend
+ geom_bar(position="fill", stat="identity")+
+ scale_fill_manual(values=bac.phyla.color)
> b.plot
> dev.off()
null device
1
>
> ggsave(file="b.phyla.pdf", plot=b.plot, width=8, height=10)
Here's a sample of the data.
dput(b.p[b.p$zone=="bIDF" & b.p$hor.om<http://hor.om><http://hor.om>=="1.2",])
structure(list(zone = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("bIDF", "bSBS", "MD",
"oBS", "oJP", "TX"), class = "factor"), om = c(2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), horizon = c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), site = structure(c(5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L), .Label = c("A7", "A8",
"A9", "BL", "BP", "BR", "DC", "JE", "JS", "JW", "LH", "LL", "OL",
"SL", "TA", "TB", "TC", "TO"), class = "factor"), erick = c(0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), hor.om<http://hor.om><http://hor.om> = c("1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2", "1.2",
"1.2", "1.2", "1.2", "1.2", "1.2"), variable = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L,
17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L,
17L, 17L, 17L, 17L), .Label = c("Alphaproteobacteria", "Betaproteobacteria",
"Deltaproteobacteria", "Gammaproteobacteria", "Proteobacteria",
"Actinobacteria", "Acidobacteria", "Bacteroidetes", "Firmicutes",
"Chloroflexi", "Cyanobacteria", "Gemmatimonadetes", "Planctomycetes",
"Verrucomicrobia", "Nitrospirae", "unclassified", "other"), class = "factor"),
value = c(0.48, 0.54, 0.45, 0.48, 0.57, 0.52, 0.54, 0.58,
0.5, 0.43, 0.5, 0.41, 0.5, 0.56, 0.5, 0.47, 0.55, 0.56, 0.43,
0.43, 0.39, 0.44, 0.52, 0.44, 0.52, 0.4, 0.44, 0.37, 0.3,
0.32, 0.03, 0.03, 0.04, 0.04, 0.03, 0.03, 0.03, 0.03, 0.01,
0.03, 0.03, 0.03, 0.02, 0.02, 0.02, 0.03, 0.04, 0.03, 0.04,
0.03, 0.03, 0.03, 0.02, 0.03, 0.02, 0.03, 0.02, 0.07, 0.03,
0.06, 0.01, 0.01, 0.02, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01,
0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01,
0.01, 0.02, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.02,
0.01, 0.02, 0.02, 0.02, 0.02, 0.01, 0.01, 0.02, 0.01, 0.02,
0.01, 0.02, 0.01, 0.01, 0.02, 0.01, 0.01, 0.01, 0.02, 0.01,
0.01, 0.01, 0.01, 0.02, 0.01, 0.02, 0.03, 0.01, 0.03, 0.03,
0.03, 0.01, 0, 0.01, 0, 0, 0, 0, 0, 0, 0, 0, 0.01, 0, 0,
0, 0, 0, 0, 0, 0, 0.01, 0, 0.01, 0, 0, 0, 0, 0, 0.01, 0,
0.28, 0.27, 0.26, 0.31, 0.24, 0.27, 0.23, 0.22, 0.2, 0.37,
0.26, 0.39, 0.33, 0.24, 0.3, 0.34, 0.23, 0.22, 0.32, 0.34,
0.36, 0.35, 0.23, 0.33, 0.24, 0.37, 0.33, 0.33, 0.42, 0.39,
0.05, 0.05, 0.07, 0.04, 0.06, 0.06, 0.09, 0.07, 0.16, 0.06,
0.07, 0.05, 0.04, 0.05, 0.07, 0.06, 0.06, 0.06, 0.05, 0.05,
0.06, 0.06, 0.1, 0.06, 0.07, 0.04, 0.06, 0.05, 0.04, 0.05,
0.02, 0.02, 0.02, 0.02, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01,
0.02, 0.02, 0.01, 0.01, 0.01, 0.02, 0.02, 0.02, 0.02, 0.02,
0.02, 0.01, 0.02, 0.01, 0.01, 0.01, 0.01, 0.03, 0.04, 0.04,
0, 0, 0, 0.01, 0, 0, 0, 0.01, 0, 0, 0, 0.01, 0, 0, 0, 0,
0.01, 0, 0.01, 0, 0, 0, 0, 0, 0, 0, 0.02, 0, 0, 0, 0.03,
0.02, 0.05, 0.02, 0.01, 0.02, 0.01, 0.01, 0.01, 0.02, 0.02,
0.02, 0.02, 0.03, 0.01, 0.01, 0.01, 0.02, 0.03, 0.03, 0.03,
0.03, 0.01, 0.02, 0.03, 0.03, 0.02, 0.02, 0.02, 0.03, 0.01,
0, 0.01, 0.01, 0, 0, 0.01, 0, 0.01, 0, 0, 0, 0, 0, 0, 0.01,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.01, 0, 0.01, 0.01,
0.01, 0.01, 0.01, 0.01, 0, 0.01, 0.01, 0.01, 0.01, 0.01,
0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01,
0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0, 0.01, 0, 0.01,
0, 0, 0.01, 0.01, 0, 0.01, 0, 0.01, 0.01, 0, 0, 0, 0.01,
0.01, 0.01, 0.01, 0, 0, 0.01, 0, 0.01, 0.01, 0, 0.01, 0.01,
0.01, 0.01, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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--
Kendra Maas, Ph.D.
Post Doctoral Research Fellow
University of British Columbia
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-------------------------------------------
Tom Philippi
Quantitative Ecologist & Data Therapist
Inventory and Monitoring Program
National Park Service
Tom_Philippi at nps.gov<mailto:Tom_Philippi at nps.gov>
http://science.nature.nps.gov/im/monitor
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