cati (version 0.8)

plot.listofindex: Plot community assembly index

Description

Plot community assembly index and confidence intervals using a list of index. S3 method for class listofindex.

Usage

## S3 method for class 'listofindex':
plot(x, type = "normal", 
	col.index = c("red", "purple", "green"), add.conf = TRUE, 
	color.cond = TRUE, val.quant = c(0.025, 0.975), 
	grid.v = TRUE, grid.h = TRUE, xlim = NULL, ylim = NULL, 
	cex.text = 0.8, plot.ask = FALSE, srt.text = 90, 
	bysite = FALSE, ...)

Arguments

x

A list of index and related null models obtained from to the as.listofindex function.

type

Type of plot. Possible type = "simple", "simple_range", "normal", "barplot" and "bytraits".

col.index

Vector of colors for index.

add.conf

Logical value; Add confidence intervals or not.

color.cond

Logical value; If color.cond=TRUE, color points indicate T-statistics values significatively different from the null model and grey points are not different from null model.

val.quant

Numeric vectors of length 2, giving the quantile to calculate confidence interval. By default val.quant=c(0.025,0.975) for a bilateral test with alpha = 5%.

grid.v

Logical value; print vertical grid or not

grid.h

Logical value; print horizontal grid or not

xlim

Numeric vectors of length 2, giving the x coordinates range

ylim

Numeric vectors of length 2, giving the y coordinates range

cex.text

Numeric value; the magnification to be used for text relative to the current setting of cex

plot.ask

Logical value; ask for plotting the next plot or not.

srt.text

Degree of rotation for text.

bysite

Logical value; plot per site or by traits.

...

Any additional arguments are passed to the plot function creating the core of the plot and can be used to adjust the look of resulting graph.

Value

• None; used for the side-effect of producing a plot.

See Also

as.listofindex; plot.Tstats; ses.listofindex

Examples

data(finch.ind)
	oldpar<-par()
	
	####
	#The function com.index allow to choose your own function 
	#(like mean, range, variance...) to calculate customize index.
	
	require(e1071)
	
	funct<-c("mean(x, na.rm=TRUE)", "kurtosis(x, na.rm=TRUE)", 
	"max(x, na.rm=TRUE) - min(x, na.rm=TRUE)", "CVNND(x)"  )
	
	res.finch.sp_mn2<-com.index(traits=traits.finch, index=funct, 
		sp=sp.finch, nullmodels=c(2,2,2,2), ind.plot=ind.plot.finch, 
		nperm=9, print=FALSE)
		
		res.finch.sp_mn3<-com.index(traits=traits.finch, index=funct, 
		sp=sp.finch, nullmodels=c(3,3,3,3), ind.plot=ind.plot.finch, 
		nperm=9, print=FALSE)

		####
		#We can represent Standardized Effect Size (ses)
		#using the function plot(as.listofindex(list1, list2, list3))
		
		list.ind2<-list(res.finch.sp_mn2, res.finch.sp_mn3)
		index.list2<-as.listofindex(list.ind2)
		
		plot(index.list2, type="bytraits")
		
		plot(index.list2)
	
	####
	#This allows to calcul index per site 
	#for example using "tapply(x, sites, mean)".
	
	funct<-c("tapply(x, ind.plot.finch, function(x) mean(x, na.rm=TRUE))", 
	"tapply(x, ind.plot.finch, function(x) kurtosis(x, na.rm=TRUE))", 
	"tapply(x, ind.plot.finch, function(x) max(x, na.rm=TRUE) - 
	min(x, na.rm=TRUE) )", "tapply(x, ind.plot.finch, function(x) CVNND(x))")
	
	
	##Null model 1 is trivial for this function 
	#because randomisation is within community only
	
	res.finch.ind_mn1<-com.index(traits=traits.finch, index=funct, 
		sp=sp.finch, nullmodels=c(1,1,1,1), ind.plot=ind.plot.finch, 
		nperm=9, print=FALSE)
		
		res.finch.ind_mn2<-com.index(traits=traits.finch, index=funct, 
		sp=sp.finch, nullmodels=c(2,2,2,2), ind.plot=ind.plot.finch, 
		nperm=9, print=FALSE)
		
		####
		#We can calcul metrics with or without intraspecific variance.
		#Calculation of trait averages per population 
		#(name_sp_site is a name of a population) 
		#like in the function com.index
		#and determine the site for each population (sites_bypop)
		
		name_sp_sites=paste(sp.finch, ind.plot.finch, sep="_")
		
		traits.by.pop<-apply(traits.finch, 2 , function (x) 
		tapply(x, name_sp_sites, mean , na.rm=TRUE))
		
		sites_bypop<-lapply(strsplit(paste(rownames(traits.by.pop), sep="_"), 
		split="_"), function(x) x[3])
		
		sites_bypop<-lapply(strsplit(paste(rownames(traits.by.pop), sep="_"), 
		split="_"), function(x) x[3])
		
		funct.withoutIV<-c("tapply(x, unlist(sites_bypop), 
		function(x) mean(x, na.rm=TRUE))", "tapply(x, unlist(sites_bypop), 
		function(x) kurtosis(x, na.rm=TRUE))", "tapply(x, unlist(sites_bypop), 
		function(x) max(x, na.rm=TRUE) - min(x, na.rm=TRUE) )", 
		"tapply(x, unlist(sites_bypop), function(x) CVNND(x))"  )
		
		funct.withoutIV<-c("tapply(x, unlist(sites_bypop), 
		function(x) mean(x, na.rm=TRUE))", "tapply(x, unlist(sites_bypop), 
		function(x) kurtosis(x, na.rm=TRUE))", "tapply(x, unlist(sites_bypop), 
		function(x) max(x, na.rm=TRUE) - min(x, na.rm=TRUE) )", 
		"tapply(x, unlist(sites_bypop), function(x) CVNND(x))"  )
		
		funct.withIV<-c("tapply(x, ind.plot.finch, function(x) 
		mean(x, na.rm=TRUE))", "tapply(x, ind.plot.finch, function(x) 
		kurtosis(x, na.rm=TRUE))", "tapply(x, ind.plot.finch, function(x) 
		max(x, na.rm=TRUE) - min(x, na.rm=TRUE) )", 
		"tapply(x, ind.plot.finch, function(x) CVNND(x))"  )
		
		funct.withIV<-c("tapply(x, ind.plot.finch, function(x) 
		mean(x, na.rm=TRUE))", "tapply(x, ind.plot.finch, function(x) 
		kurtosis(x, na.rm=TRUE))", "tapply(x, ind.plot.finch, function(x) 
		max(x, na.rm=TRUE) - min(x, na.rm=TRUE) )", 
		"tapply(x, ind.plot.finch, function(x) CVNND(x))"  )
		
		res.finch.withIV<-com.index(traits=traits.finch, index=funct.withIV, 
		sp=sp.finch, nullmodels=c(2,2,2,2), ind.plot=ind.plot.finch, 
		nperm=9, print=FALSE)
		
		res.finch.withIV<-com.index(traits=traits.finch, index=funct.withIV, 
		sp=sp.finch, nullmodels=c(2,2,2,2), ind.plot=ind.plot.finch, 
		nperm=9, print=FALSE)
		
		res.finch.withoutIV<-com.index(traits=traits.finch, index=funct.withoutIV, 
		sp=sp.finch, nullmodels=c(3,3,3,3), ind.plot=ind.plot.finch, 
		nperm=9, print=FALSE)
	
	####
	#We can also represent T-statistics and custom index thanks to
	#the plot.listofindex function.
	
	res.finch<-Tstats(traits.finch, ind_plot=ind.plot.finch, sp=sp.finch, 
		nperm=9, print=FALSE)
		
		list.ind<-list(res.finch.withIV, res.finch.withoutIV ,res.finch)
		
		index.list1<-as.listofindex(list.ind, namesindex=c("mean", "kurtosis", 
		"range", "CVNND", "mean.pop", "kurtosis.pop", "range.pop", "CVNND.pop", 
		"T_IP.IC", "T_IC.IR", "T_PC.PR"))
		
		class(index.list1)
		
		par(mfrow=c(2,3))
		plot(index.list1,type="bytraits", bysite=TRUE)
		
		par(mfrow=c(2,2))
		plot(index.list1,type="bytraits")
		par(mfrow=c(1,1))
		
		plot(index.list1,type="simple")
		plot(index.list1,type="simple_range")
		plot(index.list1,type="normal")
		plot(index.list1,type="barplot")