cati (version 0.99.3)

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 listofindex
plot(x, type = "normal", 
	col.index = c("red", "purple", "olivedrab3"), 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, alpha = 0.4, ...)

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.

alpha

Degree of transparency for null models aera.

…

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.

Details

S3 method plot for class listofindex: -Normal type plot means, standard deviations, ranges and confidence intervals of T-statistics. -Simple_range type plot means, standard deviations and range of T-statistics -Simple type plot T-statistics for each site and traits and the mean confidence intervals by traits -Barplot type plot means, standard deviations and confidence intervals of T-statistics in a barplot fashion -Bysites type plot each metrics for each sites -Bytraits type plot each metrics for each traits

See Also

as.listofindex; plot.Tstats; ses.listofindex

Examples

# NOT RUN {
	data(finch.ind)

	res.finch <- Tstats(traits.finch, ind.plot = ind.plot.finch, 
	sp = sp.finch, nperm = 9, print = FALSE)

	
# }
# NOT RUN {
		#### Use a different regional pool than the binding of studied communities
		#create a random regional pool for the example
	
		reg.p <- rbind(traits.finch, traits.finch[sample(1:2000,300), ])
	
		res.finch2 <- Tstats(traits.finch, ind.plot = ind.plot.finch, 
	    sp = sp.finch, reg.pool=reg.p, nperm = 9, print = FALSE)	
	    
	    plot(as.listofindex(list(res.finch,res.finch2)))
    
    
	    #### Use a different regional pool for each communities
		#create a random regional pool for each communities for the example
		list.reg.p <- list(
		traits.finch[sample(1:290,200), ], traits.finch[sample(100:1200,300), ], 
		traits.finch[sample(100:1500, 1000), ], traits.finch[sample(300:800,300), ],
		traits.finch[sample(1000:2000, 500), ], traits.finch[sample(100:900, 700), ] )

		# Warning: the regional pool need to be larger than the observed communities
		table(ind.plot.finch)
		# For exemple, the third community need a regional pool of more than 981 individuals
		
		res.finch3 <- Tstats(traits.finch, ind.plot = ind.plot.finch, 
	    sp = sp.finch, reg.pool=list.reg.p, nperm = 9, print = FALSE)	
	    
	    plot(as.listofindex(list(res.finch, res.finch2, res.finch3)))	
	
# }