cati (version 0.8)

plot_sp_var: Plot populations values against species values

Description

Plot populations values against species values. The objectif is to see the contribution of intra-specific vs inter-specific variation to trait gradient.

Usage

plot_sp_var(traits = NULL, ind.plot = NULL, sp = NULL, variable = NULL, 
	col.ind = rgb(0.5, 0.5, 0.5, 0.5), col.pop = NULL, col.sp = NULL, 
	col.site = NULL, resume= FALSE, p.val = 0.05, min.ind.signif = 10, 
	multipanel = TRUE, col.nonsignif.lm = rgb(0, 0, 0, 0.5), 
	col.signif.lm = rgb(1, 0.1, 0.1, 0.8), silent= FALSE)

Arguments

traits

Individual Matrix of traits with traits in columns.

ind.plot

Factor defining the name of the plot in which the individual is.

sp

Factor defining the species which the individual belong to.

variable

A matrix of variables corresponding to each site (in rows) and each trait (in columns). If you want to plot all traits against one variable, variable can be a vector of numerical values.

col.ind

Color for individual values.

col.pop

Color for populational mean values.

col.sp

Color for species mean values.

col.site

Color for sites mean values.

resume

Logical, if TRUE plot a simple form of the plot.

p.val

Choosen p.value to print significant linear relationship using linear model. Argument past to the lm funtion internally.

min.ind.signif

Minimum individual to print significant linear relationship.

multipanel

Logical value. If TRUE divides the device to shown several traits graphics in the same device.

col.nonsignif.lm

Color for non significant linear relationship.

col.signif.lm

Color for significant linear relationship.

silent

Logical value, if resume=FALSE do not print warnings argument.

Value

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

See Also

plot_dens

Examples

data(finch.ind)
	
	#Random variable for this example
	variable<-c(1,5,15,6,3,25)
	
	plot_sp_var(traits.finch, ind.plot.finch, sp.finch, variable, 
	silent=TRUE)

	#If we change the value of the threshold 
	#(alpha=10\% instead of 5\% 
	#and the minimum individual to represent significativity 
	#fixed to 3 instead of 10 by default) 
	#we can see some significant relationships.

	plot_sp_var(traits.finch, ind.plot.finch, sp.finch, variable, 
	p.val=0.1,  min.ind.signif=3, silent=TRUE)


	#For a more simple figure, add the option resume=TRUE. 
	#Again if we change the value of the threshold 
	#(alpha=10\% instead of 5\% 
	#and the minimum individual to represent significativity
	# fixed to 3 instead of 10 by default) 
	#we can see some significant relationships.

	plot_sp_var(traits.finch, ind.plot.finch, sp.finch, variable, 
	silent=TRUE, resume=TRUE, col.pop="grey")
	
	plot_sp_var(traits.finch, ind.plot.finch, sp.finch, variable, 
	silent=TRUE, resume=TRUE, col.pop="grey", col.sp="black")
	
	plot_sp_var(traits.finch, ind.plot.finch, sp.finch, variable, 
	silent=TRUE, resume=TRUE, col.pop="grey", col.sp="black", 
	p.val=0.1,  min.ind.signif=3)