adespatial (version 0.3-8)

plot.TBI: Plots of the outputs of a temporal beta diversity analysis

Description

B-C plots are an important step in temporal beta diversity analysis. This function draws B-C plots from the output of function TBI. Different graphic options are available.

Usage

# S3 method for TBI
plot(x, type = "BC", s.names = NULL, pch.loss = 21,
  pch.gain = 22, cex.names = 1, col.rim = "black",
  col.bg = "gold1", cex.symb = 3, diam = TRUE, main = "B-C plot",
  cex.main = 1, cex.lab = 1, xlim = NULL, ylim = NULL,
  silent = TRUE, ...)

Arguments

x

Output of a temporal beta diversity analysis with function TBI. The matrix BCD.mat will be extracted from that object. This matrix contains the B/den statistics in column 1 and the C/den statistics in column 2, where "den" is the denominator used in the TBI analysis.

type

Specify which outputs are plotted. At this time, only BC plots are implemented

s.names

a vector of names: Site names will be printed on the BC plot. Examples: s.names=1:25; s.names=paste("Site",1:25,sep="."); s.names=rownames(res1$BCD.mat). Else, s.names=NULL (default): no site names will be printed.

pch.loss

Symbol used for sites where losses > gains. Default: pch=21, circles. Symbols 21 to 25 have a black rim and can be filled with different colours (argument col.bg); see documentation of funciton points. Symbols 0 to 20 only have a rim.

pch.gain

Symbol used for sites where losses >= gains. Default: pch=21, squares.

cex.names

Multiplier for the font size of the site names.

col.rim

Colour of symbol rims in the plot. The following colours have been used in BC plots: "gold","grey70","cadetblue2","red","orange3","coral2","grey100","green".

col.bg

Colour filling symbols 21 to 25 in the plot.

cex.symb

Multiplier for size of the symbols representing the TBI values of the sites in the plot. With cex.symb=NULL, symbols have small and uniform sizes.

diam

If TRUE, symbol diameter represents the TBI value. If FALSE, symbol surface area represents the TBI value.

main

Main title above the plot. Change the title and adapt it to your study.

cex.main

Multiplier for the font size of the main title.

cex.lab

Multiplier for the font size of the labels.

xlim

The x limits of the plot, e.g. c(0,1).

ylim

The y limits of the plot, e.g. c(0,1).

silent

If FALSE print intercept of red line with ordinate.

Other arguments to be passed to the function

Value

A graph in the R graphic window, with the same scale along the 2 axes (asp=1).

Details

B-C plots are an informative output of temporal beta diversity analysis. The species losses (B statistics) form the abscissa and the gains (C statistics) are on the ordinate of the plot. The objective is to illustrate whether the temporal changes at the various sites are dominated by gains or by losses. Distinctive symbols are used for the sites dominated by gains (default: squares) and by losses (default: circles). The symbols are drawn to sizes representing the values of the D = (B+C) statistics.

References

Legendre, P. 2019. A temporal beta-diversity index to identify sites that have changed in exceptional ways in space-time surveys. Ecology and Evolution (in press).

van den Brink, P. J. & C. J. F. ter Braak. 1999. Principal response curves: analysis of time-dependent multivariate responses of biological community to stress. Environmental Toxicology and Chemistry 18: 138-148.

See Also

TBI

Examples

Run this code
# NOT RUN {
if(require("vegan", quietly = TRUE)) {

## Example 1 -

## Invertebrate communities subjected to insecticide treatment.

## As an example in their paper on Principal Response Curves (PRC method), van den 
## Brink & ter Braak (1999) used observations on the abundances of 178 invertebrate 
## species (macroinvertebrates and zooplankton) subjected to treatments in 12 mesocosms 
## by the insecticide chlorpyrifos. The mesocosms were sampled at 11 occasions. The 
## data, available in the {vegan} package, are log-transformed species abundances, 
## ytranformed = loge(10*y+1).

## The data of survey #4 will be compared to those of survey #11 in this example. 
## Survey #4 was carried out one week after the insecticide treatment, whereas the  
## fauna of the mesocosms was considered by the authors to have fully recovered from  
## the insecticide treatment at survey #11.

data(pyrifos)

## The mesocosms had originally been attributed at random to the treatments. However, 
## to facilitate presentation of the results, they will be listed here in order of 
## increased insecticide doses: {0, 0, 0, 0, 0.1, 0.1, 0.9, 0.9, 6, 6, 44, 44} 
## micro g/L.

## Select the 12 data rows of surveys 4 and 11 from the data file and reorder them

ord4 <- c(38,39,41,47,37,44,40,46,43,48,42,45)
ord11 <- c(122,123,125,131,121,128,124,130,127,132,126,129)

## Run the TBI function

res1 <- TBI(pyrifos[ord4,], pyrifos[ord11,], method = "%diff", nperm = 0, test.t.perm = FALSE)

res1$BCD.mat

## Draw BC plots

par(mfrow=c(1,2))

s.names <- paste("Surv",1:12,sep=".")

## In the 1st plot, the symbols have diameters proportional to the site TBI statistics 

plot(res1, s.names=s.names, col.bg="red", pch.loss=21, pch.gain=22, 
main="B-C plot, Pyrifos, surveys 4 & 11")

## In the 2nd plot, control the axes limit values by specifying xlim and ylim

plot(res1, s.names=1:12, col.bg="green", pch.loss=23, pch.gain=24, 
main="B-C plot, Pyrifos, surveys 4 & 11", xlim=c(0,0.5), ylim=c(0.1,0.6))

## In the 3rd plot, draw all symbols small and of the same size, using cex.symb=NULL

dev.off()

plot(res1, s.names=1:12, col.bg="gold", pch.loss=23, pch.gain=24, 
main="B-C plot, Pyrifos, surveys 4 & 11", cex.symb=NULL)

## Example 2 -

## This example uses the mite data available in vegan. Let us pretend that sites 1-20 
## represent a survey at time 1 (T1) and sites 21-40 a survey at time 2 (T2).

data(mite)

## Run the TBI function

res2 <- TBI(mite[1:20,],mite[21:40,],method="%diff",nperm=0,test.t.perm=FALSE)

res2$BCD.mat

## Draw BC plots

par(mfrow=c(1,2))

s.names=rownames(res2$BCD.mat)

## In the 1st plot, the symbols have diameters proportional to the site TBI statistics

plot(res2, s.names=s.names, col.bg="cadetblue2", pch.loss=21, pch.gain=22, 
main="B-C plot, Mite data")

# In the 2nd plot, control the axes limit values by specifying xlim and ylim

plot(res2, s.names=1:20, col.rim="coral2", pch.loss=19, pch.gain=15, 
main="B-C plot, Mite data", xlim=c(0,0.6), ylim=c(0,0.6))

}

# }

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