Biplots of co-correspondence analysis models

Produces biplots of the response and predictor from the results of a co-correspondence analysis models.

# S3 method for symcoca
biplot(x,
    which = "y1",
    choices = 1:2,
    benzecri = TRUE,
    type = NULL,
    xlim = NULL,
    ylim = NULL,
    col.species = "red",
    col.sites = "black",
    pch.species = 3,
    pch.sites = 1,
    cex = 0.7,
    main = "",
    sub = "",
    ylab, xlab,
    ann = par("ann"),
    axes = TRUE,
    ...)

# S3 method for predcoca
biplot(x,
    which = "response",
    choices = 1:2,
    type = NULL,
    xlim = NULL,
    ylim = NULL,
    col.species = "red",
    col.sites = "black",
    pch.species = 3,
    pch.sites = 1,
    cex = 0.7,
    main = "",
    sub = "",
    ylab, xlab,
    ann = par("ann"),
    axes = TRUE,
    ...)

Arguments

x	an object of class "symcoca", the result of a call to symcoca.
which	character; should the response or predictor scores be plotted. Can be specified in several ways: response choices are one from c("y", "Y", "y1", "response"); predictor choices are one from c("x", "X", "y2", "predictor").
choices	a vector of length 2 indicating which predictive CoCA axes to plot.
benzecri	logical, should a Benzecri plot be drawn? Such plots draw species scores, scaled by the quarter root of the respective eigenvalues, with unscaled site scores. A Benzecri plot is the recommended biplot for symmetric CoCA. See scores.symcoca.
type	one of "points", or "text". Determines how the site and species scores are displayed. If type = "points", scores are plotted as points. If type = "text", then the row names of the scores matrices are plotted.
xlim, ylim	limits for the x and y axes. If non supplied, suitable limits will be determined from the data.
col.species, col.sites, pch.species, pch.sites	colours and plotting characters used when plotting the species and sites scores.
cex	numeric; scaling factor when drawing points or text labels.
xlab, ylab	labels for the x and y axes. If non supplied suitable labels are formed from the result object.
main, sub	the main and sub titles for the plot.
ann	logical, if TRUE plots are annotated and not if FALSE, currently ignored.
axes	a logical value indicating whether axes and plot border should be drawn on the plot.
...	other graphical parameters as in 'par' may also be passed as arguments.

References

Ter Braak, C.J.F and Schaffers, A.P. (2004) Co-Correspondence Analysis: a new ordination method to relate two community compositions. Ecology 85(3), 834--846

Author

Gavin L. Simpson.

See also

coca, plot.default

Examples

## symmetric CoCA
data(beetles)
data(plants)

## log transform the beetle data
beetles <- log(beetles + 1)

## fit the model
bp.sym <- coca(beetles ~ ., data = plants, method = "symmetric")
#> 
#> Removed some species that contained no data in: beetles, plants 

## draw a biplot of the beetle results
biplot(bp.sym)


## biplot of both - Fig 1 in ter Braak & Schaffers (2004)
layout(matrix(1:2, ncol = 2))
biplot(bp.sym, which = "y1", main = "Beetles")
biplot(bp.sym, which = "y2", main = "Plants")

layout(1)

## predictive CoCA
bp.pred <- coca(beetles ~ ., data = plants)
#> 
#> Removed some species that contained no data in: beetles, plants 

## draw a biplot of the response
biplot(bp.pred)


## recreate Fig 3 in ter Braak & Schaffers (2004)
layout(matrix(1:2, ncol = 2))
biplot(bp.pred, which = "response", main = "Beetles")
biplot(bp.pred, which = "predictor", main = "Plants")

layout(1)