Plot a single dc-CA axis with CWMs, SNCs, trait and environment scores.

plot.dcca plots the CWMs and SNCs of a dc-CA axis against this axis, with optional centroids and colors for groups of sites and/or species if available in the data.

Usage

# S3 method for class 'dcca'
plot(
  x,
  ...,
  axis = 1,
  gradient_description = "correlation",
  envfactor = NULL,
  traitfactor = NULL,
  nspecies = 20,
  species_groups = NULL,
  widths = c(5, 1, 1),
  newnames = NULL,
  facet = TRUE,
  remove_centroids = FALSE,
  with_lines = 2,
  flip_axis = FALSE,
  expand = 0.2,
  formula = y ~ x,
  verbose = TRUE
)

Arguments

x: results from dc_CA of class dcca.
...: unused.
axis: the axis number to get (default 1).
gradient_description: character or 2-character vector for the trait and environmental gradient, respectively specifying what to plot in the vertical line plots to describe the dc-CA axis (trait and environmental gradients). Default: correlation for intra-set correlations of both sets of variables with their dc-CA axis. Other values are: c("weights", "tvalues", "inter_set_correlation") for regression weights, t-values and inter-set correlation, being the correlation of the SNCs and CWMs with the traits and environmental variables, respectively. "regression" is an alias for "weights".
envfactor: name of row factor to display as color and lines in the CWM plot (default NULL). The default extracts the factor from the environmental model. If set to NA, no additional coloring and lines are displayed in plot.dcca. The parameter sets the groups variable in the CWM_SNC data frame of the return value/in the plot.
traitfactor: name of column factor to display as color and lines in the SNC plot (default NULL). The default extracts the factor from the trait model. If set to NA, no additional coloring and lines are displayed in plot.dcca. The parameter sets the groups variable in the CWM_SNC data frame of the return value/in the plot.
nspecies: integer. Default 20 for including a vertical species plot with at most nspecies that have the highest contribution.
species_groups: name of a variable in dataTraits of dc_CA. Default NULL for no grouping. Species groups are colored differentially.
widths: relative widths of the CWM-SNC plot, the correlation/weight plot and the species plot. (see grid.arrange). Default c(5, 1, 1).
newnames: a list with two elements: names for traits and for environmental variables, default NULL for names derived from the result of scores.dcca with tidy = TRUE.
facet: logical. Default TRUE for CWMs and SNCs plots in separate panels. This parameter changes the position of the centroid names (from left to right for the environmental centroids). If facet = FALSE and with_lines = TRUE, the line fits ignore groups of species and of sites.
remove_centroids: logical to remove any centroids from the plot data (default FALSE). Can be a two-vector, e.g. c(TRUE, FALSE) to remove only the trait centroids.
with_lines: integer values (0,1,2). Default 2 for straight lines through groups of points, with confidence intervals around the lines. with_lines=1 drops the confidence intervals and with_lines=0 suppresses the lines.
flip_axis: flip the direction of the axis? (default FALSE).
expand: amount of extension of the line plot (default 0.2).
formula: formula to use by ggplot geom_smooth (default y~x).
verbose: logical. Default TRUE for plotting the result.

Value

a ggplot object

Details

The current implementation does not distinguish groups of points, if there are two or more factors specified in the model. If you want to label one trait factor, specify traitfactor="yourfactor" and similarly specify envfactor="yourfactor" for your environmental factor.

No lines are plotted if a single factor defines a model.

If you want to set new names, look at the names with all arguments default, i.e. myplot <- plot(x), and then consult myplot$nameList$newnames for the order of the names of traits and environmental variables. Note that covariates should not be in the list of names. Contribution (in the definition of species selection in nspecies) is defined (as in CA) as the total species abundance in the (possibly, closed) data multiplied by the square of the score on the axis.

If the plot.dcca returns the error "Error in grid.Call", enlarge the plotting area or use verbose = FALSE and assign the result.

Examples

data("dune_trait_env")

# rownames are carried forward in results
rownames(dune_trait_env$comm) <- dune_trait_env$comm$Sites

# must delete "Sites" from response matrix or data frame
Y <- dune_trait_env$comm[, -1] # must delete "Sites"

out <- dc_CA(formulaEnv = ~ A1 + Moist + Use + Manure + Mag,
                   formulaTraits = ~ SLA + Height + LDMC + Seedmass + Lifespan,
                   response = Y,
                   dataEnv = dune_trait_env$envir,
                   dataTraits = dune_trait_env$traits,
                   verbose = FALSE)
dat <- getPlotdata(out)
names(dat)
#> [1] "CWM_SNC"          "trait_env_scores" "oldNameList"      "newNameList"     
names(dat$CWM_SNC)
#>  [1] "dcCA1"         "score"         "label"         "CWM-SNC"      
#>  [5] "weight"        "type"          "points"        "sizeweight"   
#>  [9] "smoothweight"  "xforsmooth"    "groups"        "names"        
#> [13] "centroidnames"
levels(dat$CWM_SNC$groups)
#> [1] "SF"        "BF"        "HF"        "NM"        "annual"    "perennial"

plot(out)