ordisymbol {BiodiversityR}

Add Other Graphical Items to Ordination Diagrams

Description

Functions to add some other graphical itmes to ordination diagrams than provided within vegan by ordihull, ordispider, ordiarrows, ordisegments, ordigrid, ordiellipse, ordicluster and lines.spantree.

Usage

ordisymbol(ordiplot, y, factor, col = 1, colors = TRUE, pchs = TRUE,
    rainbow_hcl = TRUE, rainbow_hcl.c = 90, rainbow_hcl.l = 50, 
    rainbow = TRUE, heat.colors = FALSE, terrain.colors = FALSE,
    topo.colors = FALSE, cm.colors = FALSE,
    legend = TRUE, legend.x = "topleft", legend.ncol = 1, ...)
ordibubble(ordiplot,var,...)
ordicluster2(ordiplot, cluster, mingroups = 1, maxgroups = nrow(ordiplot$sites), ...)
ordinearest(ordiplot, dist,...)
ordivector(ordiplot, spec, lty=2,...)

Arguments

ordiplot

An ordination graph created by ordiplot (vegan).

y

Environmental data frame.

factor

Variable of the environmental data frame that defines subsets to be given different symbols.

var

Continous variable of the environmental dataset or species from the community dataset.

col

Colour (as points).

colors

Apply different colours to different factor levels

pchs

Apply different symbols (plotting characters) to different factor levels (as in points))

rainbow_hcl

Use rainbow_hcl colours (rainbow_hcl)

rainbow_hcl.c

Set the chroma value

rainbow_hcl.l

Set the luminance value

rainbow

Use rainbow colours

heat.colors

Use heat colours

terrain.colors

Use terrain colours

topo.colors

Use topo colours

cm.colors

Use cm colours

legend

Add the legend.

legend.x

Location of the legend; see also legend.

legend.ncol

the number of columns in which to set the legend items; see also legend

cluster

Cluster object.

mingroups

Minimum of clusters to be plotted.

maxgroups

Maximum of clusters to be plotted..

dist

Distance matrix.

spec

Species name from the community dataset.

lty

Line type as specified for par.

...

Other arguments passed to functions points, symbols, ordihull or arrows.

Details

Function ordisymbol plots different levels of the specified variable in different symbols and different colours. In case more than one colour palettes are selected, the last palette selected will be used.

Function ordibubble draws bubble diagrams indicating the value of the specified continuous variable. Circles indicate positive values, squares indicate negative values.

Function ordicluster2 provides an alternative method of overlaying information from hierarchical clustering on an ordination diagram than provided by function ordicluster. The method draws convex hulls around sites that are grouped into the same cluster. You can select the minimum and maximum number of clusters that are plotted (i.e. the range of clustering steps to be shown).

Function ordinearest draws a vector from each site to the site that is nearest to it as determined from a distance matrix. When you combine the method with lines.spantree using the same distance measure, then you can evaluate in part how the minimum spanning tree was constructed.

Function ordivector draws a vector for the specified species on the ordination diagramme and draws perpendicular lines from each site to a line that connects the origin and the head of species vector. This method helps in the biplot interpretation of a species vector as described by Jongman, ter Braak and van Tongeren (1995).

Value

These functions add graphical items to an existing ordination diagram.

Author(s)

Roeland Kindt (World Agroforestry Centre) and Jari Oksanen (ordinearest)

References

Jongman, R.H.G, ter Braak, C.J.F & van Tongeren, O.F.R. (1987). Data Analysis in Community and Landscape Ecology. Pudog, Wageningen.

Kindt, R. & Coe, R. (2005). Tree diversity analysis: A manual and software for common statistical methods for ecological and biodiversity studies.

https://www.worldagroforestry.org/output/tree-diversity-analysis

Examples

library(vegan)
data(dune)
data(dune.env)
Ordination.model1 <- rda(dune)
plot1 <- ordiplot(Ordination.model1, choices=c(1,2), scaling=2)
ordisymbol(plot1, dune.env, "Management", legend=TRUE, 
    legend.x="topleft", legend.ncol=1)
plot2 <- ordiplot(Ordination.model1, choices=c(1,2), scaling=1)
distmatrix <- vegdist(dune, method='bray')
cluster <- hclust(distmatrix, method='single')
ordicluster2(plot2, cluster)
ordinearest(plot2, distmatrix, col=2)
ordivector(plot2, "Agrostol", lty=2)