ordicoeno: Coenoclines for an Ordination Axis

ordicoenoR Documentation

Coenoclines for an Ordination Axis

Description

A graph is produced that summarizes (through GAM as implemented by gam) how the abundance of all species of the community data set change along an ordination axis (based on the position of sites along the axis and the information from the community data set).

Usage

ordicoeno(x, ordiplot, axis = 1, legend = FALSE, cex = 0.8, ncol = 4, ...)

Arguments

x

Community data frame with sites as rows, species as columns and species abundance as cell values.

ordiplot

Ordination plot created by ordiplot.

axis

Axis of the ordination graph (1: horizontal, 2: vertical).

legend

if TRUE, then add a legend to the plot.

cex

the amount by which plotting text and symbols should be magnified relative to the default; see also par

ncol

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

...

Other arguments passed to functions plot and points.

Details

This functions investigates the relationship between the species vectors and the position of sites on an ordination axis. A GAM (gam) investigates the relationship by using the species abundances of each species as response variable, and the site position as the explanatory variable. The graph shows how the abundance of each species changes over the gradient of the ordination axis.

Value

The function plots coenoclines and provides the expected degrees of freedom (complexity of the relationship) estimated for each species by GAM.

Author(s)

Roeland Kindt (World Agroforestry Centre)

References

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)
library(mgcv)
data(dune)
Ordination.model1 <- rda(dune)
plot1 <- ordiplot(Ordination.model1, choices=c(1,2), scaling=1)
ordicoeno(dune, ordiplot=plot1, legend=TRUE)

BiodiversityR documentation built on June 22, 2024, 11:57 a.m.