R: Community Ecology Package: Ordination, Diversity and...

vegan-package {vegan} | R Documentation

## Community Ecology Package: Ordination, Diversity and Dissimilarities

### Description

The vegan package provides tools for descriptive community ecology. It has most basic functions of diversity analysis, community ordination and dissimilarity analysis. Most of its multivariate tools can be used for other data types as well.

### Details

The functions in the vegan package contain tools for diversity analysis, ordination methods and tools for the analysis of dissimilarities. Together with the labdsv package, the vegan package provides most standard tools of descriptive community analysis. Package ade4 provides an alternative comprehensive package, and several other packages complement vegan and provide tools for deeper analysis in specific fields. Package BiodiversityR provides a GUI for a large subset of vegan functionality.

The vegan package is developed at GitHub (https://github.com/vegandevs/vegan/). GitHub provides up-to-date information and forums for bug reports.

Most important changes in vegan documents can be read with `news(package="vegan")` and vignettes can be browsed with `browseVignettes("vegan")`. The vignettes include a vegan FAQ, discussion on design decisions, short introduction to ordination and discussion on diversity methods. A tutorial of the package at http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf provides a more thorough introduction to the package.

To see the preferable citation of the package, type `citation("vegan")`.

### Author(s)

The vegan development team is Jari Oksanen, F. Guillaume Blanchet, Roeland Kindt, Pierre Legendre, Peter R. Minchin, R. B. O'Hara, Gavin L. Simpson, Peter Solymos, M. Henry H. Stevens, Helene Wagner. Many other people have contributed to individual functions: see credits in function help pages.

### Examples

    ### Example 1: Unconstrained ordination
    ## NMDS
    data(varespec)
    data(varechem)
    ord <- metaMDS(varespec)
    plot(ord, type = "t")
    ## Fit environmental variables
    ef <- envfit(ord, varechem)
    ef
    plot(ef, p.max = 0.05)
    ### Example 2: Constrained ordination (RDA)
    ## The example uses formula interface to define the model
    data(dune)
    data(dune.env)
    ## No constraints: PCA
    mod0 <- rda(dune ~ 1, dune.env)
    mod0
    plot(mod0)
    ## All environmental variables: Full model
    mod1 <- rda(dune ~ ., dune.env)
    mod1
    plot(mod1)
    ## Automatic selection of variables by permutation P-values
    mod <- ordistep(mod0, scope=formula(mod1))
    mod
    plot(mod)
    ## Permutation test for all variables
    anova(mod)
    ## Permutation test of "type III" effects, or significance when a term
    ## is added to the model after all other terms
    anova(mod, by = "margin")
    ## Plot only sample plots, use different symbols and draw SD ellipses
    ## for Managemenet classes
    plot(mod, display = "sites", type = "n")
    with(dune.env, points(mod, disp = "si", pch = as.numeric(Management)))
    with(dune.env, legend("topleft", levels(Management), pch = 1:4,
      title = "Management"))
    with(dune.env, ordiellipse(mod, Management, label = TRUE))
    ## add fitted surface of diversity to the model
    ordisurf(mod, diversity(dune), add = TRUE)
    ### Example 3: analysis of dissimilarites a.k.a. non-parametric
    ### permutational anova
    adonis(dune ~ ., dune.env)
    adonis(dune ~ Management + Moisture, dune.env)

[Package vegan version 2.4-3 Index]