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.
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
a more thorough introduction to the package.
To see the preferable citation of the package, type
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.
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### 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)
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