Function reference • vegan

All functions
`BCI` `BCI.env`	Barro Colorado Island Tree Counts
`CCorA()` `biplot(<CCorA>)`	Canonical Correlation Analysis
`MDSrotate()`	Rotate First MDS Dimension Parallel to an External Variable
`MOStest()` `plot(<MOStest>)` `fieller.MOStest()` `profile(<MOStest>)` `confint(<MOStest>)`	Mitchell-Olds \& Shaw Test for the Location of Quadratic Extreme
`RsquareAdj(<default>)` `RsquareAdj(<rda>)` `RsquareAdj(<cca>)`	Adjusted R-square
`SSarrhenius()` `SSgleason()` `SSgitay()` `SSlomolino()`	Self-Starting nls Species-Area Models
`add1(<cca>)` `drop1(<cca>)`	Add or Drop Single Terms to a Constrained Ordination Model
`adipart()` `hiersimu()`	Additive Diversity Partitioning and Hierarchical Null Model Testing
`adonis()`	Permutational Multivariate Analysis of Variance Using Distance Matrices
`anosim()`	Analysis of Similarities
`anova(<cca>)` `permutest(<cca>)`	Permutation Test for Constrained Correspondence Analysis, Redundancy Analysis and Constrained Analysis of Principal Coordinates
`avgdist()`	Averaged Subsampled Dissimilarity Matrices
`beals()` `swan()`	Beals Smoothing and Degree of Absence
`betadisper()` `anova(<betadisper>)` `scores(<betadisper>)` `eigenvals(<betadisper>)` `plot(<betadisper>)` `boxplot(<betadisper>)` `TukeyHSD(<betadisper>)` `print(<betadisper>)`	Multivariate homogeneity of groups dispersions (variances)
`betadiver()` `plot(<betadiver>)` `scores(<betadiver>)`	Indices of beta Diversity
`bgdispersal()`	Coefficients of Biogeographical Dispersal Direction
`bioenv(<default>)` `bioenv(<formula>)` `bioenvdist()`	Best Subset of Environmental Variables with Maximum (Rank) Correlation with Community Dissimilarities
`biplot(<rda>)`	PCA biplot
`capscale()` `dbrda()`	[Partial] Distance-based Redundancy Analysis
`cascadeKM()` `cIndexKM()` `plot(<cascadeKM>)`	K-means partitioning using a range of values of K
`cca(<formula>)` `rda(<formula>)` `cca(<default>)` `rda(<default>)`	[Partial] [Constrained] Correspondence Analysis and Redundancy Analysis
`ordiYbar()` `model.frame(<cca>)` `model.matrix(<cca>)` `weights(<cca>)`	Result Object from Constrained Ordination
`clamtest()` `summary(<clamtest>)` `plot(<clamtest>)`	Multinomial Species Classification Method (CLAM)
`commsim()` `make.commsim()` `print(<commsim>)`	Create an Object for Null Model Algorithms
`contribdiv()` `plot(<contribdiv>)`	Contribution Diversity Approach
`decorana()` `plot(<decorana>)` `text(<decorana>)` `points(<decorana>)` `summary(<decorana>)` `print(<summary.decorana>)` `downweight()` `scores(<decorana>)`	Detrended Correspondence Analysis and Basic Reciprocal Averaging
`decostand()` `wisconsin()`	Standardization Methods for Community Ecology
`designdist()` `chaodist()`	Design your own Dissimilarities
`deviance(<cca>)` `extractAIC(<cca>)`	Statistics Resembling Deviance and AIC for Constrained Ordination
`dispindmorisita()`	Morisita index of intraspecific aggregation
`dispweight()` `gdispweight()` `summary(<dispweight>)`	Dispersion-based weighting of species counts
`distconnected()` `no.shared()`	Connectedness of Dissimilarities
`diversity()` `fisher.alpha()` `specnumber()`	Ecological Diversity Indices
`dune` `dune.env`	Vegetation and Environment in Dutch Dune Meadows.
`dune.taxon` `dune.phylodis`	Taxonomic Classification and Phylogeny of Dune Meadow Species
`eigenvals()` `summary(<eigenvals>)`	Extract Eigenvalues from an Ordination Object
`envfit(<default>)` `envfit(<formula>)` `plot(<envfit>)` `scores(<envfit>)` `vectorfit()` `factorfit()`	Fits an Environmental Vector or Factor onto an Ordination
`eventstar()`	Scale Parameter at the Minimum of the Tsallis Evenness Profile
`fisherfit()` `prestonfit()` `prestondistr()` `plot(<prestonfit>)` `lines(<prestonfit>)` `veiledspec()` `as.fisher()` `plot(<fisher>)` `as.preston()` `plot(<preston>)` `lines(<preston>)`	Fit Fisher's Logseries and Preston's Lognormal Model to Abundance Data
`goodness(<cca>)` `inertcomp()` `spenvcor()` `intersetcor()` `vif.cca()` `alias(<cca>)`	Diagnostic Tools for [Constrained] Ordination (CCA, RDA, DCA, CA, PCA)
`goodness(<metaMDS>)` `stressplot(<default>)`	Goodness of Fit and Shepard Plot for Nonmetric Multidimensional Scaling
`indpower()`	Indicator Power of Species
`hatvalues(<cca>)` `rstandard(<cca>)` `rstudent(<cca>)` `cooks.distance(<cca>)` `sigma(<cca>)` `vcov(<cca>)` `SSD(<cca>)` `qr(<cca>)` `df.residual(<cca>)`	Linear Model Diagnostics for Constrained Ordination
`isomap()` `isomapdist()` `summary(<isomap>)` `plot(<isomap>)`	Isometric Feature Mapping Ordination
`kendall.global()` `kendall.post()`	Kendall coefficient of concordance
`linestack()`	Plots One-dimensional Diagrams without Overwriting Labels
`make.cepnames()`	Abbreviates a Botanical or Zoological Latin Name into an Eight-character Name
`mantel()` `mantel.partial()`	Mantel and Partial Mantel Tests for Dissimilarity Matrices
`mantel.correlog()` `plot(<mantel.correlog>)`	Mantel Correlogram
`metaMDS()` `plot(<metaMDS>)` `points(<metaMDS>)` `text(<metaMDS>)` `scores(<metaMDS>)` `metaMDSdist()` `metaMDSiter()` `initMDS()` `postMDS()` `metaMDSredist()`	Nonmetric Multidimensional Scaling with Stable Solution from Random Starts, Axis Scaling and Species Scores
`mite` `mite.env` `mite.pcnm` `mite.xy`	Oribatid Mite Data with Explanatory Variables
`monoMDS()` `scores(<monoMDS>)` `plot(<monoMDS>)` `points(<monoMDS>)` `text(<monoMDS>)`	Global and Local Non-metric Multidimensional Scaling and Linear and Hybrid Scaling
`mrpp()` `meandist()` `summary(<meandist>)` `plot(<meandist>)`	Multi Response Permutation Procedure and Mean Dissimilarity Matrix
`mso()` `msoplot()`	Functions for performing and displaying a spatial partitioning of cca or rda results
`multipart()`	Multiplicative Diversity Partitioning
`nestedchecker()` `nestedn0()` `nesteddisc()` `nestedtemp()` `nestednodf()` `nestedbetasor()` `nestedbetajac()` `plot(<nestedtemp>)` `plot(<nestednodf>)`	Nestedness Indices for Communities of Islands or Patches
`nobs(<cca>)`	Extract the Number of Observations from a vegan Fit.
`nullmodel()` `print(<nullmodel>)` `simulate(<nullmodel>)` `update(<nullmodel>)` `print(<simmat>)` `smbind()`	Null Model and Simulation
`oecosimu()` `as.ts(<oecosimu>)` `as.mcmc(<oecosimu>)`	Evaluate Statistics with Null Models of Biological Communities
`ordiArrowTextXY()` `ordiArrowMul()`	Support Functions for Drawing Vectors
`ordiarrows()` `ordisegments()` `ordigrid()`	Add Arrows and Line Segments to Ordination Diagrams
`ordihull()` `ordiellipse()` `ordibar()` `ordispider()` `ordicluster()` `summary(<ordihull>)` `summary(<ordiellipse>)` `ordiareatest()`	Display Groups or Factor Levels in Ordination Diagrams
`ordilabel()`	Add Text on Non-transparent Label to an Ordination Plot.
`ordiplot()` `identify(<ordiplot>)` `points(<ordiplot>)` `text(<ordiplot>)`	Alternative plot and identify Functions for Ordination
`ordipointlabel()` `plot(<ordipointlabel>)`	Ordination Plots with Points and Optimized Locations for Text
`ordiresids()`	Plots of Residuals and Fitted Values for Constrained Ordination
`ordistep()` `ordiR2step()`	Choose a Model by Permutation Tests in Constrained Ordination
`ordisurf(<default>)` `ordisurf(<formula>)` `calibrate(<ordisurf>)` `plot(<ordisurf>)`	Fit and Plot Smooth Surfaces of Variables on Ordination.
`orditkplot()` `plot(<orditkplot>)` `points(<orditkplot>)` `text(<orditkplot>)` `scores(<orditkplot>)`	Ordination Plot with Movable Labels
`orditorp()`	Add Text or Points to Ordination Plots
`ordixyplot()` `ordisplom()` `ordicloud()`	Trellis (Lattice) Plots for Ordination
`pcnm()`	Principal Coordinates of Neighbourhood Matrix
`permatfull()` `permatswap()` `print(<permat>)` `summary(<permat>)` `print(<summary.permat>)` `plot(<permat>)` `lines(<permat>)` `as.ts(<permat>)` `as.mcmc(<permat>)`	Matrix Permutation Algorithms for Presence-Absence and Count Data
`permustats()` `summary(<permustats>)` `densityplot(<permustats>)` `density(<permustats>)` `qqnorm(<permustats>)` `qqmath(<permustats>)` `boxplot(<permustats>)` `pairs(<permustats>)`	Extract, Analyse and Display Permutation Results
`permutations`	Permutation tests in Vegan
`permutest(<betadisper>)`	Permutation test of multivariate homogeneity of groups dispersions (variances)
`plot(<cca>)` `text(<cca>)` `points(<cca>)` `scores(<cca>)` `scores(<rda>)` `summary(<cca>)` `print(<summary.cca>)` `head(<summary.cca>)` `tail(<summary.cca>)`	Plot or Extract Results of Constrained Correspondence Analysis or Redundancy Analysis
`prc()` `summary(<prc>)` `plot(<prc>)`	Principal Response Curves for Treatments with Repeated Observations
`fitted(<cca>)` `fitted(<capscale>)` `residuals(<cca>)` `predict(<cca>)` `predict(<rda>)` `calibrate(<cca>)` `coef(<cca>)` `predict(<decorana>)`	Prediction Tools for [Constrained] Ordination (CCA, RDA, DCA, CA, PCA)
`procrustes()` `summary(<procrustes>)` `plot(<procrustes>)` `points(<procrustes>)` `text(<procrustes>)` `lines(<procrustes>)` `residuals(<procrustes>)` `fitted(<procrustes>)` `predict(<procrustes>)` `protest()`	Procrustes Rotation of Two Configurations and PROTEST
`pyrifos`	Response of Aquatic Invertebrates to Insecticide Treatment
`radfit(<default>)` `rad.null()` `rad.preempt()` `rad.lognormal()` `rad.zipf()` `rad.zipfbrot()` `predict(<radline>)` `plot(<radfit>)` `plot(<radfit.frame>)` `plot(<radline>)` `radlattice()` `lines(<radfit>)` `points(<radfit>)` `as.rad()` `plot(<rad>)`	Rank -- Abundance or Dominance / Diversity Models
`rankindex()`	Compares Dissimilarity Indices for Gradient Detection
`rarefy()` `rrarefy()` `drarefy()` `rarecurve()` `rareslope()`	Rarefaction Species Richness
`raupcrick()`	Raup-Crick Dissimilarity with Unequal Sampling Densities of Species
`read.cep()`	Reads a CEP (Canoco) data file
`renyi()` `plot(<renyi>)` `renyiaccum()` `plot(<renyiaccum>)` `persp(<renyiaccum>)`	Renyi and Hill Diversities and Corresponding Accumulation Curves
`reorder(<hclust>)` `rev(<hclust>)` `scores(<hclust>)` `cutreeord()`	Reorder a Hierarchical Clustering Tree
`scores(<default>)`	Get Species or Site Scores from an Ordination
`screeplot(<cca>)` `screeplot(<decorana>)` `screeplot(<prcomp>)` `screeplot(<princomp>)` `bstick()`	Screeplots for Ordination Results and Broken Stick Distributions
`simper()` `summary(<simper>)`	Similarity Percentages
`simulate(<rda>)`	Simulate Responses with Gaussian Error or Permuted Residuals for Constrained Ordination
`sipoo` `sipoo.map`	Birds in the Archipelago of Sipoo (Sibbo and Borgå)
`spantree()` `as.hclust(<spantree>)` `cophenetic(<spantree>)` `spandepth()` `plot(<spantree>)` `lines(<spantree>)`	Minimum Spanning Tree
`specaccum()` `plot(<specaccum>)` `boxplot(<specaccum>)` `fitspecaccum()` `plot(<fitspecaccum>)` `predict(<specaccum>)` `predict(<fitspecaccum>)` `specslope()`	Species Accumulation Curves
`specpool()` `estimateR()` `specpool2vect()` `poolaccum()` `estaccumR()` `summary(<poolaccum>)` `plot(<poolaccum>)`	Extrapolated Species Richness in a Species Pool
`sppscores<-`()	Add or Replace Species Scores in Distance-Based Ordination
`stepacross()`	Stepacross as Flexible Shortest Paths or Extended Dissimilarities
`stressplot(<wcmdscale>)`	Display Ordination Distances Against Observed Distances in Eigenvector Ordinations
`taxondive()` `taxa2dist()`	Indices of Taxonomic Diversity and Distinctness
`tolerance()`	Species tolerances and sample heterogeneities
`treedive()` `treeheight()` `treedist()`	Functional Diversity and Community Distances from Species Trees
`tsallis()` `tsallisaccum()` `persp(<tsallisaccum>)`	Tsallis Diversity and Corresponding Accumulation Curves
`varechem` `varespec`	Vegetation and environment in lichen pastures
`varpart()` `showvarparts()` `plot(<varpart234>)`	Partition the Variation of Community Matrix by 2, 3, or 4 Explanatory Matrices
`vegan-deprecated`	Deprecated Functions in vegan package
`ordiParseFormula()` `ordiTerminfo()` `ordiNAexclude()` `ordiNApredict()` `ordiArgAbsorber()` `centroids.cca()` `getPermuteMatrix()` `howHead()` `pasteCall()` `veganCovEllipse()` `veganMahatrans()` `hierParseFormula()` `GowerDblcen()` `addLingoes()` `addCailliez()`	Internal vegan functions
`vegan-package`	Community Ecology Package: Ordination, Diversity and Dissimilarities
`vegdist()`	Dissimilarity Indices for Community Ecologists
`vegemite()` `tabasco()` `coverscale()`	Display Compact Ordered Community Tables
`wascores()` `eigengrad()`	Weighted Averages Scores for Species
`wcmdscale()` `plot(<wcmdscale>)` `scores(<wcmdscale>)`	Weighted Classical (Metric) Multidimensional Scaling

Reference

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