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BCI
BCI.env
- Barro Colorado Island Tree Counts
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CCorA()
biplot(<CCorA>)
- Canonical Correlation Analysis
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MDSaddpoints()
dist2xy()
- Add New Points to NMDS ordination
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MDSrotate()
- Rotate First MDS Dimension Parallel to an External Variable
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MOStest()
plot(<MOStest>)
fieller.MOStest()
profile(<MOStest>)
confint(<MOStest>)
- Mitchell-Olds and Shaw Test for the Location of Quadratic Extreme
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RsquareAdj(<default>)
RsquareAdj(<rda>)
RsquareAdj(<cca>)
- Adjusted R-square
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SSarrhenius()
SSgleason()
SSgitay()
SSlomolino()
- Self-Starting nls Species-Area Models
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add1(<cca>)
drop1(<cca>)
- Add or Drop Single Terms to a Constrained Ordination Model
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adipart()
hiersimu()
- Additive Diversity Partitioning and Hierarchical Null Model Testing
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adonis2()
- Permutational Multivariate Analysis of Variance Using Distance Matrices
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anosim()
- Analysis of Similarities
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anova(<cca>)
permutest(<cca>)
- Permutation Test for Constrained Correspondence Analysis, Redundancy Analysis and Constrained Analysis of Principal Coordinates
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avgdist()
- Averaged Subsampled Dissimilarity Matrices
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beals()
swan()
- Beals Smoothing and Degree of Absence
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betadisper()
anova(<betadisper>)
scores(<betadisper>)
eigenvals(<betadisper>)
plot(<betadisper>)
boxplot(<betadisper>)
TukeyHSD(<betadisper>)
print(<betadisper>)
- Multivariate homogeneity of groups dispersions (variances)
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betadiver()
plot(<betadiver>)
scores(<betadiver>)
- Indices of beta Diversity
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bgdispersal()
- Coefficients of Biogeographical Dispersal Direction
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bioenv(<default>)
bioenv(<formula>)
bioenvdist()
- Best Subset of Environmental Variables with Maximum (Rank) Correlation with Community Dissimilarities
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biplot(<rda>)
- PCA biplot
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cascadeKM()
cIndexKM()
plot(<cascadeKM>)
- K-means partitioning using a range of values of K
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cca(<formula>)
rda(<formula>)
cca(<default>)
rda(<default>)
ca()
pca()
- [Partial] [Constrained] Correspondence Analysis and Redundancy Analysis
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ordiYbar()
model.frame(<cca>)
model.matrix(<cca>)
weights(<cca>)
- Result Object from Constrained Ordination
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centredist(<default>)
centredist(<betadisper>)
centredist(<cca>)
centredist(<rda>)
centredist(<dbrda>)
centredist(<wcmdscale>)
- Distances of Points to Class Centroids
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clamtest()
summary(<clamtest>)
plot(<clamtest>)
- Multinomial Species Classification Method (CLAM)
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commsim()
make.commsim()
print(<commsim>)
- Create an Object for Null Model Algorithms
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contribdiv()
plot(<contribdiv>)
- Contribution Diversity Approach
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dbrda()
capscale()
pco()
- Principal Coordinates Analysis and [Partial] Distance-based Redundancy Analysis
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decorana()
plot(<decorana>)
text(<decorana>)
points(<decorana>)
scores(<decorana>)
downweight()
- Detrended Correspondence Analysis and Basic Reciprocal Averaging
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decostand()
wisconsin()
decobackstand()
- Standardization Methods for Community Ecology
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designdist()
designdist2()
chaodist()
- Design your own Dissimilarities
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deviance(<cca>)
extractAIC(<cca>)
- Statistics Resembling Deviance and AIC for Constrained Ordination
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dispindmorisita()
- Morisita index of intraspecific aggregation
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dispweight()
gdispweight()
summary(<dispweight>)
- Dispersion-based weighting of species counts
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distconnected()
no.shared()
- Connectedness of Dissimilarities
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diversity()
simpson.unb()
fisher.alpha()
specnumber()
- Ecological Diversity Indices
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dune
dune.env
- Vegetation and Environment in Dutch Dune Meadows.
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dune.taxon
dune.phylodis
- Taxonomic Classification and Phylogeny of Dune Meadow Species
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eigenvals()
summary(<eigenvals>)
- Extract Eigenvalues from an Ordination Object
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envfit(<default>)
envfit(<formula>)
plot(<envfit>)
scores(<envfit>)
vectorfit()
factorfit()
- Fits an Environmental Vector or Factor onto an Ordination
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eventstar()
- Scale Parameter at the Minimum of the Tsallis Evenness Profile
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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
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goodness(<cca>)
inertcomp()
spenvcor()
intersetcor()
vif.cca()
alias(<cca>)
- Diagnostic Tools for [Constrained] Ordination (CCA, RDA, DCA, CA, PCA)
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goodness(<metaMDS>)
stressplot(<default>)
- Goodness of Fit and Shepard Plot for Nonmetric Multidimensional Scaling
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indpower()
- Indicator Power of Species
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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
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isomap()
isomapdist()
summary(<isomap>)
plot(<isomap>)
- Isometric Feature Mapping Ordination
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kendall.global()
kendall.post()
- Kendall coefficient of concordance
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linestack()
- Plots One-dimensional Diagrams without Overwriting Labels
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make.cepnames()
- Abbreviates a Two-Part Botanical or Zoological Latin Name into Character String
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mantel()
mantel.partial()
- Mantel and Partial Mantel Tests for Dissimilarity Matrices
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mantel.correlog()
plot(<mantel.correlog>)
- Mantel Correlogram
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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
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mite
mite.env
mite.pcnm
mite.xy
- Oribatid Mite Data with Explanatory Variables
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monoMDS()
scores(<monoMDS>)
plot(<monoMDS>)
points(<monoMDS>)
text(<monoMDS>)
- Global and Local Non-metric Multidimensional Scaling and Linear and Hybrid Scaling
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mrpp()
meandist()
summary(<meandist>)
plot(<meandist>)
- Multi Response Permutation Procedure and Mean Dissimilarity Matrix
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mso()
msoplot()
- Functions for performing and displaying a spatial partitioning of cca or rda results
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multipart()
- Multiplicative Diversity Partitioning
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nestedchecker()
nestedn0()
nesteddisc()
nestedtemp()
nestednodf()
nestedbetasor()
nestedbetajac()
plot(<nestedtemp>)
plot(<nestednodf>)
- Nestedness Indices for Communities of Islands or Patches
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nobs(<cca>)
- Extract the Number of Observations from a vegan Fit.
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nullmodel()
print(<nullmodel>)
simulate(<nullmodel>)
update(<nullmodel>)
print(<simmat>)
smbind()
- Null Model and Simulation
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oecosimu()
as.ts(<oecosimu>)
toCoda(<oecosimu>)
- Evaluate Statistics with Null Models of Biological Communities
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ordiArrowTextXY()
ordiArrowMul()
- Support Functions for Drawing Vectors
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ordiarrows()
ordisegments()
ordigrid()
- Add Arrows and Line Segments to Ordination Diagrams
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ordihull()
ordiellipse()
ordibar()
ordispider()
ordicluster()
summary(<ordihull>)
summary(<ordiellipse>)
ordiareatest()
- Display Groups or Factor Levels in Ordination Diagrams
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ordilabel()
- Add Text on Non-transparent Label to an Ordination Plot.
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ordiplot()
points(<ordiplot>)
text(<ordiplot>)
identify(<ordiplot>)
- Alternative plot and identify Functions for Ordination
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ordipointlabel()
plot(<ordipointlabel>)
- Ordination Plots with Points and Optimized Locations for Text
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ordiresids()
- Plots of Residuals and Fitted Values for Constrained Ordination
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ordistep()
ordiR2step()
- Choose a Model by Permutation Tests in Constrained Ordination
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ordisurf(<default>)
ordisurf(<formula>)
calibrate(<ordisurf>)
plot(<ordisurf>)
- Fit and Plot Smooth Surfaces of Variables on Ordination.
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orditorp()
- Add Text or Points to Ordination Plots
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ordixyplot()
ordisplom()
ordicloud()
- Trellis (Lattice) Plots for Ordination
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pcnm()
- Principal Coordinates of Neighbourhood Matrix
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permatfull()
permatswap()
print(<permat>)
summary(<permat>)
print(<summary.permat>)
plot(<permat>)
lines(<permat>)
as.ts(<permat>)
toCoda(<permat>)
- Matrix Permutation Algorithms for Presence-Absence and Count Data
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permustats()
summary(<permustats>)
densityplot(<permustats>)
density(<permustats>)
qqnorm(<permustats>)
qqmath(<permustats>)
boxplot(<permustats>)
pairs(<permustats>)
- Extract, Analyse and Display Permutation Results
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permutations
- Permutation tests in Vegan
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permutest(<betadisper>)
- Permutation test of multivariate homogeneity of groups dispersions (variances)
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plot(<cca>)
text(<cca>)
points(<cca>)
scores(<cca>)
scores(<rda>)
summary(<cca>)
labels(<cca>)
- Plot or Extract Results of Constrained Correspondence Analysis or Redundancy Analysis
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prc()
summary(<prc>)
plot(<prc>)
- Principal Response Curves for Treatments with Repeated Observations
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fitted(<cca>)
fitted(<capscale>)
residuals(<cca>)
predict(<cca>)
predict(<rda>)
predict(<dbrda>)
calibrate(<cca>)
coef(<cca>)
predict(<decorana>)
- Prediction Tools for [Constrained] Ordination (CCA, RDA, DCA, CA, PCA)
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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
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pyrifos
- Response of Aquatic Invertebrates to Insecticide Treatment
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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
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rankindex()
- Compares Dissimilarity Indices for Gradient Detection
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rarefy()
rrarefy()
drarefy()
rarecurve()
rareslope()
- Rarefaction Species Richness
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raupcrick()
- Raup-Crick Dissimilarity with Unequal Sampling Densities of Species
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read.cep()
- Reads a CEP (Canoco) data file
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renyi()
plot(<renyi>)
renyiaccum()
plot(<renyiaccum>)
persp(<renyiaccum>)
- Renyi and Hill Diversities and Corresponding Accumulation Curves
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reorder(<hclust>)
rev(<hclust>)
scores(<hclust>)
cutreeord()
- Reorder a Hierarchical Clustering Tree
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scores(<default>)
- Get Species or Site Scores from an Ordination
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screeplot(<cca>)
screeplot(<decorana>)
screeplot(<prcomp>)
screeplot(<princomp>)
bstick()
- Screeplots for Ordination Results and Broken Stick Distributions
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simper()
summary(<simper>)
- Similarity Percentages
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simulate(<rda>)
- Simulate Responses with Gaussian Error or Permuted Residuals for Constrained Ordination
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sipoo
sipoo.map
- Birds in the Archipelago of Sipoo (Sibbo and Borgå)
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spantree()
as.hclust(<spantree>)
cophenetic(<spantree>)
spandepth()
plot(<spantree>)
lines(<spantree>)
- Minimum Spanning Tree
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specaccum()
plot(<specaccum>)
boxplot(<specaccum>)
fitspecaccum()
plot(<fitspecaccum>)
predict(<specaccum>)
predict(<fitspecaccum>)
specslope()
- Species Accumulation Curves
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specpool()
estimateR()
specpool2vect()
poolaccum()
estaccumR()
summary(<poolaccum>)
plot(<poolaccum>)
- Extrapolated Species Richness in a Species Pool
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`sppscores<-`()
- Add or Replace Species Scores in Distance-Based Ordination
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stepacross()
- Stepacross as Flexible Shortest Paths or Extended Dissimilarities
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stressplot(<wcmdscale>)
- Display Ordination Distances Against Observed Distances in Eigenvector Ordinations
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taxondive()
taxa2dist()
- Indices of Taxonomic Diversity and Distinctness
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tolerance()
- Species tolerances and sample heterogeneities
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treedive()
treeheight()
treedist()
- Functional Diversity and Community Distances from Species Trees
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tsallis()
tsallisaccum()
persp(<tsallisaccum>)
- Tsallis Diversity and Corresponding Accumulation Curves
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varechem
varespec
- Vegetation and environment in lichen pastures
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varpart()
summary(<varpart>)
showvarparts()
plot(<varpart234>)
- Partition the Variation of Community Matrix by 2, 3, or 4 Explanatory Matrices
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orditkplot()
as.mcmc.oecosimu()
as.mcmc.permat()
- Deprecated Functions in vegan package
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ordiParseFormula()
ordiTerminfo()
ordiNAexclude()
ordiNApredict()
ordiArgAbsorber()
centroids.cca()
getPermuteMatrix()
howHead()
pasteCall()
veganCovEllipse()
veganMahatrans()
hierParseFormula()
GowerDblcen()
addLingoes()
addCailliez()
- Internal vegan functions
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vegan-package
vegan
- Community Ecology Package: Ordination, Diversity and Dissimilarities
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vegdist()
- Dissimilarity Indices for Community Ecologists
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vegemite()
tabasco()
coverscale()
- Display Compact Ordered Community Tables
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wascores()
eigengrad()
scores(<wascores>)
- Weighted Averages Scores for Species
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wcmdscale()
plot(<wcmdscale>)
scores(<wcmdscale>)
- Weighted Classical (Metric) Multidimensional Scaling