Introduction | What is vegan? | How to obtain vegan and R? | What other packages are available for ecologists? | What other documentation is available for vegan? | Is there a Graphical User Interface (GUI) for vegan? | How to cite vegan? | How to build vegan from sources? | Are there binaries for devel versions? | How to report a bug in vegan? | Is it a bug or a feature? | Can I contribute to vegan? | Ordination | I have only numeric and positive data but vegan still complains | Can I use tibbles in ordination? | Can I analyse binary or cover class data? | Why dissimilarities in vegan differ from other sources? | I cannot get repeated solutions in metaMDS | I get zero stress but no repeated solutions in metaMDS | I have heard that you cannot fit environmental vectors or surfaces to NMDS results which only have rank-order scores | Why ordiellipses are much smaller than ggplot2 ellipses? | Where can I find numerical scores of ordination axes? | How the RDA results are scaled? | Variance explained by ordination axes. | Can I have random effects in constrained ordination or in adonis? | Is it possible to have passive points in ordination? | Class variables and dummies | How are environmental arrows scaled? | I cannot see all variables in constrained ordination | Plotting aliased variables | Restricted permutations in vegan | Why restricted permutation does not influence adonis results? | How to use different plotting symbols in ordination graphics? | How to avoid cluttered ordination graphs? | Can I flip an axis in ordination diagram? | Can I zoom into an ordination plot? | Other analysis methods | Is there TWINSPAN?

Diversity indices | Rarefaction | Taxonomic and functional diversity | Species abundance models | Species accumulation and beta diversity | Species pool

Ordination | Ordination graphics | Fitting environmental variables | Constrained ordination

Introduction | Motivation | Design and implementation | Limitations

Landscape | Population | Behavior | Detection | Transcription | Statistical validity of the simulations

Sensitivity analysis | Varying landscapes

Introduction | Landmark data | Reading data from xyz files | The EDMA data format | EDMA data dimensions and names | Selecting subsets of EDMA data objects | Coercing EDMA data into other object types | Turning 3D arrays into EDMA data objects | Visual inspection of the data | Spotting data errors | Ordination and clustering | Writing data to xyz format

Publication bias | Correcting for publication bias | Worst-case meta-analysis | Publication bias required to explain away the results | Significance funnel plot | p-hacking | Correction for p-hacking | Diagnostic plots | Multiple biases | Correction for internal bias and/or publication bias | Bias required to explain away the results

Introduction | Estimating the form matrices | Form difference | Global T-test | Local testing | Influential landmarks | Ordination and clustering for specimens | Visualizing landmarks

Introduction | Estimating the growth matrices | Global T-test | Local testing | Influential landmarks | Ordination and clustering for specimens | Visualizing landmarks | Growth difference matrix

Introduction | Nonparametric fit | Form matrix | Visualizing the mean form | Changing the default colors

Introduction | Components of detectability | Data and data processing | Variables | Phylogenetic correlations | Analysis | Variable screening for SR | Variable screening for DD | Mixed model selection | Profile likelihood for lambda | Leave-one-out (LOO) analysis | Parametric bootstrap | Prediction intervals | Results | Table with estimates and MSE | Tree with SR, DD, and trait values | Profile likelihood profiles for lambda | Bootstrap distributions of lambda | LOO cross validation plots | Mapping continuous traits on the tree

Parallel processing | Nestedness and Null models | Scaling in redundancy analysis | Weighted average and linear combination scores