Introduction | Setup | Journal fairness | Article fairness | Citation ratio | Author ratio | References

Package content | Package metadata | DESCRIPTION | README | Recommended workflow | Resources

Prerequisites | GIT configuration | Creating a GitHub repo | Managing credentials | Usage | Resources | Contributing | Colophon

Compendium content | Compendium metadata | DESCRIPTION | README | Recommendations | Advanced features | Using renv | Using docker

About this tutorial | Overview of the functional framework | 1. Know your data | 1.1. What types of traits am I using? | 1.2. Summarize my traits | 1.3. Summarize my assemblages | 2. Gathering species into functional entities | 3. Computing distances between species based on functional traits | 4. Computing functional spaces & their quality | 4.1. Compute multimensional functional spaces and assess their quality | 4.2. Illustrating the quality of the selected functional spaces | 5. Test correlation between functional axes and traits | 6. Plot functional space | 7. Compute functional diversity indices & plot them | 7.1. Functional alpha diversity indices in a multidimensional space | 7.2. Functional beta diversity indices based on multidimensional space | References

About this tutorial | 1. Load dataset | 2. Compute the functional space | 3. Plot functional space, compute and illustrate indices | References

About this FAQ | Functional traits | What is the difference between nominal and ordinal traits? | How should I handle my data if it shows correlated traits? | Intraspecific variation in traits | My species*traits data contains NA, what should I do? | PCoA and negative eigenvalues | Functional space | Overlaying traits as vectors in the functional space | Cumulative variance explained by PCoA axes | Choosing the number of functional axes | Functional Entities vs Species frameworks | How should I choose between working with Functional Entities or Species? | Which indices can I compute with the Functional Entities framework and how? | Functional indices | Access functional specialisation and originality per species | Fuzzy traits and alpha diversity | Fuzzy traits and Weights | High beta diversity in functional space & low beta diversity using Hill numbers | Beta FD Hill and pairs of sites | What does "functionally equally dstinct species" mean? | Null values of Beta FD Hill | How to plot species detected in both assemblages with a third color?

Count formats | Conversion functions | compute_abundances() | compute_concentrations() | compute_frequencies()

Setup | Spatial visualization | Creating a world map | Mapping FORCIS data | Temporal visualization | Plot data by year of sampling | Plot data by month of sampling | Plot data by season | Vertical visualization | Plot data by depth of sampling

Installation | Download FORCIS database | Import FORCIS data | Select a FORCIS taxonomy | Use case 1: Exploration | Use case 2: Specific question | Find the species name | Species filter | Temporal filter | Spatial filter | Distribution map | To go further | References

Setup | Selecting columns | Select a taxonomy | Select required columns | Filtering rows | Filter by month of data collection | Filter by year of data collection | Filter by bounding box | Filter by ocean | Filter by spatial polygon | Filter by species | Reshaping | Convert to long format

Site identifier | Profile identifier | Cast identifier | Sample identifier | Subsample identifier

Using the latest version | Using a specific version

Network properties | Neighbors detection | Workflow | Node labels | Edge list | Connectivity matrix | Extending chessboard | with sf | with ggplot2 | with igraph | Plot the network w/ igraph ----

Pawn | Fool | Rook | Bishop | Knight | Queen | Wizard | Custom moves | References

Visualizing chessboard | gg_chessboard | geom_node | geom_neighbors | geom_edges | Plotting matrices | Mapping edges

Statistical method | Field method | Count conversion | Relative rate of increase | Checking data | Formatting data | Fitting trend | References

Setup | Datasets | Compute distances

1. Why Functional Entities (FEs)? | 2. Tutorial's data | 3. Gather species into FEs | 4. Compute alpha and beta functional indices | 5. Plot functional indices based on FEs | References

About this tutorial | Load data | Plotting more than two assemblages | Basic workflow before plotting | Plotting functional convex-hulls for more than two assemblages for one pair of axis | a - Background | b - Add the global convex-hull | c - Add the convex-hulls and species of the wanted assemblages | Plotting functional convex-hulls for more than two assemblages for several pair of axis | Gathering plots together using the patchwork package | Plotting species differently according to one trait value (coming soon...)

Usage

Compute Distinctiveness from Global Pool - distinctiveness_global() | Compute functional rarity indices across combinations of traits | Compare Distinctiveness computed on all traits and each trait - distinctiveness_dimensions() | Compare Uniqueness computed on all traits and each trait - uniqueness_dimensions() | Compute Relative Abundances - make_relative()

Introduction | Framework | Dataset example | Functional rarity indices | Inputs of functions | Indices | Distance matrix computation | Functional Distinctiveness computation | Formula | Computation with site-species matrix | Computation with stacked data.frame | Scarcity | Computation | Uniqueness | Geographical Restrictedness | funrar | Plots | References

Sparse Matrices Usefulness | Benchmark | Systematic benchmark

Presence-Absence | Theoretical definition | Implementation | Using real data | Considering Abundance | Definitive formula | Reconciling with presence-absence definition

About this tutorial | 1. Tutorial's data | 2. Compute trait-based distance between species | 3. Compute functional space, quality metrics and plot them | 3.1. Compute functional spaces and associated quality metrics | 3.2. Focus on dendrograms | 3.3. Focus on the effect of square-rooting distance matrix before computing PcoA | References

Calculating rmax | Building conversion table | Categorizing species | References

About this tutorial | What is this tutorial about? | Let's load data and compute functional distance | Generalisation of Hill numbers for alpha functional diversity | Generalisation of Hill numbers for beta functional diversity | References

Overview | Managing WDPA API Token | Getting Countries Information | Downloading Protected Areas