FD-package | R Documentation |

FD is a package to compute different multidimensional functional diversity (FD) indices. It implements a distance-based framework to measure FD that allows any number and type of functional traits, and can also consider species relative abundances. It also contains other tools for functional ecologists (e.g. `maxent`

).

Package: | FD |

Type: | Package |

Version: | 1.0-12 |

Date: | 2014-08-19 |

License: | GPL-2 |

LazyLoad: | yes |

LazyData: | yes |

FD computes different multidimensional FD indices. To compute FD indices, a species-by-trait(s) matrix is required (or at least a species-by-species distance matrix). `gowdis`

computes the Gower dissimilarity from different trait types (continuous, ordinal, nominal, or binary), and tolerates `NA`

s. It can treat ordinal variables as described by Podani (1999), and can handle asymetric binary variables and variable weights. `gowdis`

is called by `dbFD`

, the main function of FD.

`dbFD`

uses principal coordinates analysis (PCoA) to return PCoA axes, which are then used as ‘traits’ to compute FD. `dbFD`

computes several multidimensional FD indices, including the three indices of Villéger et al. (2008): functional richness (FRic), functional evenness (FEve), and functional divergence (FDiv). It also computes functional dispersion (FDis) (Laliberté and Legendre 2010), Rao's quadratic entropy (Q) (Botta-Dukát 2005), a posteriori functional group richness (FGR), and the community-level weighted means of trait values (CWM), an index of functional composition. Some of these indices can be weighted by species abundances. `dbFD`

includes several options for flexibility.

Etienne Laliberté, Pierre Legendre and Bill Shipley

Maintainer: Etienne Laliberté <etiennelaliberte@gmail.com> https://www.elaliberte.info/

Botta-Dukát, Z. (2005) Rao's quadratic entropy as a measure of functional diversity based on multiple traits. *Journal of Vegetation Science* **16**:533-540.

Laliberté, E. and P. Legendre (2010) A distance-based framework for measuring functional diversity from multiple traits. *Ecology* **91**:299-305.

Podani, J. (1999) Extending Gower's general coefficient of similarity to ordinal characters. *Taxon* **48**:331-340.

Villéger, S., N. W. H. Mason and D. Mouillot (2008) New multidimensional functional diversity indices for a multifaceted framework in functional ecology. *Ecology* **89**:2290-2301.

# examples with a dummy dataset ex1 <- gowdis(dummy$trait) ex1 ex2 <- functcomp(dummy$trait, dummy$abun) ex2 ex3 <- dbFD(dummy$trait, dummy$abun) ex3 # examples with real data from New Zealand short-tussock grasslands # these examples may take a few seconds to a few minutes each to run ex4 <- gowdis(tussock$trait) ex5 <- functcomp(tussock$trait, tussock$abun) # 'lingoes' correction used because 'sqrt' does not work in that case ex6 <- dbFD(tussock$trait, tussock$abun, corr = "lingoes") ## Not run: # ward clustering to compute FGR, cailliez correction ex7 <- dbFD(tussock$trait, tussock$abun, corr = "cailliez", calc.FGR = TRUE, clust.type = "ward") # choose 'g' for number of groups # 6 groups seems to make good ecological sense ex7 # however, calinksi criterion in 'kmeans' suggests # that 6 groups may not be optimal ex8 <- dbFD(tussock$trait, tussock$abun, corr = "cailliez", calc.FGR = TRUE, clust.type = "kmeans", km.sup.gr = 10) ## End(Not run)

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