FD::dbFD() is probably the most known function to compute functional diversity indices. It comes from the
FD package proposed by Laliberté, Legendre, and Shipley (2014). It can compute many indices: functional richness, Rao’s quadratic entropy, community-weighted mean, functional divergence, functional dispersion, and functional group richness. This swiss-army knife of functional diversity indices has many options and compute several indices in a single run.
hillR::hill_func() comes from the
hillR package that computes Hill numbers for taxonomic, functional, and functional diversity (Li 2018). It implements indices proposed by Chao, Chiu, and Jost (2014). It computes Rao’s quadratic entropy, the mean functional diversity per species, as well as the total functional diversity.
adiv::QE() comes from the
adiv package which proposes a toolkit to analyze biodiversity (Pavoine 2020). This function computes Rao’s quadratic entropy.
SYNCSA::rao.diversity() comes from
SYNCSA package which proposes a simulation framework for meta-communities (Debastiani and Pillar 2012). The function computes Rao’s quadratic entropy as well as functional redundancy.
mFD::alpha.fd.hill() comes from the
mFD package which offers a coherent framework to work with functional spaces and perform quality checks, diagnostic plots, as well as computing many functional diversity indices.