What is picante?

Picante is an R package designed for the analysis of phylogenetic and ecological data. It provides tools for calculating phylogenetic diversity metrics, testing for phylogenetic signal, and performing phylogenetic regressions.

Here's a breakdown of key aspects:

• Phylogenetic Diversity Metrics: Picante offers functions to calculate various measures of how much evolutionary history is represented in a community or dataset. This includes metrics like:

  • Phylogenetic Diversity (PD): The sum of branch lengths on the phylogenetic tree spanning all species in a community.
  • Mean Pairwise Distance (MPD): The average phylogenetic distance between all pairs of species in a community.
  • Mean Nearest Taxon Distance (MNTD): The average phylogenetic distance between each species and its nearest relative in the community.
  • Faith's Phylogenetic Diversity: Another name for Phylogenetic Diversity (PD).
  • Phylogenetic Species Variability (PSV): Measures the amount of trait variation explained by phylogeny.

• Phylogenetic Signal: Picante provides tools to assess whether traits are phylogenetically conserved, meaning that closely related species tend to have more similar trait values than distantly related species. Key functions for this include calculating Blomberg's K and Pagel's lambda.

• Phylogenetic Regression: Picante allows users to perform statistical analyses that account for the non-independence of data points due to shared evolutionary history. This is often done using phylogenetic generalized least squares (PGLS). This helps prevent statistical errors that might arise if related species are treated as independent data points.

• Data Input: Picante requires a phylogenetic tree (usually in the phylo format from the ape package) and a community data matrix (species abundances or presences/absences). It can also work with trait data associated with the species.

• Applications: Picante is widely used in ecology, evolutionary biology, and conservation biology to understand the relationships between species, their traits, and their environment. It helps researchers investigate questions about community assembly, niche conservatism, and the impact of biodiversity loss.