R: Functional Diversity and Community Distances from Species...

treedive {vegan} | R Documentation

## Functional Diversity and Community Distances from Species Trees

### Description

Functional diversity is defined as the total branch length in a trait dendrogram connecting all species, but excluding the unnecessary root segments of the tree (Petchey and Gaston 2006). Tree distance is the increase in total branch length when combining two sites.

### Usage

    treedive(comm, tree, match.force = TRUE, verbose = TRUE)
    treeheight(tree)
    treedist(x, tree, relative = TRUE, match.force = TRUE, ...)

### Arguments

`comm, x` | Community data frame or matrix.
`tree` | A dendrogram which for `treedive` must be for species (columns).
`match.force` | Force matching of column names in data (`comm`, `x`) and labels in `tree`. If `FALSE`, matching only happens when dimensions differ (with a warning or message). The order of data must match to the order in `tree` if matching by names is not done.
`verbose` | Print diagnostic messages and warnings.
`relative` | Use distances relative to the height of combined tree.
`...` | Other arguments passed to functions (ignored).

### Details

Function `treeheight` finds the sum of lengths of connecting segments in a dendrogram produced by `hclust`, or other dendrogram that can be coerced to a correct type using `as.hclust`. When applied to a clustering of species traits, this is a measure of functional diversity (Petchey and Gaston 2002, 2006), and when applied to phylogenetic trees this is phylogenetic diversity.

Function `treedive` finds the `treeheight` for each site (row) of a community matrix. The function uses a subset of dendrogram for those species that occur in each site, and excludes the tree root if that is not needed to connect the species (Petchey and Gaston 2006). The subset of the dendrogram is found by first calculating `cophenetic` distances from the input dendrogram, then reconstructing the dendrogram for the subset of the cophenetic distance matrix for species occurring in each site. Diversity is 0 for one species, and `NA` for empty communities.

Function `treedist` finds the dissimilarities among trees. Pairwise dissimilarity of two trees is found by combining species in a common tree and seeing how much of the tree height is shared and how much is unique. With `relative = FALSE` the dissimilarity is defined as 2AB - A - B, where A and B are heights of component trees and AB is the height of the combined tree. With `relative = TRUE` the dissimilarity is (2AB - A - B)/(AB). Although the latter formula is similar to Jaccard dissimilarity (see `vegdist`, `designdist`), it is not in the range 0 … 1, since combined tree can add a new root. When two zero-height trees are combined into a tree of above zero height, the relative index attains its maximum value 2. The dissimilarity is zero from a combined zero-height tree.

The functions need a dendrogram of species traits or phylogenies as an input. If species traits contain `factor` or `ordered` factor variables, it is recommended to use Gower distances for mixed data (function `daisy` in package cluster), and usually the recommended clustering method is UPGMA (`method = "average"` in function `hclust`) (Podani and Schmera 2006). Phylogenetic trees can be changed into dendrograms using `as.hclust.phylo` (package ape)

It is possible to analyse the non-randomness of tree diversity using `oecosimu`. This needs specifying an adequate Null model, and the results will change with this choice.

### Value

A vector of diversity values or a single tree height, or a dissimilarity structure that inherits from `dist` and can be used similarly.

### Author(s)

Jari Oksanen

### References

Lozupone, C. and Knight, R. 2005. UniFrac: a new phylogenetic method for comparing microbial communities. Applied and Environmental Microbiology 71, 8228–8235.

Petchey, O.L. and Gaston, K.J. 2002. Functional diversity (FD), species richness and community composition. Ecology Letters 5, 402–411.

Petchey, O.L. and Gaston, K.J. 2006. Functional diversity: back to basics and looking forward. Ecology Letters 9, 741–758.

Podani J. and Schmera, D. 2006. On dendrogram-based methods of functional diversity. Oikos 115, 179–185.

### See Also

Function `treedive` is similar to the phylogenetic diversity function `pd` in picante, but excludes tree root if that is not needed to connect species. Function `treedist` is similar to the phylogenetic similarity `phylosor` in picante, but excludes unneeded tree root and returns distances instead of similarities.

`taxondive` is something very similar from another world.

### Examples

    ## There is no data set on species properties yet, and we demonstrate
    ## the methods using phylogenetic trees
    data(dune)
    data(dune.phylodis)
    cl <- hclust(dune.phylodis)
    treedive(dune, cl)
    ## Significance test using Null model communities.
    ## The current choice fixes numbers of species and picks species
    ## proportionally to their overall frequency
    oecosimu(dune, treedive, "r1", tree = cl, verbose = FALSE)
    ## Phylogenetically ordered community table
    dtree <- treedist(dune, cl)
    tabasco(dune, hclust(dtree), cl)
    ## Use tree distances  in capscale
    capscale(dtree ~ 1, comm=dune)

[Package vegan version 2.4-3 Index]