pcd: Phylogenetic Community Dissimilarity
In picante: R tools for integrating phylogenies and ecology

Description Usage Arguments Details Value Note Author(s) References See Also Examples

Pairwise dissimilarity in phylogenetic community composition that is partitioned into a nonphylogenetic and a phylogenetic component.

1	pcd(comm, tree, PSVmncd=NULL, PSVpool=NULL, reps=10^4)

`comm`	Community data matrix
`tree`	Object of class phylo or a phylogenetic covariance matrix
`PSVmncd`	Vector of null mean conditional phylogenetic species variability (PSV) values
`PSVpool`	The standard, unconditional PSV calculated for the species pool
`reps`	The number of random draws from the species pool used to produce `PSVmncd`

Phylogenetic community dissimilarity (PCD) is the pairwise differences between communities derived by asking how much of the variance among species in the values of a hypothetical nonselected trait in one community can be predicted by the known trait values of species in another community. PCD is partitioned into a nonphylogenetic component that reflects shared species between communities (PCDc) and a phylogenetic component that reflects the evolutionary relationships among nonshared species (PCDp). In order to compare communities that vary in species richness, the metric is standardized under the assumption that the species in communities are selected at random from the species pool. The analyses here define the species pool as the list of all species in the set of communities in comm, but the species pool can be defined under any hypothesis of community assembly either by manipulating the code or inputting a user defined PSVmncd and PSVpool.

The function returns a list with items:

`PCD`	A square matrix of PCD values
`PCDc`	A square matrix of PCDc values
`PCDp`	A square matrix of PCDp values
`PSVmncd`	A vector of null mean conditional PSV values used to calculate PCD
`PSVpool`	The unconditional PSV of the species pool used to calculate PCD

The sampling procedure used to standardize PCD and produce PSVmncd and PSVpool can be slow.

Anthony Ives <arives@wisc.edu> and Matthew Helmus <mrhelmus@gmail.com>

Ives A.R. & Helmus M.R. (2010). Phylogenetic metrics of community similarity. The American Naturalist, 176, E128-E142.

psv, phylosor, unifrac

## Not run: 
data(phylocom)
pcd(phylocom$sample, phylocom$phylo)

## End(Not run)

Loading required package: ape
Loading required package: vegan
Loading required package: permute
Loading required package: lattice
This is vegan 2.4-3
Loading required package: nlme
$PCD
           clump1   clump2a   clump2b    clump4      even
clump2a 1.2115647                                        
clump2b 1.1369843 1.1107540                              
clump4  1.6239315 0.9942661 0.9328716                    
even    1.5140665 1.3736529 1.2770356 0.6998496          
random  1.5119775 1.3601456 1.2437288 1.2036341 0.9279553

$PCDc
           clump1   clump2a   clump2b    clump4      even
clump2a 0.7352941                                        
clump2b 0.7352941 0.7352941                              
clump4  1.1029412 0.7352941 0.7352941                    
even    1.1029412 1.1029412 1.1029412 0.7352941          
random  1.1029412 1.1029412 1.1029412 1.1029412 1.1029412

$PCDp
           clump1   clump2a   clump2b    clump4      even
clump2a 1.6477280                                        
clump2b 1.5462987 1.5106254                              
clump4  1.4723646 1.3522019 1.2687054                    
even    1.3727536 1.2454453 1.1578456 0.9517954          
random  1.3708596 1.2331987 1.1276475 1.0912949 0.8413461

$PSVmncd
[1] 0.7477140 0.6818843 0.6195806 0.5690865 0.5167180 0.4749888 0.4338025
[8] 0.3942528

$PSVpool
[1] 0.8233333