Phylogenetic Species Diversity Metrics

Source: R/psv.R

Calculate the bounded phylogenetic biodiversity metrics: phylogenetic species variability, richness, evenness and clustering for one or multiple communities.

psv(
  comm,
  tree,
  compute.var = TRUE,
  scale.vcv = TRUE,
  prune.tree = FALSE,
  cpp = TRUE
)

psr(
  comm,
  tree,
  compute.var = TRUE,
  scale.vcv = TRUE,
  prune.tree = FALSE,
  cpp = TRUE
)

pse(comm, tree, scale.vcv = TRUE, prune.tree = FALSE, cpp = TRUE)

psc(comm, tree, scale.vcv = TRUE, prune.tree = FALSE)

psv.spp(comm, tree, scale.vcv = TRUE, prune.tree = FALSE, cpp = TRUE)

psd(
  comm,
  tree,
  compute.var = TRUE,
  scale.vcv = TRUE,
  prune.tree = FALSE,
  cpp = TRUE
)

Arguments

comm

Community data matrix, site as rows and species as columns, site names as row names.

tree

A phylo tree object with class "phylo" or a phylogenetic covariance matrix.

compute.var

Logical, default is TRUE, computes the expected variances for PSV and PSR for each community.

scale.vcv

Logical, default is TRUE, scale the phylogenetic covariance matrix to bound the metric between 0 and 1 (i.e. correlations).

prune.tree

Logical, default is FALSE, prune the phylogeny before converting to var-cov matrix? Pruning and then converting VS converting then subsetting may have different var-cov matrix resulted.

cpp

Logical, default is TRUE, whether to use cpp for internal calculations.

Value

Returns a dataframe of the respective phylogenetic species diversity metric values

Details

Phylogenetic species variability (PSV) quantifies how phylogenetic relatedness decreases the variance of a hypothetical unselected/neutral trait shared by all species in a community. The expected value of PSV is statistically independent of species richness, is one when all species in a community are unrelated (i.e., a star phylogeny) and approaches zero as species become more related. PSV is directly related to mean phylogenetic distance, except except calculated on a scaled phylogenetic covariance matrix. The expected variance around PSV for any community of a particular species richness can be approximated. To address how individual species contribute to the mean PSV of a data set, the function psv.spp gives signed proportions of the total deviation from the mean PSV that occurs when all species are removed from the data set one at a time. The absolute values of these “species effects” tend to positively correlate with species prevalence.

Note

These metrics are bounded either between zero and one (PSV, PSE, PSC) or zero and species richness (PSR); but the metrics asymptotically approach zero as relatedness increases. Zero can be assigned to communities with less than two species, but conclusions drawn from assigning communities zero values need be carefully explored for any data set. The data sets need not be species-community data sets but may be any community data set with an associated phylogeny.

References

Helmus M.R., Bland T.J., Williams C.K. & Ives A.R. 2007. Phylogenetic measures of biodiversity. American Naturalist, 169, E68-E83

Author

Matthew Helmus mrhelmus@gmail.com

Examples

psv(comm = comm_a, tree = phylotree) 
#>            PSVs SR        vars
#> s3293        NA  1          NA
#> s3294 0.7294797  5 0.002882626
#> s3295 0.7937525  6 0.001787660
#> s3296 0.8998803  4 0.005107335
#> s3297 0.7831887  4 0.005107335
#> s3299 0.7664551  5 0.002882626
#> s3300 0.8085234  6 0.001787660
#> s3301 0.7167665  2 0.033698666
#> s3302 0.6987934  4 0.005107335
#> s3303 0.8083833  2 0.033698666
#> s3304 0.7645509  3 0.010756048
#> s3307 0.8534491  5 0.002882626
#> s3308 0.6796509  5 0.002882626
#> s3309 0.7469461  3 0.010756048
#> s3311 0.7706318  5 0.002882626