As described in Pearse et al. (2014), an evenness metric is one the examines the phylogenetic structure of species present in each assemblage, taking into account their abundances. For completeness, options are provided to calculate these metrics using species traits.
pez.evenness(
data,
sqrt.phy = FALSE,
traitgram = NULL,
traitgram.p = 2,
ext.dist = NULL,
quick = TRUE,
q = 1
)
phy.structure
list object of metric values. Use
coefs
to extract a summary metric table, or examine each
individual metric (which gives more details for each) by calling
print
on the output (i.e., type output
in the example
below).
comparative.comm
object
If TRUE (default is FALSE) your phylogenetic distance matrix will be square-rooted; specifying TRUE will force the square-root transformation on phylogenetic distance matrices (in the spirit of Leitten and Cornwell, 2014). See `details' for details about different metric calculations when a distance matrix is used.
If not NULL (default), a number to be passed to
funct.phylo.dist
(phyloWeight
; the `a' parameter),
causing analysis on a distance matrix reflecting both traits and
phylogeny (0-->only phylogeny, 1--> only traits; see
funct.phylo.dist
). If a vector of numbers is given,
pez.eveness
iterates across them and returns a
data.frame
with coefficients from each iteration. See
`details' for details about different metric calculations when a
distance matrix is used.
A value for `p' to be used in conjunction with
traitgram
when calling funct.phylo.dist
.
Supply an external species-level distance matrix for use in calculations. See `details' for comments on the use of distance matrices in different metric calculations.
Only calculate metrics which are quick to calculate
(default: TRUE); setting to FALSE will also calculate
fd.dist
and the Pagel transformations (lambda, delta,
kappa).
value for q in scheiner
(default 1)
M.R. Helmus, Will Pearse
Most of these metrics do not involve comparison with some kind of
evolutionary-derived expectation for phylogenetic shape. Those that
do, however, such as PSE, make no sense unless applied to a
phylogenetic distance matrix - their null expectation *requires*
it. Using square-rooted distance matrices, or distance matrices
that incorporate trait information, can be an excellent thing to
do, but (for the above reasons), pez
won't give you an
answer for metrics for which WDP thinks it makes no
sense. pae
, iac
, haead
& eaed
can
(...up to you whether you should!...) be used with a square-rooted
distance matrix, but the results *will always be wrong* if you do
not have an ultrametric tree (branch lengths proportional to time)
and you will be warned about this. WDP strongly feels you should
only be using ultrametric phylogenies in any case, but code to fix
this bug is welcome.
Pearse W.D., Purvis A., Cavender-Bares J. & Helmus M.R. (2014). Metrics and Models of Community Phylogenetics. In: Modern Phylogenetic Comparative Methods and Their Application in Evolutionary Biology. Springer Berlin Heidelberg, pp. 451-464.
pse
Helmus M.R., Bland T.J., Williams C.K. &
Ives A.R. (2007). Phylogenetic measures of biodiversity. American
Naturalist, 169, E68-E83.
Pearse W.D., Purvis A., Cavender-Bares J. & Helmus M.R. (2014). Metrics and Models of Community Phylogenetics. In: Modern Phylogenetic Comparative Methods and Their Application in Evolutionary Biology. Springer Berlin Heidelberg, pp. 451-464.
pse
Helmus M.R., Bland T.J., Williams C.K. &
Ives A.R. (2007). Phylogenetic measures of biodiversity. American
Naturalist, 169, E68-E83.
rao
Webb C.O. (2000). Exploring the phylogenetic
structure of ecological communities: An example for rain forest
trees. American Naturalist, 156, 145-155.
taxon
Clarke K.R. & Warwick R.M. (1998). A
taxonomic distinctness index and its statistical
properties. J. Appl. Ecol., 35, 523-531.
entropy
Allen B., Kon M. & Bar-Yam Y. (2009). A
New Phylogenetic Diversity Measure Generalizing the Shannon Index
and Its Application to Phyllostomid Bats. The American Naturalist,
174, 236-243.
pae,iac,haed,eaed
Cadotte M.W., Davies T.J.,
Regetz J., Kembel S.W., Cleland E. & Oakley
T.H. (2010). Phylogenetic diversity metrics for ecological
communities: integrating species richness, abundance and
evolutionary history. Ecology Letters, 13, 96-105.
lambda,delta,kappa
Mark Pagel (1999) Inferring
the historical patterns of biological evolution. Nature 6756(401):
877--884.
innd,mipd
Ness J.H., Rollinson E.J. & Whitney
K.D. (2011). Phylogenetic distance can predict susceptibility to
attack by natural enemies. Oikos, 120, 1327-1334.
scheiner
Scheiner, S.M. (20120). A metric of
biodiversity that integrates abundance, phylogeny, and function.
Oikos, 121, 1191-1202.
pez.shape pez.dispersion pez.dissimilarity
data(laja)
data <- comparative.comm(invert.tree, river.sites, invert.traits)
pez.evenness(data)
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