shape(data, metric = c("all-quick", "all", "psv", "psr", "mpd", "mntd", "pd",
"colless", "gamma", "taxon", "eigen.sum", "eed", "hed", "dist.fd"),
sqrt.phy = FALSE, traitgram = NULL, traitgram.p = 2, ext.dist = NULL,
which.eigen = 1, remove.errors = TRUE, ...)
comparative.comm
objectall-quick
)
calculates everything bar fd.dist
, all
calculates
everything. Individually call-able metrics are: psv
,
psr
, mpd
, mntd
, eigen.sum
)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
fun
traitgram
when calling funct.phylo.dist
.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).PSV,PSR
Helmus M.R., Bland T.J., Williams C.K. & Ives A.R. (2007). Phylogenetic measures of biodiversity. American Naturalist, 169, E68-E83.
PD
Faith D.P. (1992). Conservation evaluation and phylogenetic diversity. Biological Conservation, 61, 1-10.
colless
Colless D.H. (1982). Review of phylogenetics: the theory and practice of phylogenetic systematics. Systematic Zoology, 31, 100-104.
gamma
Pybus O.G. & Harvey P.H. (2000) Testing macro-evolutionary models using incomplete molecular phylogenies. _Proceedings of the Royal Society of London. Series B. Biological Sciences 267: 2267--2272.
taxon
Clarke K.R. & Warwick R.M. (1998). A taxonomic distinctness index and its statistical properties. J. Appl. Ecol., 35, 523-531.
eigen.sum
Diniz-Filho J.A.F., Cianciaruso M.V., Rangel T.F. & Bini L.M. (2011). Eigenvector estimation of phylogenetic and functional diversity. Functional Ecology, 25, 735-744.
eed,hed
(i.e., Eed, Hed) 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.
evenness
dispersion
dissimilarity
data(laja)
data <- comparative.comm(invert.tree, river.sites, invert.traits)
(output<-shape(data))
str(output)
shape(data, "colless")
shape(data, "eigen.sum", which.eigen=2)
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