rankindex.new {asbio} | R Documentation |
This function is a wrapper for rankindex
from vegan
.
rankindex.new(grad, veg, indices = c("matching", "rogers", "jaccard.pa", "sorenson", "kulkczynski.pa", "ochiai", "gower", "steinhaus", "kulkczynski.q", "jaccard.q", "euclidean", "rel.euclidean", "manhattan", "czekanowski", "whittaker", "canberra", "chi.metric", "chi.dist", "morisita", "morisita.horn", "minkowski", "mountford", "raup.crick", "binomial", "chao"), stepacross = FALSE, method = "pearson", ...)
grad |
An s x e matrix of environmental variables, where s = the number of sites and e = the number of environmental variables. |
veg |
An s x p community matrix, where s = the number of sites and p = the number of species. |
indices |
Some subset from the character string: c("matching", "rogers",
"jaccard.pa", "sorenson", "kulkczynski.pa", "ochiai", "gower", "steinhaus",
"kulkczynski.q", "jaccard.q", "euclidean", "rel.euclidean", "manhattan",
"czekanowski", "whittaker", "canberra", "chi.metric", "chi.dist", "morisita",
"morisita.horn", "minkowski", "mountford", "raup.crick", "binomial", "chao") . |
stepacross |
Logical, specifies whether a step across transformation should be applied to the resemblance matrix. |
method |
What method is used to calculate correlations between
environmental and communtiy matrices. Must be one of "pearson", "kendall" , or "spearman" . |
... |
Other parameters to stepacross from vegan . |
A number of ecologists have evaluated the performance of distance measures by
comparing environmental distance (i.e. differences along gradients) to distance
in ordination space (Beals, 1984; Faith et al., 1987; De'ath, 1999). If species
distributions are well described by environmental variables, then a strong
association should exist between distances in species space and differences in
environmental space. Thus, poor correlations represent poor performance by the
distance measure. Obviously this analysis becomes more meaningful as the number
of important environmental variables increases in ones measure of environmental distance.
The library vegan
has a function called rankindex which ranks dissimilarity or
distances used for finding community distances or dissimilarities by how well
these indices agree with gradient differences. The gradient separation between
each point is expressed as Euclidean distance for continuous variables and as
Gower's metric for mixed data (i.e. when at least some environmental variables
are categorical or ordinal). In the later case the library cluster is required.
The association of community and environmental distance matrices is simply the
correlation of the community and environmental distance ranks and can be
measured with any of the conventional measures described in Ch. 11. The
function rankindex.new
is a wrapper for rankindex
and uses Oksanen's
method to compare the efficacy of 25 of the 26 indices generated by get.dist
.
Mahalanobis distance is left out, since it does not create a distance matrix
per se, but a simultaneous comparison of each site to all other sites.
The function returns a table of ranked Pearson's correlations (default) and a barplot.
Ken Aho
Oksanen, J., Kindt, R., Legendre, P., O'Hara, B., Simpson, G. L., and Stevens, M. H. H. (2008) vegan: community ecology package. R package version 1.13-0. http://vegan.r-forge.r-project.org/
library(vegan) data(varechem) data(varespec) r<-rankindex.new(scale(varechem),varespec)