rankindex {vegan}R Documentation

Compares Dissimilarity Indices for Gradient Detection


Rank correlations between dissimilarity indices and gradient separation.


rankindex(grad, veg, indices = c("euc", "man", "gow", "bra", "kul"),
          stepacross = FALSE, method = "spearman", ...)


grad The gradient variable or matrix.
veg The community data matrix.
indices Dissimilarity indices compared, partial matches to alternatives in vegdist.
stepacross Use stepacross to find a shorter path dissimilarity. The dissimilarities for site pairs with no shared species are set NA using no.shared so that indices with no fixed upper limit can also be analysed.
method Correlation method used.
... Other parameters to stepacross.


A good dissimilarity index for multidimensional scaling should have a high rank-order similarity with gradient separation. The function compares most indices in vegdist against gradient separation using rank correlation coefficients in cor.test. The gradient separation between each point is assessed as Euclidean distance for continuous variables, and as Gower metric for mixed data using function daisy when grad has factors.


Returns a named vector of rank correlations.


There are several problems in using rank correlation coefficients. Typically there are very many ties when n(n-1)/2 gradient separation values are derived from just n observations. Due to floating point arithmetics, many tied values differ by machine epsilon and are arbitrarily ranked differently by rank used in cor.test. Two indices which are identical with certain transformation or standardization may differ slightly (magnitude 10^{-15}) and this may lead into third or fourth decimal instability in rank correlations. Small differences in rank correlations should not be taken too seriously. Probably this method should be replaced with a sounder method, but I do not yet know which... You may experiment with mantel, anosim or even protest.

Earlier version of this function used method = "kendall", but that is far too slow in large data sets.


Jari Oksanen


Faith, F.P., Minchin, P.R. and Belbin, L. (1987). Compositional dissimilarity as a robust measure of ecological distance. Vegetatio 69, 57-68.

See Also

vegdist, stepacross, no.shared, isoMDS, cor, Machine, and for alternatives anosim, mantel and protest.


## The next scales all environmental variables to unit variance.
## Some would use PCA transformation.
rankindex(scale(varechem), varespec)
rankindex(scale(varechem), wisconsin(varespec))

[Package vegan version 1.16-32 Index]