NMDS with metaMDS from vegan following an example from Numerical Ecology with R

Dear list members,

I am working on an NMDS using metaMDS from vegan with the Doubs fish data
from the book Numerical ecology with R.

especies <- read.csv("DoubsSpe.csv", row.names = 1)
e.mds = metaMDS(especies, distance = "bray")

Run 0 stress 0.003706943
Run 1 stress 0.0004788424
... New best solution
... procrustes: rmse 0.009197047  max resid 0.01874812
Run 2 stress 0.0004600702
... New best solution
... procrustes: rmse 0.0002883791  max resid 0.0005590752
*** Solution reached

Mensajes de aviso perdidos
In distfun(comm, method = distance, ...) :
 you have empty rows: their dissimilarities may be meaningless in method
?bray?

My results are "strange" (stress is too low and different to the one on the
book) and the plot is very different to the one that appears in the book.

Manuel,

I'm too lazy to go to have a look at the book now (I'm sitting in my balcony sipping my morning coffee), but I assume that the difference is that metaMDS in your book was still based on MASS::isoMDS(), but the current vegan (from 2.0-0) uses its own monoMDS() function as a default. One difference is that isoMDS() expresses the stress per cent, and monoMDS() as parts of one, so that equal isoMDS() is 100x higher. Another difference is that monoMDS() implements treatment of tied dissimilarity values, and defaults to "weak" ties so that equal observed dissimilarities can be allowed to be at different ordination distances. If I remember correctly, these Doubs fish data are very simple so that monoMDS() really may be able to have nearly zero stress (which is suspect in general). 

For better correspondence to the book, you may first try setting 'weakties = FALSE' which will force tie treatment that is closer to isoMDS(), but still not identical. For true replication of the book results you should set 'engine = "isoMDS"'.

As usual, these are documented features.

Cheers, Jari Oksanen

Jari Oksanen, Dept Biology, Univ Oulu, 90014 Finland
jari.oksanen at oulu.fi, Ph. +358 400 408593, http://cc.oulu.fi/~jarioksa