Dear R and vegan package users, I have been experiencing problems with the metaMDS function when working on a dataset (euk) consisting of 9 "sites" (RNA extracts of 9 biofilms samples) and 340 "species" (microbial taxa based on rRNA sequences). The problem is that I get nMDS ordinations with overlapping points, so that it looks like 6 samples are identical, while the remaining 3 are well separated. The dataset is rather large, and quite complex so I do not think that this is a correct representation of dissimilarities. Every time this happens, I get the warning message:
"In metaMDS(t(euk_red), distance = "bray") : Stress is (nearly) zero - you may have insufficient data" Removing relatively rare species using: euk_red<-euk[rowSums(euk)>100,] results in an nMDS ordination with scattered points that looks more reasonable. However, removing even more rare species (<1000) results in a different, but similarly uncomplex ordination and the same warning message. Changing the distance metric to euclidean seems even more sensitive to this problem, yielding uncomplex ordinations with almost any rare species cutoff. The code I am using is: euk_MDS<-metaMDS(t(euk_red), distance="bray") ordiplot(euk_MDS, display="sites") I have tried the arguments engine=isoMDS, and changing maxit and trymax without noticeable effect. Generating the distance matrices separately in vegdist yields distance matrices that look normal to my eye. It seems like a similar problem to a recent thread in the R-help (Fabian Boetzl, Feb 2014), but my dataset has many species that are shared between all sites. I would be happy to provide the dataset if this may help in figuring out what the problem is. I am using R version 3.1.0 for MacOS, coupled to R-studio (version 0.98.510). Thanks in advance and best regards! Mia M. Bengtsson, University of Vienna [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.