NMDS is useful when you want to find the best 1D, 2D, 3D (or more, you can choose how many D's) representation of your dataset. In your case, I suggest you just run a PCA on your 5 variables on look at what variables have the strongest loadings on each axis.
-- Etienne Laliberté ================================ School of Forestry University of Canterbury Private Bag 4800 Christchurch 8140, New Zealand Phone: +64 3 366 7001 ext. 8365 Fax: +64 3 364 2124 www.elaliberte.info
