The results of PCA showed that it is not possible to highlight one single factor (i.e. axis) mainly affecting data ordination, because 20% of data variability is distributed along the first axis of the space outlined by the principal components, while 18% and 14% is distributed along the second and third axes respectively, i.e., only half of the entire variability is explained by means of the three most meaningful principal components. Moreover, the sample sites were drawn close together and mainly around the axes’ origin, which is a probable symptom of the lack of preponderance among the several factors affecting species distribution.