We analysed each paper according to (i) year of publication, (ii) journal of publication and impact factor of each journal, (iii) number of citations, (iv) first author's country, (v) region covered by the study, (vi) type of species-occurrence records (presence-only, or presence and absence), (vii) biological groups (algae, amphibians, birds, fish, fungi, insects, mammals, other invertebrates, plants, and reptiles), (viii) type of predictor variables (aquatic, climatic, human, land cover, land use, soil properties, topographic, and vegetation), (ix) spatial scale of the study (global, continental, national, regional, and local), (x) environment covered by the study (aquatic or terrestrial), and (xi) methods used to generate the models in each study.
Plants and insects were the biological groups most often used for predict the distribution of invasive species.
Each biological group has been studied differently, mainly due to fact that sampling and collecting methods differ, and that the determination of species in some groups, like fungi and prokaryotes, is difficult (Stiling, 1994).
Regression analysis was also used to evaluate the proportion of articles through time devoted to each of the major biological groups (plants, invertebrates, and vertebrates), the proportion of studies done in each geographical region, and the proportion of contributions from authors working in the USA and from authors working in other countries.
The result of Discriminant Analysis significantly distinguished the biological groups from the oceanic hillside (Wilks' lambda = 0.
The relative air humidity, the litter depth, the atmospheric temperature and soil temperature determined the biological groups found on both hillsides.
The luminosity and the canopy closure also determined the biological groups found on the continental hillside.