In this paper, we investigate the impact of species’spatial and spatiotemporal distribution information onspeciation, using an individual-based ecosystem simulation(Ecosim). For this purpose, using machine learning techniques,we try to predict if one species will split in near future. Because ofthe imbalanced nature of our dataset we use smote algorithm tomake a relatively balanced dataset to avoid dismissing the minorclass samples. Experimental results show very good predictionsfor the test set generated from the same run as the learning set. Italso shows good results on test sets generated from different runsof Ecosim. We also observe superior results when we use, for thelearning set, a run with more species compare to a run with lessspecies. Finally we can conclude that spatial and spatiotemporalinformation are very effective in predicting speciation
