Investigating the Effect of Spatial Distribution and Spatiotemporal Information on Speciation using Individual-Based Ecosystem Simulation

Abstract

In this paper, we investigate the impact of species’ spatial and spatiotemporal distribution information on speciation, 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 of the imbalanced nature of our dataset we use smote algorithm to make a relatively balanced dataset to avoid dismissing the minor class samples. Experimental results show very good predictions for the test set generated from the same run as the learning set. It also shows good results on test sets generated from different runs of Ecosim. We also observe superior results when we use, for the learning set, a run with more species compare to a run with less species. Finally we can conclude that spatial and spatiotemporal information are very effective in predicting speciation.