Predicting predator-prey interactions in terrestrial endotherms using random forest
J. Llewelyn, G. Strona, C. R. Dickman, A. Greenville, G. Wardle, M. S. Y. Lee, S. Doherty, F. Shabani, F. Saltre, C. J. A. Bradshaw
This study uses random forest to predict predator-prey interactions in birds and mammals using ecomorphological and phylogenetic traits, achieving up to 88% accuracy in global data and 67% in a specific community.
bioRxiv · Sep 2, 2022Ecology