Machine learning improves global models of plant diversity
L. Cai, H. Kreft, A. Taylor, P. Denelle, J. Schrader, F. Essl, M. v. Kleunen, J. Pergl, P. Pysek, A. Stein, M. Winter, J. F. Barcelona, N. Fuentes, I. Inderjit, D. N. Karger, , P. Weigelt
The paper uses machine learning and statistical models to predict global plant diversity patterns based on environmental data, achieving high accuracy for species and phylogenetic richness.
bioRxiv · Apr 8, 2022Ecology