Automated assessment reveals extinction risk of reptiles is widely underestimated across space and phylogeny
G. H. de Oliveira Caetano, D. G. Chapple, R. Grenyer, T. Raz, J. Rosenblatt, R. Tingley, M. Böhm, S. Meiri, U. Roll
This paper presents an automated machine learning method to assess extinction risk for unassessed reptiles, finding that unassessed species are more likely to be threatened and that assessor bias affects outcomes.
bioRxiv · Jan 19, 2022 · PreprintEcology