U. Roll

Automated assessment reveals extinction risk of reptiles is widely underestimated across space and phylogeny

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.

Global priorities for conservation of reptilian phylogenetic diversity in the face of human impacts

The paper develops metrics combining phylogenetic diversity and human impact for reptile conservation, finding high human impact areas coincide with high reptilian diversity and identifying data-deficient species as high priority.