Spatiophylogenetic modelling of extinction risk reveals evolutionary distinctiveness and brief flowering period as risk factors in a diverse hotspot plant genus

Abstract

Comparative models used to predict species threat status often combine variables measured at the species level with spatial variables, causing multiple statistical challenges, including phylogenetic and spatial non-independence. We present a novel bayesian approach for modelling threat status that simultaneously deals with both forms of non-independence and estimates their relative contribution, and we apply the approach to modelling threat status in the Australian plant genus Hakea. We find that after phylogenetic and spatial effects are accounted for, species with greater evolutionary distinctiveness and a shorter annual flowering period are more likely to be threatened. The model allows us to combine information on evolutionary history, species biology, and spatial data, to calculate latent extinction risk (potential for non-threatened species to become threatened), and estimate the most important drivers of risk for individual species. This could be of value for proactive conservation decision-making that targets species of concern before they become threatened.