title: Historical drivers of extinction risk: using past evidence to direct future monitoring.
abstract: Global commitments to halt biodiversity decline mean that it is essential to monitor species' extinction risk. However, the work required to assess extinction risk is intensive. We demonstrate an alternative approach to monitoring extinction risk, based on the response of species to external conditions. Using retrospective International Union for Conservation of Nature Red List assessments, we classify transitions in the extinction risk of 497 mammalian carnivores and ungulates between 1975 and 2013. Species that moved to lower Red List categories, or remained Least Concern, were classified as 'lower risk'; species that stayed in a threatened category, or moved to a higher category of risk, were classified as 'higher risk'. Twenty-four predictor variables were used to predict transitions, including intrinsic traits (species biology) and external conditions (human pressure, distribution state and conservation interventions). The model correctly classified up to 90% of all transitions and revealed complex interactions between variables, such as protected areas (PAs) versus human impact. The most important predictors were: past extinction risk, PA extent, geographical range size, body size, taxonomic family and human impact. Our results suggest that monitoring a targeted set of metrics would efficiently identify species facing a higher risk, and could guide the allocation of resources between monitoring species' extinction risk and monitoring external conditions.
authors.affiliation: Global Mammal Assessment Program, Department of Biology and Biotechnologies, Sapienza Università di Roma, Viale dell' Università 32, Rome 00185, Italy ARC Centre of Excellence for Environmental Decisions, Centre for Biodiversity and Conservation Science, University of Queensland, Brisbane, Queensland 4072, Australia School of Geography, Planning and Environmental Management, University of Queensland, Brisbane, Queensland 4072, Australia moreno.dimarco@gmail.com.
authors.forename: Moreno
authors.initials: M
authors.lastname: Di Marco
authors.affiliation: Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, UK.
authors.forename: Ben
authors.initials: B
authors.lastname: Collen
authors.affiliation: Global Mammal Assessment Program, Department of Biology and Biotechnologies, Sapienza Università di Roma, Viale dell' Università 32, Rome 00185, Italy.
authors.forename: Carlo
authors.initials: C
authors.lastname: Rondinini
authors.affiliation: Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, UK.
authors.forename: Georgina M
authors.initials: GM
authors.lastname: Mace
mesh_terms: D000818:Animals; D044822:Biodiversity; D003247:Conservation of Natural Resources / Q000379:methods*; D056727:Endangered Species; D053476:Extinction, Biological; D008322:Mammals / Q000502:physiology*; D008954:Models, Biological; D018570:Risk Assessment / Q000379:methods
keywords: biodiversity; conservation; human threats; mammals; random forest model