Climate change is likely to become an increasingly major obstacle to slowing the rate of species extinctions. Several new assessment approaches have been proposed for identifying climate-vulnerable species, based on the assumption that established systems such as the IUCN Red List need revising or replacing because they were not developed to explicitly consider climate change. However, no assessment approach has been tested to determine its ability to provide advanced warning time for conservation action for species that might go extinct due to climate change. To test the performance of the Red List system in this capacity, we used linked niche-demographic models with habitat dynamics driven by a 'business-as-usual' climate change scenario. We generated replicate 100-year trajectories for range-restricted reptiles and amphibians endemic to the United States. For each replicate, we categorized the simulated species according to IUCN Red List criteria at annual, 5-year, and 10-year intervals (the latter representing current practice). For replicates that went extinct, we calculated warning time as the number of years the simulated species was continuously listed in a threatened category prior to extinction. To simulate data limitations, we repeated the analysis using a single criterion at a time (disregarding other listing criteria). Results show that when all criteria can be used, the Red List system would provide several decades of warning time (median = 62 years; >20 years for 99% of replicates), but suggest that conservation actions should begin as soon as a species is listed as Vulnerable, because 50% of replicates went extinct within 20 years of becoming uplisted to Critically Endangered. When only one criterion was used, warning times were substantially shorter, but more frequent assessments increased the warning time by about a decade. Overall, we found that the Red List criteria reliably provide a sensitive and precautionary way to assess extinction risk under climate change.
Keywords: IUCN Red List; Red List Categories and Criteria; climate change; linked demographic-habitat models; probability of extinction; threatened species.
© 2014 John Wiley & Sons Ltd.