Predicting species extinctions due to climate change

Background/Question/Methods

Identifying species vulnerable to climate change remains a challenging task for conservation biologists.  Several new assessment approaches have been proposed for doing this, based on the assumption that  established assessments such as the IUCN Red List need revising or replacing because they have not explicitly considered climate change.  However, no assessment approach has been tested to determine its ability to identify species that might go extinct due to climate change.  To test the ability of the Red List system to identify species vulnerable to climate change, we developed a novel modeling approach, linking downscaled climate model ensembles, ecological niche models, and generic life history models that predict extinction probability. We generated replicate 100-year abundance trajectories under climate change for range-restricted reptiles and amphibians endemic to the US.  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 the number of years the simulated species was continuously listed in a threatened category.

Results/Conclusions

Analysis of simulation results reveals interacting effects of life history traits and range shifts on the vulnerability of species to climate change.  Our results also indicate that the IUCN Red List system nearly always (>95% of replicates) provides conservation practitioners with >20 years of advance warning prior to extinction, even for the species most vulnerable to climate change. However, our results strongly suggest that conservation actions should begin as soon as a species is listed as Vulnerable, because species often (>50% of replicates) went extinct within 20 years of becoming uplisted to the Critically Endangered category. Overall, we found that the Red List criteria reliably provide a sensitive and precautionary way to assess extinction risk under climate change.