Detecting Extinction Risk from Climate Change by IUCN Red List Criteria
AuthorKeith, DA; Mahony, M; Hines, H; Elith, J; Regan, TJ; Baumgartner, JB; Hunter, D; Heard, GW; Mitchell, NJ; Parris, KM; ...
Source TitleCONSERVATION BIOLOGY
University of Melbourne Author/sRegan, Tracey; Heard, Geoffrey; TRACY, CHRISTOPHER; Elith, Rosemary; Tingley, Reid; Baumgartner, John; West, Matthew; Penman, Trent; Baumgartner, John; West, Matthew
AffiliationSchool of Botany
Forest and Ecosystem Science
Document TypeJournal Article
CitationsKeith, DA; Mahony, M; Hines, H; Elith, J; Regan, TJ; Baumgartner, JB; Hunter, D; Heard, GW; Mitchell, NJ; Parris, KM; Penman, T; Scheele, B; Simpson, CC; Tingley, R; Tracy, CR; West, M; Akcakaya, HR, Detecting Extinction Risk from Climate Change by IUCN Red List Criteria, CONSERVATION BIOLOGY, 2014, 28 (3), pp. 810 - 819
Access StatusOpen Access
Anthropogenic climate change is a key threat to global biodiversity. To inform strategic actions aimed at conserving biodiversity as climate changes, conservation planners need early warning of the risks faced by different species. The IUCN Red List criteria for threatened species are widely acknowledged as useful risk assessment tools for informing conservation under constraints imposed by limited data. However, doubts have been expressed about the ability of the criteria to detect risks imposed by potentially slow-acting threats such as climate change, particularly because criteria addressing rates of population decline are assessed over time scales as short as 10 years. We used spatially explicit stochastic population models and dynamic species distribution models projected to future climates to determine how long before extinction a species would become eligible for listing as threatened based on the IUCN Red List criteria. We focused on a short-lived frog species (Assa darlingtoni) chosen specifically to represent potential weaknesses in the criteria to allow detailed consideration of the analytical issues and to develop an approach for wider application. The criteria were more sensitive to climate change than previously anticipated; lead times between initial listing in a threatened category and predicted extinction varied from 40 to 80 years, depending on data availability. We attributed this sensitivity primarily to the ensemble properties of the criteria that assess contrasting symptoms of extinction risk. Nevertheless, we recommend the robustness of the criteria warrants further investigation across species with contrasting life histories and patterns of decline. The adequacy of these lead times for early warning depends on practicalities of environmental policy and management, bureaucratic or political inertia, and the anticipated species response times to management actions.
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