Print PageIdentifying potential ramifications of global climate change on organisms presents a significant challenge to ecologists, conservationists, and natural resource managers. Because it is not feasible to address the response of entire assemblages of organisms to large-scale changes in climate with experimentation, modeling has emerged as the preeminent tool for addressing long-term conservation needs of species. Amphibians are one of the world's most imperiled taxa, which makes understanding their response to climate change extremely important when formulating conservation plans. We surveyed wildlife managers responsible for amphibian monitoring and management in each of eight southeastern states to identify the five amphibians that they were most concerned with in the face of climate change. We then forecasted these species' responses to climate change using species distribution models generated in Maxent. Models were based on a suite of 11 climate variables at a scale of 1 km2, and species presences were identified using a combination of museum database records and state-held records on species localities. As such, these models represent some of the most robust assessments of how amphibian distributions may shift under climate change. We generated ensemble models for each species using two general circulation models (GCM) and two CO2 emissions scenarios.
Results/Conclusions
The survey of state priority species resulted in a list of 21 amphibians. The list included 16 salamanders and five frogs, and nearly half of the species were listed as a priority by more than one state. Habitat suitability loss was observed in all species in both the 2020 and 2050 climate projections; however, the proportion of lost habitat was not equivalent among species. Wide-ranging species that extend beyond the southeast are projected to fare better than species with small ranges. For example, the eastern tiger salamander is projected maintain 62% of currently suitable habitat by 2050, while gopher frogs are projected to only maintain 4% under the same GCM/CO2 scenario. In addition to identifying species most at risk to changing climates, these models identify areas most valuable to species protection in the future. Many of the species of concern to ecologists are those that are either inherently rare, or have become rare. As a result, data deficiencies were common during the modeling process. We discuss how this was addressed, and the implications for model results. The species list, and our use of it during the modeling process, demonstrates how expert opinion can help prioritize limited conservation resources.
