Climate change threatens the persistence of species found on isolated mountain ranges because of their insular nature. The Great Basin provides an excellent system to study the effects of climate change where immigration is limited. The McDonald and Brown (1992) climate change model was based on three assumptions: 1) an increase in regional temperature of 3ºC by 2050, 2) a 500 meter shift in elevation, resulting in a decrease in total area of the mountain life zones, and 3) mammalian fauna exhibits the nested subset pattern. Criticism of the McDonald and Brown (1992) model has warranted the re-evaluation of the effects of climate change on the distributions and predicted extinctions of montane mammals in the Great Basin. We have modeled the distributions of twelve montane mammals found in the Great Basin and have identified possible extinctions using maximum entropy modeling (Maxent). Inputs were species occurrence records from the Global Biodiversity Information Network (GBIF), GAP maps, and present and future climate data from WorldCLIM. We predicted the changed distributions for two emission scenarios of changing climate for the year 2050: a minimum (b2a) and a maximum (a2a).
Results/Conclusions
Overall, a majority of Great Basin mammal species examined are predicted to experience reductions in distribution ranging from approximately 2-64% for a minimum emission scenario (b2a) and 39-79% for a maximum emission scenario (a2a). The predictions made by Maxent were compared to those of the McDonald and Brown (1992) relative to local extinctions at a particular site. In particular, there was agreement between models on four local extinctions for a minimum emission scenario (b2a) and five local extinctions for a maximum emission scenario (a2a). Instances in which model predictions relative to species distributions and abundances are consistent might provide a basis on which we can develop generalities about biotic responses to changing environmental conditions. By better understanding what environmental factors influence species occurrence, we can infer how climate change is likely to affect biodiversity and their spatial distributions. With this better understanding, we can manage and conserve populations.