Assessing climate change vulnerability for ecosystems of the southwestern U.S.
Land managers require information about the ongoing and potential effects of climate change to coordinate responses for ecosystems, species, and human communities. Several organizations in the Southwestern US, including the Rocky Mountain Research Station of the US Forest Service, The Nature Conservancy, and others have developed assessments, tools, and methods for evaluating vulnerability for key ecological components (e.g., Robles and Enquist 2010, Davison et al. 2011). Our climate change vulnerability assessment complements much of this work with the development of an ecosystem-based analysis of adequate spatial and thematic detail to support local decisions. The study utilized a correlative model based on site potential and known vegetation-climate relationships to rate vulnerability by the projected departure from the historic climate envelope for a given ecosystem and location. Uncertainty was evaluated based on the level of agreement among outputs from three climate models with the same emissions scenario. Though the assessment was conducted on all lands in Arizona and New Mexico, the Cibola National Forest, in central New Mexico, was used as a case study from which to report and discuss results.
The vulnerability assessment resulted in surfaces of vulnerability and uncertainy, revealing broad patterns of low, moderate, and high vulnerability across the extent of the two-state area. The results for the case study show that most of the area, 90%, is in moderate to high vulnerability (2-4 standard deviations from the climate envelope mean. By the year 2090, only a small area of about 5% of the Cibola National Forest is projected to remain within its historic climate envelope. The proportion of the study area in each vulnerability category is comparable to the proportions reported for individual ecosystem types. The assessment represents future climate as a potential stressor on the structure, composition, and function of ecosystems, and in specific terms as the relative probability of type conversion.