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Assessing Vulnerability and Resilience of Major Vegetation Types of the Western Interior U.S.- Forests and Woodlands
U.S. Department of the Interior, Bureau of Land Management

The objectives of this project are to understand current trends in climate change across the western conterminous United States, assess the potential impact of these changes on major vegetation types of high importance to BLM management, and interpret these changes to assist BLM in determining climate smart management strategies. This project is based in part on methods that have been developed in response to BLM management needs during NatureServe’s work across the region, on Rapid Ecoregional Assessments in the Great Basin, the Mojave Basin, and the Madrean ecoregions (e.g., Comer et al. 2013, Crist et al. 2014), and on methods piloted with the U.S. Fish and Wildlife Service and the Desert Landscape Conservation Cooperative (Comer et al. 2012).

NatureServe’s framework for measuring climate change vulnerability of habitats and ecosystems (HCCVI) provides a practical approach to organize criteria and indicators for this purpose (Comer et al. 2012, Comer et al, in review). The methods developed for the HCCVI are applicable to any given ecosystem or community type that the user might select; wildlife habitat can also be assessed with this framework. For this assessment, NatureServe’s terrestrial ecological systems classification (Comer et al. 2003) is used to define types being assessed. The advantage of using this classification system for this approach is that it represents an established nationwide classification of several hundred upland and wetland types mapped for use by federal and state resource managers (Comer and Schulz 2007, Rollins 2009) in the USA and adjacent Canada and Mexico (Comer et al. in prep). The expected historical extents, or “potential” distribution of each type, mapped at 90m pixel resolution, or upscaled to 800m pixel resolution, are used, depending on the specific analysis.

Citation
Comer, P., M. Reid, K. Schulz, J. Hak, S. Auer, M. Kling, and H. Hamilton