CSP identifies vulnerable Sierra Nevada meadows using climate and remote sensing data

CSP is developing a decision framework for focusing restoration and conservation actions in Sierra Nevada meadows based on an assessment of their vulnerability to climate change.

Two CSP scientists — Christine Albano and Meredith McClure — are leading a study of meadow ecosystems in the Sierra Nevada ecoregion. The 2-year study, which kicked off this past July, involves developing a tool to identify the most vulnerable meadows to guide decision-making and monitoring in these areas. The CSP team is working with scientists from the Desert Research Institute (DRI) as well as resource managers from the Forest Service. The resulting decision-support tool will be piloted by the Amador-Calaveras Consensus Group (ACCG), a consortium of 34 organizations that plans to prioritize 20 meadows for restoration in the upper Mokelumne, Stanislaus, Calaveras, and Consumnes watersheds of California.

The study focuses on meadows because of their ecological significance. Although they comprise less than 1 percent of lands within the Sierra Nevada ecoregion, meadows perform critical functions: they store carbon and nitrogen, mediate surface water flows, recharge aquifers, filter sediments, and provide refugia for numerous species. Unfortunately, they are highly vulnerable to climate variations because they depend largely on shallow groundwater systems to feed surface flows, seeps, and springs. These systems can be profoundly affected by rising temperatures and reductions in rainfall and snow pack.

To assess how vegetation has changed in response to variations in climate, the research team is analyzing 26 years of data for about 6,000 meadows and evaluating these responses in the context of geologic, topographic, and hydrologic factors. The project builds on existing work —datasets, analyses, computational methods, and software — developed by the PIs and partners. Stakeholders will be able to visualize vegetation conditions under various climate scenarios and time scales using a Google Earth technology.