GSA Annual Meeting in Phoenix, Arizona, USA - 2019

Paper No. 17-12
Presentation Time: 11:20 AM


HAUSNER, Mark B., ALBANO, Christine, PEARSON, Chris and HUNTINGTON, Justin L., Division of Hydrologic Sciences, Desert Research Institute, 2215 Raggio Pkwy, Reno, NV 89512

Mountain meadows are productive ecosystems with unique hydrologic, vegetative, and soil characteristics. In the Sierra Nevada, drought, climate change, and local and regional development impact meadow health, leading to encroachment by woody species and degradation of riparian habitat. Addressing this degradation presents management challenges on a regional scale. Recent advances in cloud computing have made it possible to access and analyze remotely sensed data at high spatial and temporal resolution. Here we use the Landsat archive to develop a robust and repeatable analysis to identify trends in the vegetation vigor and hydrologic function of meadows throughout the Lake Tahoe Basin. We use spatially and temporally averaged normalized difference vegetation index (NDVI) as an annual indicator of the state of the meadow for the duration of the Landsat archive (1985 – 2018). To control for both site-to-site and inter-annual variability, we use a multivariate regression that includes the full data set of 353 meadows, annual meteorological data, other remotely sensed data, and geomorphic characteristics. Using the full data set minimizes the impacts of transient signals like wildfires or restoration work. After controlling for the natural variability across the basin, the residuals of this regression identify both long-term trends in meadow condition and transient impacts, such as fire or restoration projects.