Big sagebrush Artemisia tridentata is the dominant plant across a major portion of the western United States. Occurring largely on public lands, this shrub is the subtle backdrop against which many of the most contentious issues facing land management in the West play out. Historically dismissed as merely a competitor for species more palatable to livestock, sagebrush recently gained national attention when the U.S. Fish and Wildlife Service reviewed the greater sage grouse for protection under the Endangered Species Act. Sagebrush systems have been reduced to about half of their historic extent by agriculture, urban development, oil and gas extraction, over-grazing, fire, and invasion by annual grasses. Sagebrush systems are further imperiled by climate change. Rising temperatures are likely to dramatically alter the availability of water in time and space, which could reduce the suitability of much of the current range of sagebrush.
My research will investigate the trajectory of sagebrush systems under changing climatic conditions at two scales. For a regional perspective, I will quantify the current composition and range of variation in sagebrush systems by analyzing climate data and a large vegetation data‑set from the Bureau of Land Management. This project investigates how differences in climate across the sagebrush region influence the importance of different plant functional groups. For a local perspective, I will investigate a large-scale sagebrush die-off in southwest Wyoming. In 2012, the region experienced severe drought conditions with very low precipitation accompanied by the highest temperatures on record. The region remained relatively dry in 2013 until September, when unusually high precipitation fell in one month. Following these events, land managers reported standing water in lowland positions and subsequent widespread sagebrush mortality. In 2016, I sampled 95 vegetation plots within and around the sagebrush die-off. Using these 95 points as a reference, I will investigate the ability of remote sensing imagery to detect the die-off.