A WESTERN UNITED STATES ASSESSMENT OF SOIL-CLIMATE FOR INFORMING CONSERVATION OF SAGEBRUSH ECOSYSTEMS

Patterns and fluctuations of soil temperature and moisture can affect microbial activity, plant growth, and fuel moisture; however, there is a lack of spatial information describing the persistence, anomalies, and changes in soil-climate and how these changes may influence biological processes. Therefore, developing methods to estimate soil moisture variability could increase our understanding of habitat conditions to improve conservation across diverse ecosystems. We developed a framework that expands the Newhall simulation model to estimate spatiotemporal-varying soil moisture (monthly, annual, and seasonal) and temperature-moisture regimes within a high-performance computing environment using a hybrid of climate (temperature, precipitation, snow) and soils data. As a proof of concept, we applied the model across the western United States with monthly climate averages (1981–2010). These results demonstrated significant correlations where soil moisture variables predicted sagebrush (R² = 0.51), annual herbaceous plant cover (R² = 0.687), exposed soil (R² = 0.656), and fire occurrence (R² = 0.343). The resulting data are intended to help improve conservation and habitat management by linking patterns of soil-climate to restoration effectiveness, the spread of invasive species, wildfire risk, and prioritization of habitat conservation/restoration. Using this modeling framework, we are expanding temporal perspectives using climate scenarios and annual time-step climate archives to assess inter-annual variability; therefore, we can increase our understanding of how soil moisture persistence and drought deficits may affect biological processes.