Climate change over the past century has altered vegetation community composition and species distributions across rangelands in the western United States. The scale and magnitude of climatic influences are largely unknown. We used fractional component cover data for rangeland functional groups and weather data from the 1985 to 2023 reference period in conjunction with soils and topography data to develop empirical models describing the spatio-temporal variation in component cover. To investigate the ramifications of future change across the western US, we extended models based on historical relationships over the reference period to model landscape effects based on future weather conditions from two emissions scenarios (Representative Concentration Pathways [RCP] 4.5 and 8.5) and three time periods (2020s, 2050s, and 2080s). We build upon the projections of Rigge 2022 and Rigge et al. 2023, expanding our study area to include the entire Rangeland Condition Monitoring Assessment and Projection (RCMAP) study area (including all the sagebrush biome and Canadian expansion), using updated climate projections (Mahony et al. 2022), and applying a Deep Neural Net (DNN) classifier. In general, both scenarios yielded similar results, but RCP 8.5 tended to be more extreme, with greater change relative to the reference period. This information can be used to inform management to prepare for future vegetation composition and cover through the prioritization of conservation and restoration and shed light on species range shifts.