Ecosystem dynamic models have been widely used to estimate terrestrial carbon flux and to project ecosystem structure and composition over time and space, because of their efficiency over direct field measurements and easy applicability to broader spatial coverage. However, such models have also been associated with internal uncertainties, as well as complexities arising from distinct qualities of the ecosystem being analyzed. The widespread sagebrush-steppe ecosystem (dominated by Artemisia spp.) in Western North America holds high ecological and social significance, but is threatened by anthropogenic forcing factors, including impacts from invasive species, climate change, and altered fire regimes. To restore the ecosystem, land managers have focused on reducing flammable vegetation and seeding native species. However, the collective effects of restoration activities, fire, climate change, and invasive species on ecosystem dynamics are poorly understood. We applied the Ecosystem Demography (ED2) model to analyze its effectiveness in predicting plant function type (PFT) composition and ecosystem fluxes, parameterized and validated using empirical datasets for different carbon, vegetation and fire scenarios at Reynolds Creek Experimental Watershed (RCEW), Idaho, USA. We initialized ED2 with 20 x 40 grids of 1 km resolution representing and allowed PFTs to grow for 20 years to reach an equilibrium state. Results showed shrubs dominating C3 grass in a few years of time, sooner for increased CO2 and initial ecosystem condition. A separate scenario with potential fire showed significant loss in biomass within eight years of time. Results from this modeling study can improve our understanding of broad-scale ecosystem processes in sagebrush-steppe landscapes and inform land management and restoration strategies.