Pinyon–juniper ecosystems in the Western United States exist on vast areas of public lands and are ecologically, economically, and culturally significant. Shifts in climate and land use have driven tree expansion and densification in these systems, creating degraded landscapes and prompting the implementation of tree reduction treatments. In my dissertation, I utilized existing data sources to assess the effects of these treatments and investigate the influence of treatment factors and environmental conditions on treatment outcomes. I first used observational monitoring data and causal inference techniques to assess pinyon–juniper treatment effectiveness in Northwest Colorado. After developing a thorough methodology to account for challenges in data quality, I found that treatments had varied effects on understory vegetation cover—both native and nonnative—and that those effects changed with the method of tree removal and the vegetation cover at a site prior to treatment. I then investigated treatment effectiveness at sites on the Colorado Plateau using meta-analytical methods and existing data from the literature. Findings from my meta-analysis also showed that the effect of treatment on understory vegetation varied by treatment type, although was mostly positive, and included variation in treatment effects by environmental conditions like aridity and elevation. The Northwest Colorado study and the Colorado Plateau study both revealed potential treatment benefits of increased native understory vegetation cover and potential risks of invasive species introduction and proliferation, highlighting tradeoffs of treatment implementation. Together, my dissertation chapters convey the power of utilizing existing data, particularly to assess landscape-scale restoration treatments carried out on U.S. public lands. My work emphasizes the knowledge that can be gleaned from treatment evaluation and provides data and information to support land managers in promoting more resilient ecosystems in the face of environmental change.