We know that climate sensitivity can vary within species, but the factors that influence which climatic variables influence population dynamics remain unclear. In this study, I assess whether macroclimate influences the climate sensitivity of four high elevation conifer species: Pacific silver fir (Abies amabilis), mountain hemlock (Tsuga mertensiana), Alaska yellow cedar (Callitropsis nootkatensis), and sub-alpine fir (Abies lasiocarpa). I also investigate if climate sensitivity of tree communities Mt. Rainier is changing over time. To address these questions, I analyzed tree core data from three high elevation sites at Mt. Rainier National Park. Each site is located in a distinctly different climatic zone on the mountain. I compared standardized tree growth to climate variables (mean growing-season temperature, total growing-season precipitation, annual snowpack, climate moisture deficit, etc.) using linear mixed effect models and “treeclim”, a tree ring analysis program in R. With these methods, I determine how influential climate variables differ by location, by species and over time. Gaining more insight into which climate variables have the greatest influence on growth in different areas will allow us to better predict how specific plant populations will react to ongoing climate change. Moreover, studying tree communities at high elevations is particularly important, since behavior at treeline will determine whether a species’ range expands, contracts or shifts, which in turn has implications for both that species and other species. For example, conifer range expansion on Mt. Rainier could positively increase carbon sequestration (by increasing woody cover in the park) while negatively encroaching on the alpine wildflower meadows, a major attraction for tourists. Widespread range contractions could potentially reduce the ability of those forests to sequester carbon from the atmosphere. Thus, with better predictions of tree shifts, we can make more informed management decisions for ecotourism and conservation.