As climate change alters global fire regimes, fire and forest managers must prioritize management actions that simultaneously protect sensitive resources and allow fire to maintain its ecological role. Over the last twenty years, this task has become more difficult, as increased fire severity and season length have caused suppression costs to rise from 16 to 52% of the USFS annual budget, limiting funding for other agency projects (USFS 2015). Further, climate change is expected to because increased fire frequency, severity, and area burned, exacerbating budgetary uncertainty and highlighting the need to prioritize management actions and ensure funds are used efficiently. Whitebark pine (Pinus albicaulis) is a widely distributed subalpine and treeline species of management concern in the western U.S that relies on high severity burns to create early seral communities that favor its regeneration, but wildfire may also kill mature whitebark pine in absence of protective actions to prevent mortality. Management using wildland fire, or mid-to high-severity prescribed burns therefore prioritize regeneration opportunities over mature tree persistence. However, empirical analyses demonstrating the relative importance of regeneration vs. mature trees to population growth are lacking. Additionally, reductions in fire return interval, which are predicted to occur as the climate warms (from >120 to <30 years in the GYE), increase the risk of population extinction. We do not yet understand the impact of these novel fire regimes on whitebark pine population extinction risk and population dynamics. We created a stochastic stage-based projection model to investigate the effect of decreasing fire return intervals on the probability of extinction and time to extinction of a whitebark pine population. This projection model relies on demographic data collected intermittently from 1990 to 2017 from whitebark pine communities recovering from the 1988 Yellowstone fires and contiguous unburned locations, and values obtained from the literature. We projected whitebark pine population size 500 years into the future 10,000 times considering the effects of fire return intervals decreasing from > 200 years to < 30 years by 2100. We used these projected population sizes to estimate population density at each time step, probability of population extinction, average time to population extinction, and the stochastic growth rate. We also estimated the contribution of each survival and transition rate to the overall population growth (i.e., stochastic elasticity) to determine whether protecting mature trees or promoting regeneration would benefit whitebark pine population growth as fire regimes change. As originally proposed, the model structure does not sufficiently describe whitebark pine population dynamics, and results in unrealistically high population densities (maximum projected density over 10,000 iterations = 6.79e+89 trees/m2). We estimated stochastic lambda to be 1.12, or 12% growth per year. The original proposal and literature lack an understanding of the specific nature and timing of density-dependent factors that restrict whitebark recruitment and growth in successional communities, but the 1990 to 2017 post-fire dataset may provide insight into these effects in the developing community. In light of our initial results, we are expanding the model to incorporate density-dependent effects including the effects of canopy closure on germination and seedling survival, variation in seed dispersal rates as seed production fluctuates, the relationship between cone production and predispersal cone predation, and the increase in post-dispersal seed predation with time since fire. To begin, we incorporated the effects of canopy closure on germination and cone crop size on seed dispersal. Management recommendations will be made when the final model incorporating density-dependent effects is completed.