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The 1964 Wilderness Act was passed to preserve undeveloped landscapes and to sustain opportunities for people to experience and enjoy “natural” places. Nevertheless, wilderness is still vulnerable to the direct and indirect impacts of climate change. Using active management to respond to climate change in wilderness is complicated by the very protections afforded to wilderness that limit human impacts. Scientists at the Aldo Leopold Wilderness Research Institute (ALWRI) worked with land stewards and their collaborators to apply the resist-accept-direct (RAD) framework to illuminate a decision space surrounding climate-driven ecological transformation of whitebark pine ecosystems in wilderness. Whitebark pine (Pinus albicaulis) is a federally threatened and geographically widespread upper subalpine tree species threatened by warming temperatures, wildfire, forest pests, and disease. Further loss of whitebark pine may ecologically destabilize upper subalpine communities and impact biocultural relationships important to Native American heritage. Addressing the loss of whitebark pine and associated ecosystems is particularly complex, as much of the estimated range of whitebark pine overlaps with wilderness. The overarching goal of the RAD Decisions in Rad Landscapes: Climate Adaptation for Whitebark Pine in Wilderness case study was to provide USDA Forest Service staff and partners with knowledge and tools to support intentional and transparent decision-making for whitebark pine ecosystems in wilderness. Scientists from ALWRI researched the potential ecological consequences of climate change for whitebark pine as well as managers’ perceived ability to respond to ecological change. Additionally, scientists at ALWRI facilitated a 2-day workshop which engaged Forest Service staff, National Park Service staff, Tribal staff and representatives, and non-profit partners in an adaptation planning process to clarify values and desired conditions, generate decision alternatives under the RAD framework, and evaluate the potential implications of various decision alternatives.