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Effective range management requires long-term planning, but in this era of unprecedented climate change, multiple uncertainties increase the challenges associated with such planning. Scenario planning (SP) is one tool to deal with these uncertainties because it guides managers through a process of examining their management practice options under a range of divergent and challenging, yet plausible, story lines. However, SP may lack the quantitative comparisons and scientific process needed by public land management agencies to support their decision-making. We used an iterative approach for combining quantitative ecological modeling with qualitative, participatory SP in a southwest South Dakota study area. This approach included a series of workshops with resource managers to identify key resources, impacts, and uncertainties under four climate change scenarios. In the workshops, managers qualitatively explored the interacting effects of grazing, fire, climate, and invasive species on vegetation condition and key animal species. Using the information on interacting influences garnered from these workshops and beginning with the conceptual state-and-transition models and productivity information in ecological site descriptions for dominant soil types in the study area, we developed a state-and-transition simulation model of vegetation dynamics. We used the model to explore the effects of four general management approaches under the four climate scenarios.� In the qualitative SP workshops, managers imagined the need to reduce stocking rates under hotter and drier conditions, and they expressed concerns about invasive plants in wetter conditions. Key results from the modeling exercise, however, suggest that conservative stocking rates maintained by the national park in the study area may adversely affect vegetation composition in any climate scenario. Results also illustrate potential problems (e.g., lack of forage, increase of undesirable vegetation states) that may arise when management practices designed for one climate projection are implemented under different climate conditions.