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North America has a diverse array of mammalian species. Model projections indicate significant variations in future climate conditions of North America, and the habitats of woodland mammals of this continent may be particularly sensitive to changes in climate.We report on the potential spatial distributions of 13 wide‐ranging, relatively common species of North American woodland mammals under future climate scenarios.We examined the potential influence of the mean and seasonal climate variables on the distribution of species. Presence‐only occurrence records of species, four predictor variables, two future climate scenarios (Representative Concentration Pathways 4.5 and 8.5), and two time steps (current and 2070) were used to build species' distribution models using a maximum entropy algorithm (MaxEnt).Our results suggested that overall, 11 of the 13 species are likely to gain climatically suitable space (regions where climate conditions will be similar to those of area currently occupied) at the continental scale, but American marten Martes americana and 'woodland' caribou Rangifer tarandus are likely to lose suitable climate range by 2070. Furthermore, climate space is likely to be expanding northwards under future climate scenarios for most of the mammals, and many jurisdictions in the border region between Canada and the USA are likely to lose iconic species, such as moose Alces alces. We identified regions as potential in situ and ex situ climate change refugia, which are increasingly considered to be important for biodiversity conservation.The model results suggest significant implications for conservation planning for the 13 mammalian species under global climate change, especially at fine spatial scales. Numerous species that are presently common at their southern range edge will be functionally or completely extirpated in 50 years. The potential in situ and ex situ climate change refugia could provide an effective support for adaptive strategies aimed at species conservation planning. [ABSTRACT FROM AUTHOR]