Species inhabiting sky islands are particularly susceptible to climate and land-use change-processes that drive the reduction of an already limited habitable area. As the temperature and precipitation patterns shift toward those of a more arid environment, the climate envelope for a given species will decrease in size or shift toward higher latitudes in the southern hemisphere. Species' capacity to migrate if the climatic and/or structural suitability of their habitat changes, that is, along with their climate envelopes, should therefore be determined. This task requires an understanding of species' dispersal capacity. Here, we analyzed the population genetic structure of the endemic sky-island lizard Liolaemus nigroviridis using SNPs and mitochondrial DNA sequences. We examined the population genetic differentiation and possible temporal changes using historical data of mtDNA sequences and patterns of population demography over time. L. nigroviridis exhibited a high population genetic structure between mountains, suggesting the effect of geographic barriers and low dispersal capacity that would prevent the species from migrating along with its climate envelope in future scenarios. Four evolutionary significant units and five management units were detected. However, at a smaller geographic scale, within a single sampling site, gene flow was observed across 1.2 km of continuous habitat, suggesting that the species can disperse within a sky island but not between sky islands. Populations in the Coastal and northernmost Andean studied locality showed decreasing effective population sizes in the last 2000 years, possibly as a result of climate change. We propose that since the Coastal-Range Cantillana population is a declining unique genetic entity geographically isolated and surrounded by a matrix of anthropization, it is a good candidate for assisted migration. Our study addresses the challenge of conserving sky-island species by exploring population genetic differentiation and patterns of population demography over time in the context of climate and land-use change, providing essential information for decision-making.