Species distributions are largely determined by three main drivers: abiotic environmental conditions, dispersal, and biotic interactions. Because abiotic environmental conditions determine habitat suitability, they also have direct implications on the capacity of species to disperse and how species interact with one another in space. However, it is specifically the variability in abiotic environmental conditions (i.e., environmental heterogeneity) and how they are spatially structured (i.e., environmental spatial autocorrelation - ESA) that determines whether or not a habitat, or even a landscape, is environmentally suitable for species establishment. Environmental heterogeneity itself is spatially structured; where environmental conditions/features that are closer together in space tend to be more similar than those farther apart. As such, the spatial structure of environmental features (i.e., ESA) mimics dispersal networks because spatial patterns in environmental heterogeneity affect the strategies and energetic costs (and their associated fitness consequences) involved in movement and dispersal among patches. At broad spatial scales, species distributions are shaped by environmental conditions, namely, those of climate. Climatic conditions thus also impose important physiological and life history constraints on species and in accordance with environmental features, are also often heterogeneous and spatially structured. Yet, how they affect and contribute to species distributions remains unknown. Here, we use species distribution models (SDMs) in a novel framework in which we demonstrate for the first time, the influence of climate heterogeneity (within and between patches) and climate spatial structure on species distributions. We evaluated six different SDMs testing both the individual and combined effects of climate variables (i.e., between and within-patch climate heterogeneity and climate spatial structure) on species distributions, using 301 North American amphibian species as a case study. Our results demonstrate that a model using climate spatial structure as a predictor alone explained species distributions better than any other model in the majority of species. Although a model including both climate heterogeneity (within and between-patch) and climate spatial structure as predictors was only the best model for a handful of species, we provide critical evidence that there is added value in considering climate spatial structure when fitting different SDMs for the same species. Most importantly, we demonstrate that climate spatial structure and heterogeneity are important mechanisms driving species distributions in North America.