With projected decreases in biodiversity looming due to changing environmental conditions, it is important for conservation managers to have accurate predictions of species’ distributions. Species distribution modeling (SDM) and mechanistic modeling approaches that account for biophysical factors are important tools for predicting potential distributions and range limitations for many species. Recent advances in microclimate modeling have allowed for the incorporation of microclimate models into SDMs and other mechanistic approaches, a critical step for developing biologically relevant models for the variety of organisms reliant on microclimatic regimes. However, there remains a need to integrate microclimate-derived SDMs and mechanistic models at fine spatio-temporal scales to quantify and limit model uncertainty. In this study, we developed microclimate SDMs and mechanistic models of dispersal resistance for two plethodontid salamanders at a fine spatial resolution (3 m2) across Great Smoky Mountains National Park, USA during the 2010, 2030, and 2050 time periods. We determined the spatio-temporal agreement between microclimate SDMs and dispersal resistance to assess model uncertainty. We also modeled microclimate dispersal corridors and assessed spatio-temporal variability within these pathways. We found that agreement between microclimate SDMs and dispersal resistance models was generally poor. Importantly, model agreement varied across temporal periods and at differing spatial extents and resolutions. Furthermore, dispersal corridors varied temporally and demonstrated increased habitat fragmentation under future projections. The findings from this study highlight a potential contradiction in which we have a need to model species distributions with microclimate data at finer, more biologically meaningful resolutions but model agreement between correlative and mechanistic approaches may be weakened at these fine scales. Further quantifying model uncertainty and working on alternative methods for integrating SDMs and mechanistic models at fine-scale resolutions will be an important step towards accurately predicting species distributions under changing environmental conditions.