Understanding and conserving ecological connectivity is critical to the preservation of vulnerable landscapes. Circuit theory, in which landscapes are imagined as circuit boards with varying resistances to the flow of current, is being increasingly used to model spatially explicit connectivity of landscapes and to inform land management and conservation decision-making. Utilizing continuous, quantitative estimates of percent cover by five land cover functional groups to create a conductance surface, this study expanded upon an established application of circuit theory that used the open-source software Circuitscape to model species-agnostic, omnidirectional connectivity. This model was automated using Python to create time-series connectivity maps from which comparisons could be made across time to assess pre- and postfire land cover patterns across the landscape. By applying this methodology to a U.S. Great Plains landscape affected by a large wildfire in 2012, this study found that for most functional land cover types, spatial configurations of areas of high and low connectivity changed in response to the wildfire disturbance, but quickly returned to pre-fire conditions. Exceptions were the tree and shrub functional groups, which saw persistent patterns of decreased connectivity in areas that were burned. This approach to modeling landscape connectivity over time could further enhance circuit theory-based assessments of landscapes affected by wildfire and tools for land managers promoting functional connectivity and resiliency in those landscapes.