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Abstract Conservationists and scientists throughout the world consider butterflies important indicators of broadscale factors affecting global biodiversity. And like other facets of biodiversity, declines in many butterfly populations appear related to human activities, and the potential of their extinction could jeopardize key ecosystem services. The regal fritillary ( Argynnis idalia ), a butterfly associated with tall‐ and mixed‐grass prairies in the United States, is a species currently being considered for federal protection under the Endangered Species Act. As with many butterflies, a paucity of data makes evidence‐based assessments of their population and distributional status difficult. Citizen science data provide one possible source of broadscale information about this species, but using these data is not simple because of spatial scaling and sampling bias problems. Here, we developed a model to analyze a data set from the citizen science program called the Fourth of July Butterfly Count (4JC) to make inferences about regal fritillary abundance in the Great Plains and Midwest regions of the United States. More specifically, we aimed to determine the extent to which grassland fragmentation, spring weather conditions, or other spatial factors were correlated with the intensity of use within 4JC survey areas. Our findings indicated that regal fritillaries used locations surrounded by grassland and with minimal forest cover. We included smoothing spline terms in our model, which indicated other sources of spatial structuring in these data. It is possible that these additional sources of variation could reflect variation in habitat quality. We also found that local averaged spring weather variables indicated that regal fritillary abundance varied over a wider range of precipitation conditions, but a narrower range of temperature conditions. Further analyses indicated that a systematic increase in temperature from climate change could lead to a pronounced northward shift in the regal fritillary's distribution. These findings have implications for the development of a recovery plan, since such a plan will need to outline a strategy that accounts for a range of patch sizes whose quality appears to vary spatially, as well as address numerous uncertainties about the future.