BackgroundThe environment is a strong driver of genetic structure in many natural populations, yet often neglected in population genetic studies. This may be a particular problem in vagile species, where subtle structure cannot be explained by limitations to dispersal. These species might falsely be considered panmictic and hence potentially mismanaged. Here we analysed the genetic structure in an economically important and widespread pollinator, the buff-tailed bumble bee (Bombus terrestris), which is considered to be quasi-panmictic at mainland continental scales. We first quantified population structure in Romania and Bulgaria with spatially implicit Fst and Bayesian clustering analyses. We then incorporated environmental information to infer the influence of the permeability of the habitat matrix between populations (resistance distances) as well as environmental differences among sites in explaining population divergence.ResultsGenetic structure of the buff-tailed bumble bee was subtle and not detected by Bayesian clustering. As expected, geographic distance and habitat permeability were not informative in explaining the spatial pattern of genetic divergence. Yet, environmental variables related to temperature, vegetation and topography were highly informative, explaining between 33 and 39% of the genetic variation observed.ConclusionsWhere in the past spatially implicit approaches had repeatedly failed, incorporating environmental data proved to be highly beneficial in detecting and unravelling the drivers of genetic structure in this vagile and opportunistic species. Indeed, structure followed a pattern of isolation by environment, where the establishment of dispersers is limited by environmental differences among populations, resulting in the disruption of genetic connectivity and the divergence of populations through genetic drift and divergent natural selection. With this work, we highlight the potential of incorporating environmental differences among population locations to complement the more traditional approach of isolation by geographic distance, in order to obtain a holistic understanding of the processes driving structure in natural populations.