Biodiversity studies that guide agricultural subsidy policy have generally compared farming systems at a single spatial scale: the field. However, diversity patterns vary across spatial scales. Here, we examined the effects of farming system (organic vs. conventional) and position in the field (edge vs. center) on plant species richness in wheat fields at three spatial scales. We quantified alpha-, beta-, and gamma-diversity at the microscale in 800 plots, at the mesoscale in 40 fields, and at the macroscale in three regions using the additive partitioning approach, and evaluated the relative contribution of beta-diversity at each spatial scale to total observed species richness. We found that alpha-, beta-, and gamma-diversity were higher in organic than conventional fields and higher at the field edge than in the field center at all spatial scales. In both farming systems, beta-diversity at the meso- and macroscale explained most of the overall species richness (up to 37% and 25%, respectively), indicating considerable differences in community composition among fields and regions due to environmental heterogeneity. The spatial scale at which beta-diversity contributed the most to overall species richness differed between rare and common species. Total richness of rare species (present in < or = 5% of total samples) was mainly explained by differences in community composition at the meso- and macroscale (up to 27% and 48%, respectively), but only in organic fields. Total richness of common species (present in > or = 25% of total samples) was explained by differences in community composition at the micro- and mesoscale (up to 29% and 47%, respectively), i.e., among plots and fields, independent of farming system. Our results show that organic farming made the greatest contribution to total species richness at the meso (among fields) and macro (among regions) scale due to environmental heterogeneity. Hence, agri-environment schemes should exploit this large-scale contribution of beta-diversity by tailoring schemes at regional scales to maximize dissimilarity between conservation areas using geographic information systems rather than focusing entirely at the classical local-field scale, which is the current practice.