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The population concept is central in evolutionary and conservation biology, but identifying the boundaries of natural populations is often challenging. Here, we present a new approach for assessing spatial genetic structure without the a priori assumptions on the locations of populations made by adopting an individual-centred approach. Our method is based on assignment tests applied in a moving window over an extensively sampled study area. For each individual, a spatially explicit probability surface is constructed, showing the estimated probability of finding its multilocus genotype across the landscape, and identifying putative migrants. Population boundaries are localized by estimating the mean slope of these probability surfaces over all individuals to identify areas with genetic discontinuities. The significance of the genetic discontinuities is assessed by permutation tests. This new approach has the potential to reveal cryptic population structure and to improve our ability to understand gene flow dynamics across landscapes. We illustrate our approach by simulations and by analysing two empirical datasets: microsatellite data of Ursus arctos in Scandinavia, and amplified fragment length polymorphism (AFLP) data of Rhododendron ferrugineum in the Alps.