AbstractAimThe alpine region of mainland Australia is one of the world's 187 biodiversity hotspots. Genetic analyses of Australian alpine fauna indicate high levels of endemism on fine spatial scales, unlike Northern Hemisphere alpine systems where shallow genetic differentiation is typically observed among populations. These discrepancies have been attributed to differences in elevation and influence from glacial activity, and point to a unique phylogeographic history affecting Australian alpine biodiversity. To test generality of these findings across Australian alpine biota, we assessed patterns of genetic structure across plant species.LocationThe Australian Alps, Victoria, eastern Australia.MethodsWe used an economical pooled genotyping‐by‐sequencing (GBS) approach to examine patterns of genetic diversity among seven widespread species including shrubs and forbs from 16 mountain summits in the Australian Alpine National Park. Patterns of genetic structure among summit populations for each species were inferred from an average of 2,778 independentSNPloci using Bayesian phylogenomic inference and clustering approaches.ResultsSNPresults were consistent across species in identifying deep evolutionary splits among summit communities from the Northern and Central Victorian Alpine regions. These patterns of genetic structure are also consistent with those previously reported for invertebrate and mammal taxa. However, local genetic structure was less pronounced in the plants, supporting the notion that population connectivity tends to be higher in plant species.Main conclusionThere is deep lineage diversification between the North and Central Victorian Alpine regions, reflecting a high level of endemism. These findings differ from those reported for alpine biodiversity from New South Wales and much of the Northern Hemisphere, and support the notion that genetic diversity is typically greatest in areas least affected by historical ice sheet formation. We discuss the implications of our findings in the context of conservation planning, and highlight the benefits of this rapid and cost‐effective genome scan approach for characterizing evolutionary processes at multispecies and landscape scales.