1. The negative impact of invasive alien plants (IAPs) in protected areas (PAs) is managed through control programmes, often using area-based management, where identified IAPs in management units are controlled simultaneously. However, this approach has shortfalls, including the methods used to prioritise management units, spatial grain dependence and spatial interdependence of management units. Species-based management approaches, though used less frequently, are usually aimed at eradication. 2. We propose using a Commonness framework to reconcile area-based and species-based management approaches, viewing the invasion process as a population trajectory from uncommon to common. The framework assigns species to one of eight commonness types at a given scale using three species characteristics: local population size (small/large), geographic range (wide/narrow) and spatial pattern (even/clumped). These metrics were calculated using a comprehensive fine-scale IAP dataset from Table Mountain National Park, South Africa, at six scales of increasing spatial grain, enabling quantification of the effects of scale and species' range structure on management potential of IAPs. 3. Most species exhibited the Point Source commonness type at fine spatial grains, requiring Rapid Response, Reconnaissance or Sweeping management strategies. At coarser grains, species were mostly classed within wide occupancy ranges, with small population sizes (Dispersed and Sparse types). The Control strategy currently applied in the area (best suited for large populations across a narrow range) should be re-evaluated given the progress made by historical clearing in reducing commonness. Using a phylo-tree, we identified adjacent areas that require different strategies as well as changes in species-specific goals at particular sites with increasing grain coarseness. For example, species generally deemed to be common, for which a Control strategy is applied, may require Rapid Response type strategies for isolated and/or small, clumped subpopulations.