Scarce funds for conservation need to be optimally used, yet there are few studies that record the costs and projected outcomes of major conservation efforts. Here we document the historical costs and extent of efforts to control invasive alien plants in the protected areas of the Cape Floristic Region of South Africa, a biodiversity hotspot of global importance. We also estimate the resources that would be needed to bring the problem under control within a reasonable timeframe, under a range of scenarios of funding, rate of spread, and management effort. Trees and shrubs in the genera Pinus, Acacia, Eucalyptus, Hakea, Leptospermum and Populus were estimated to cover N 66% of 750 000 ha at various densities in 2014. Historical costs of attempts to control these invasions over the past 20 years amounted to ZAR 564 million (~38 million US$), most of which (90%) was expended on Acacia, Pinus and Hakea in that order. The estimated cost to bring remaining invasions under control was between ZAR 170 and 2608 million (~1.3 and 174 million US$), depending on the scenario. Only substantial increases in annual funding under a scenario of low spread (4%), and removal of some taxa from the control programme, would allow for control to be achieved in b 20 years. Even with increased spending, control would probably not be achieved under less favourable but more probable scenarios. Our findings suggest that, unless bold steps are taken to improve management, then a great deal of money would have been, and will continue to be, wasted. The essential element of an improved management approach would be to practice conservation triage, focusing effort only on priority areas and species, and accepting trade-offs between conserving biodiversity and reducing invasions.

Successful long-term invasive alien plant control programmes rely on alien plant distribution and abundance data to assess, prioritise, implement and monitor the efficacy of the programme. Here we assess the impact of data accuracy using the alien plant programme in Table Mountain National Park, South Africa. A systematic plot-based survey method was carried out to assess the distribution of alien plants in the park at a fine scale (systematic sampling). Alien plant richness, total area invaded and the degree of spatial overlap in species' presence were compared between the systematic sample and a protected area (PA) managers' dataset (collated from collective observations by park visitors, rangers and managers) and Working for Water (WfW) project data (data collected for the planning and implementation of the alien plant clearing programme) using a range of confusion matrix-based statistics to assess similarity and error rates between the datasets. A total of 106 alien plant taxa were detected across the three datasets, 12 in PA manager's data, 23 in WfW data and 101 in the systematic survey. Overall, there was substantive disagreement between the datasets on the distribution of alien plants. For example both management datasets estimated species' hectare coverage at orders of magnitude greater than indicated by systematic sampling. The inaccuracy of manager data has direct negative implications for funding allocation, which currently appears to be in excess of what is required. We recommend that contrary to perception, fine-scale surveys are a cost-effective way to inform long-term monitoring programmes and improve programme effectiveness.

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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.