Space matters when defining effective management for invasive plants.

Aim Invasive alien species are a threat to biodiversity and can harm resident plants, animals, humans and infrastructure. To reduce deleterious effects, effective management planning for invasive plants is required. Currently, the effectiveness of management is primarily optimized locally through eradication of individual populations. By contrast, spatial prioritization of control activities at the landscape level has received less attention, despite its potential to improve management planning in complex landscapes, especially under budget constraints. Location North-eastern Switzerland, Europe. Methods We used a dynamic simulation model to evaluate the effectiveness of spatially designed management planning for controlling the expansion of three invasive alien plants ( IAPs; Heracleum mantegazzianum, Impatiens glandulifera and Reynoutria japonica) across a heterogeneous landscape in North-eastern Switzerland. The model predicted the spread of IAPs from their current distribution under constraints of 361 control options differing in local intensity, frequency, duration, area and spatial prioritization of eradication measures. Results Our results demonstrate that IAP-control actions under a restricted budget are more effective if control actions are spatially prioritized. Most effective spatial treatments generally prioritized small populations in the case of the annual species and large populations in the case of the perennial species. Further, applying intensive control at early stages generally increased effectiveness of control. Main conclusions For IAP-management planning, our findings suggest that control should be applied early when IAPs start spreading, to maximize success or minimize costs. Further, spatial prioritization schemes are particularly useful under limited financial means for IAP-management. Finally, our modelling approach may serve as a proof of concept to evaluate the effectiveness of control actions of various IAPs in complex landscapes. [ABSTRACT FROM AUTHOR]