Clearing of invasive alien plants under different budget scenarios: using a simulation model to test efficiency

Clearing of invasive alien plants (IAPs) is a necessary but expensive exercise. Typically, insufficient resources are available to clear all areas simultaneously. Consequently areas need to be prioritized for clearing. The financial resources available determine the extent of the area which can be cleared, while the prioritization identifies the location of the areas to be cleared. We investigate the following questions: (1) How does a change in the budget impact on the efficiency of the clearing operations over time? (2) How does this differ for different sites? (3) Can we identify pattern which make it possible for managers to determine if their budget is sufficient to achieve a management goal (e. g. clearing 95% of the area of IAPs) in a given time? (4) Can we draw general rules about how the time needed of achieving a management goal is changing when increasing the budget? We use a spatio-temporal explicit simulation model (SPREADSIM) to simulate the spread of major woody IAPs over time, using a random prioritization strategy as a null model. This strategy requires no understanding or assumptions about the factors influencing spread; it is thus a reasonable baseline prioritization strategy. Our results confirm that a reduction of the budget increases the time needed to reach a management goal of 95% non-invaded areas and simultaneously increases the overall budget needed to achieve this goal. In addition, for each site, we can identify three values. Firstly, a lower critical limit of the budget, below which the IAP spread is only slowed down and management does not result in a reduction of the area invaded by IAPs, which is independent of the management goal. Secondly, the critical budget, at which we have a chance of more than 50% of achieving our management goal in a given time. Thirdly, an upper critical limit for the budget, above which no substantial change in the time needed to reach the management goal can be observed. For all our three sites, the upper critical limit'' is located at approximately 1.7 times the critical budget. The variability of the temporal trajectories of the area covered by IAPs for different simulations for the same input parameter and highly non-linear change in IAP cover over time indicate that an identification of the critical budget based on few years of IAP management is nearly impossible and that the use of simulation models is imperative. Nevertheless, the general pattern observed can be generalized to other prioritization strategies and provide important guidance for budget allocations.