1. A key problem facing invasive species management is how best to allocate surveillance and control effort. Models of the establishment and spread of invasive species are widely used to predict species’ occurrence across space and inform resource prioritization. However, the way they should be used to direct control effort is less clear. Managers could exhaustively search and treat the few highest priority locations or apply less thorough effort more broadly. The choice between these options is a question of balancing resources to maximize local success while minimizing further spread.
2. We link a spatial model predicting the likelihood of occurrence with a decision model to efficiently allocate human resources to control the weed Salix cinerea in south-eastern Australia. Using data collected during an ongoing control programme, we construct a species distribution model, empirically estimate control effectiveness and perform a budget-constrained optimization that identifies priority regions for control.
3. Two alternative scenarios were explored against two seasonal budgets: control is equally valued in all areas or control is doubly valuable in conservation areas.
4. Optimal control effort per site varied according to the likelihood of occurrence and site-specific benefits of control. Prioritizing conservation areas led to a reduction in area treated because of greater allocation of control effort.
5. Quantifying control effectiveness was critical for realistically allocating control effort. Targeting obvious individuals and then moving to new sites was more cost-effective than attempting to control every individual at a high-priority site.
6. Synthesis and applications. We have developed a method to identify priority locations for invasive species control across a landscape. By integrating a decision model with an empirical distribution model, our method offers a better management outcome by maximizing the efficiency of control efforts. It identifies where and how much control effort should be allocated for maximum effect within a season. Effort is expressed as control staff time spent per site with the allocation readily visualized as a map. In general, a strategy of visiting sites where the species is most likely to occur and exerting a moderate amount of effort at these sites is most efficient.