LAUSR

Aquatic invasive species (AIS) cause significant ecological and economic damages around the world. A major spread mechanism for AIS is traffic of boaters transporting their watercraft from invaded to uninvaded waterbodies. To inhibit the spread of AIS, Canadian provinces and American states often set up watercraft inspection stations at roadsides, where potentially infested boats are screened for AIS and, if necessary, decontaminated. However, since budgets for AIS control are limited, watercraft inspection stations can only be operated at specific locations and daytimes. Though theoretical studies provide managers with general guidelines for AIS management, more specific results are needed to determine when and where watercraft inspections would be most effective. This is the subject of this paper. We show how linear integer programming techniques can be used to optimize watercraft inspection policies under budget constraints. We introduce our approach as a general framework and apply it to the prevention of the spread of zebra and quagga mussels (Dreissena spp.) to the Canadian province of British Columbia. We consider multiple scenarios and show how variations in budget constraints, propagule sources, and model uncertainty affect the optimal policy. Based on these results, we identify simple, generally applicable principles for optimal AIS management.