New modeling approaches to improve the surveillance of long-distance human-mediated spread of invasive pests

Long-distance, human-mediated spread is a key contributor to the expansion of invasive insect populations in North America. We present two modeling approaches which address the problem of balancing the allocation of pest surveillance resources against the capacity to account for low-probability cases of long-distance pest incursions. The first methodology presented in this study provides a way to ensure the geographical diversification of pest surveillance activities, while also enabling decision-makers to explore the trade-offs between the degree of diversification, the desired level of pest survey performance, and tolerated levels of uncertainty. The second approach is based on the maximum expected coverage problem concept and generates economically optimal allocations of surveillance activities by maximizing the coverage of the species' potential origin locations, as well as the likelihood that the surveillance scheme covers a subset of infested locations deemed high-risk. We demonstrate these new approaches by analyzing pathways of the spread of the emerald ash borer (Agrilus planipennis Fairmaire), a major pest of ash trees in North America, with infested firewood that may be carried by visitors to campground facilities in central Canada and the U.S. Midwest. Overall, the new methodologies offer workable strategies for dealing with the typical uncertainty about the human-mediated long-distance spread of invasive forest pests, and make the geographical allocation of pest surveillance activities less subject to possible errors in the long-distance spread estimates.