Print PageThis paper presents a new methodology to estimate pathways of human-mediated spread of alien invasive pests with transportation and cross-border trade. We have developed a stochastic model of how these species may be moved with commodity flows through a network of major transportation corridors and border crossings in North America. The model is formulated as a Markovian pathway matrix, and offers the potential to analyze pathways from both existing and anticipated infestations, undertake reverse pathway analyses and works with a wide range of transportation, traffic and commodity flow data. We have also addressed the issue of epistemic uncertainty in model-based forecasts and estimated an integrated risk of pest’s long-distance introductions via an aggregation of two somewhat conflicting components: (1) the likelihood of the pest to be introduced at a new locale and (2) the level of epistemic uncertainty of that estimate. We use the stochastic dominance criteria to aggregate these components and order geographic locations by their integrated pest invasion risk.
The model has been applied to assess the pathways of human-assisted spread of emerald ash borer (EAB, Agrilus planipennis Fairmaire), an invasive forest pest that has been introduced into the U.S. Midwest and Ontario, Canada and is now spreading to new areas in North America. In our study we estimate the potential of EAB long-distance introductions with commercial transportation via the road network in Canada and U.S. The study makes use of a Transport Canada roadside survey data and a U.S. Freight Analysis framework database complemented with empirical observations of historical detection rates for EAB.
Results/Conclusions
Results show the tradeoffs between estimated rates of EAB transmission and the amount of epistemic uncertainty in model-based forecasts and help delineate major “crossroads” and U.S. border crossings where the movement of the pest with a commercial transportation is most likely to occur. Both, pathway-specific and location-specific risk estimates have identified the system of major expressways in Ontario and Quebec as the primary gateway of EAB spread through the Canadian landscape. Overall, the new modeling approach generates more accurate predictions of EAB long-distance spread events and can help design more effective pest surveillance and regulatory programs. Better prediction of long-distance introductions leads to a more accurate delineation of distant population nuclei and thus helps reduce the cost of monitoring and controlling the spread of the pest across large geographic regions.
