Search

Early detection of hitchhiking pests requires the identification of strategic introduction points via transport. We propose a framework for achieving this in Europe using the Japanese beetle (Popillia japonica) as a case study. Human-mediated spread has been responsible for its introduction into several continents over the last century, including a recent introduction in continental Europe, where it is now listed as a priority pest. Furthermore, recent interceptions far from the infested area confirm the risk of unintentional transport within continental Europe. Here, we analysed how three modes of transport - air, rail and road - connect the infested area to the rest of Europe. We ranked all European regions from most to least reachable from the infested area. We identified border regions and distant major cities that are readily reachable and observed differences between modes. We propose a composite reachability index combining the three transport modes, which provides a valuable tool for designing a continental surveillance strategy and prioritising highly reachable regions, as demonstrated by recent interceptions. [ABSTRACT FROM AUTHOR]

The risk of introducing weeds to new areas through grain (cereals, oilseeds and pulses) intended for processing or consumption is typically considered less than that from seed or plants for planting. However, within the range of end uses for grain, weed risk varies significantly and should not be ignored. In this paper, we discuss pathway risk analysis as a framework to examine the association of weed seeds with grain commodities throughout the production process from field to final end use, and present inspection sampling data for grain crops commonly imported to Canada. In the field, weed seed contamination of grain crops is affected by factors such as country of origin, climate, biogeography and production and harvesting practices. As it moves toward export, grain is typically cleaned at a series of elevators and the effectiveness and degree of cleaning are influenced by grain size, shape and density as well as by grade requirements. In cases where different grain lots are blended, uncertainty may be introduced with respect to the species and numbers of weed seed contaminants. During transport and storage, accidental spills and cross-contamination among conveyances may occur. At the point of import to Canada, inspection sampling data show that grain shipments contain a variety of contaminants including seeds of regulated weeds and species that represent new introductions. However, grain cleaning and processing methods tailored to end use at destination also affect the presence and viability of weed seeds. For example, grains that are milled or crushed for human use present a lower risk of introducing weed seeds to new environments than grains that undergo minimal or no processing for livestock feed, or screenings that are produced as a by-product of grain cleaning. Pathway risk analysis allows each of these stages to be evaluated in order to characterize the overall risk of introducing weeds with particular commodities, and guide regulatory decisions about trade and plant health. [ABSTRACT FROM AUTHOR]

Quantitative models have several advantages compared to qualitative methods for pest risk assessments (PRA). Quantitative models do not require the definition of categorical ratings and can be used to compute numerical probabilities of entry and establishment, and to quantify spread and impact. These models are powerful tools, but they include several sources of uncertainty that need to be taken into account by risk assessors and communicated to decision makers. Uncertainty analysis (UA) and sensitivity analysis (SA) are useful for analyzing uncertainty in models used in PRA, and are becoming more popular. However, these techniques should be applied with caution because several factors may influence their results. In this paper, a brief overview of methods of UA and SA are given. As well, a series of practical rules are defined that can be followed by risk assessors to improve the reliability of UA and SA results. These rules are illustrated in a case study based on the infection model of Magarey et al. (2005) where the results of UA and SA are shown to be highly dependent on the assumptions made on the probability distribution of the model inputs. [ABSTRACT FROM AUTHOR]