No abstract

Pest Risk Analyses (PRAs) are conducted worldwide to decide whether and how exotic plant pests should be regulated to prevent invasion. There is an increasing demand for science-based risk mapping in PRA. Spread plays a key role in determining the potential distribution of pests, but there is no suitable spread modelling tool available for pest risk analysts. Existing models are species specific, biologically and technically complex, and data hungry. Here we present a set of four simple and generic spread models that can be parameterised with limited data. Simulations with these models generate maps of the potential expansion of an invasive species at continental scale. The models have one to three biological parameters. They differ in whether they treat spatial processes implicitly or explicitly, and in whether they consider pest density or pest presence/absence only. The four models represent four complementary perspectives on the process of invasion and, because they have different initial conditions, they can be considered as alternative scenarios. All models take into account habitat distribution and climate. We present an application of each of the four models to the western corn rootworm, Diabrotica virgifera virgifera, using historic data on its spread in Europe. Further tests as proof of concept were conducted with a broad range of taxa (insects, nematodes, plants, and plant pathogens). Pest risk analysts, the intended model users, found the model outputs to be generally credible and useful. The estimation of parameters from data requires insights into population dynamics theory, and this requires guidance. If used appropriately, these generic spread models provide a transparent and objective tool for evaluating the potential spread of pests in PRAs. Further work is needed to validate models, build familiarity in the user community and create a database of species parameters to help realize their potential in PRA practice.

Expanding international trade and increased transportation are heavily implicated in the growing threat posed by invasive pathogens to biodiversity and landscapes. With trees and woodland in the UK now facing threats from a number of disease systems, this paper looks to historical experience with the Dutch elm disease (DED) epidemic of the 1970s to see what can be learned about an outbreak and attempts to prevent, manage and control it. The paper draws on an interdisciplinary investigation into the history, biology and policy of the epidemic. It presents a reconstruction based on a spatial modelling exercise underpinned by archival research and interviews with individuals involved in the attempted management of the epidemic at the time. The paper explores what, if anything, might have been done to contain the outbreak and discusses the wider lessons for plant protection. Reading across to present-day biosecurity concerns, the paper looks at the current outbreak of ramorum blight in the UK and presents an analysis of the unfolding epidemiology and policy of this more recent, and potentially very serious, disease outbreak. The paper concludes by reflecting on the continuing contemporary relevance of the DED experience at an important juncture in the evolution of plant protection policy.

The application of pest risk analysis (PRA) decision‐support schemes, such as that used by the European and Mediterranean Plant Protection Organization (EPPO), generates many ratings for likelihood or magnitude of risk factors, each with an associated uncertainty. In accordance with the international standard ISPM 11 (FAO, 2004), questions have been devised to assess the key elements of pest risk in the four main sections of pest risk assessment: Entry, Establishment, Spread and Impact. After completing each section, risk assessors are required to give a summary rating and an uncertainty score for that section. The large number of question ratings and uncertainty scores make the task of summarizing each section and its uncertainty quite difficult. Two graphical tools have been developed to aid this task: the PRA Risk score and uncertainty visualizer (Visualizer) and the Rule‐based matrix model (RBMM). The Visualizer presents a case summary graph on a single page in such a way that the risk assessors and peer reviewers can see rating scores and uncertainties in a pictorial manner; the RBMM integrates all the individual questions in the assessment through a hierarchy of rules that attempt to mimic the logic used by the assessors and are arranged in the form of a flow chart to give an overall rating with an accompanying expression of uncertainty.