This chapter highlights quantitative methods designed to identify and rank exotic species with potential risk to cause economic and/or environmental harm if they establish in a new area. Until now, pest risk assessments have tended to be qualitative and reactive instead of quantitative and proactive. Here, a computational-intelligence technique called a self-organizing map (SOM) is described that can be used to analyse regional profiles or assemblages of pest species to determine their potential for establishment in new regions. In addition to the SOM, two other useful clustering or classification algorithms, k-means and hierarchical analysis, are also demonstrated to provide a quantitative framework to the risk assessment process. The examples described for each method illustrate how a pest risk analyst can identify, from a large list of potential hazards, which species present the most risk to target areas. Furthermore, examples are given of how such analyses may indicate donor and recipient regions for pest invasion and can highlight previously unknown or ignored threats for further investigation. Finally, cautions are provided and limitations of SOMs and other clustering methods applied to the area of pest risk assessment are discussed.

This report considers the prospects for increasing the use of quantitative models for plant pest spread and dispersal in EFSA Plant Health risk assessments. The agreed major aims were to provide an overview of current modelling approaches and their strengths and weaknesses for risk assessment, and to develop and test a system for risk assessors to select appropriate models for application. First, we conducted an extensive literature review, based on protocols developed for systematic reviews. The review located 468 models for plant pest spread and dispersal and these were entered into a searchable and secure Electronic Model Inventory database. A cluster analysis on how these models were formulated allowed us to identify eight distinct major modelling strategies that were differentiated by the types of pests they were used for and the ways in which they were parameterised and analysed. These strategies varied in their strengths and weaknesses, meaning that no single approach was the most useful for all elements of risk assessment. Therefore we developed a Decision Support Scheme (DSS) to guide model selection. The DSS identifies the most appropriate strategies by weighing up the goals of risk assessment and constraints imposed by lack of data or expertise. Searching and filtering the Electronic Model Inventory then allows the assessor to locate specific models within those strategies that can be applied. This DSS was tested in seven case studies covering a range of risk assessment scenarios, pest types and dispersal mechanisms. These demonstrate the effectiveness of the DSS for selecting models that can be applied to contribute to EFSA Plant Health risk assessments. Therefore, quantitative spread and dispersal modelling has potential to improve current risk assessment protocols and contribute to reducing the serious impacts of plant pests in Europe.

A risk analysis framework comprised of assessment, response and communication elements is discussed in the context of forest pest management in Canada. Despite many shared pests and common issues in resource management, capacity in forest pest management varies greatly by jurisdictions depending on historical, socio-economic and cultural expectations. Research and operational expertise is separated among jurisdictions as is responsibility for native and alien pests. A risk analysis framework provides a structure for the development of common evidence-based analysis, harmonized responses and best practices. Two case studies: mountain pine beetle, a native insect, and gypsy moth, an alien invasive insect, are presented to illustrate the process.

As part of an ecological risk assessment, Roundup Ready 2 Yield® soybean (MON 89788) was compared to a conventional control soybean variety, A3244, for disease and arthropod damage, plant response to abiotic stress and cold, effects on succeeding plant growth (allelopathic effects), plant response to a bacterial symbiont, and effects on the ability of seed to survive and volunteer in a subsequent growing season. Statistically significant differences between MON 89788 and A3244 were considered in the context of the genetic variation known to occur in soybean and were assessed for their potential impact on plant pest (weed) potential and adverse environmental impact. The results of these studies revealed no effects of the genetic modification that would result in increased pest potential or adverse environmental impact of MON 89788 compared with A3244. This paper illustrates how such characterization studies conducted in a range of environments where the crop is grown are used in an ecological risk assessment of the genetically modified (GM) crop. Furthermore, risk assessors and decision makers use this information when deciding whether to approve a GM crop for cultivation in—or grain import into—their country.

International audience | The estimation of rates and patterns of spread is one of the key steps in a pest risk assessment. Pest risk analysts across the world wish to make quantitative, scientifically defensible assessments of likely spread by invasive alien species. However, data and time to develop detailed models for pest invasions are usually lacking and the resources to test those models in practice are not available. Therefore, generic and simple models are needed. A generic spread module composed of four models has been developed to assess the spread of plant pests. Four different models were developed to represent differences in objectives, available data and assumptions underlying the assessment of spread. The most complex of the models simulates spread in time and space and has four biological parameters, representing population growth and dispersal. The simplest of the models has only one parameter and considers only geographic range expansion. A third model assumes logistic growth of invaded area and a fourth model assumes logistic growth of population density in invaded cells. All models consider climatic suitability and presence of hosts. Consideration of economic value is optional. This chapter describes concepts and application of these models. They are illustrated by case studies for western corn rootworm, Diabrotica virgifera virgifera, in Europe.

The estimation of rates and patterns of spread is one of the key steps in a pest risk assessment. Pest risk analysts across the world wish to make quantitative, scientifically defensible assessments of likely spread by invasive alien species. However, data and time to develop detailed models for pest invasions are usually lacking and the resources to test those models in practice are not available. Therefore, generic and simple models are needed. A generic spread module composed of four models has been developed to assess the spread of plant pests. Four different models were developed to represent differences in objectives, available data and assumptions underlying the assessment of spread. The most complex of the models simulates spread in time and space and has four biological parameters, representing population growth and dispersal. The simplest of the models has only one parameter and considers only geographic range expansion. A third model assumes logistic growth of invaded area and a fourth model assumes logistic growth of population density in invaded cells. All models consider climatic suitability and presence of hosts. Consideration of economic value is optional. This chapter describes concepts and application of these models. They are illustrated by case studies for western corn rootworm, Diabrotica virgifera virgifera, in Europe.

In pest risk assessment it is frequently necessary to make time-critical decisions regarding management of expanding pest populations. When an invasive pest outbreak is expanding rapidly, preemptive quarantine of areas that are under imminent threat of infestation is one of only a few available management tools that can be implemented quickly to help control the expansion. The preemptive quarantine of locations that surround an infested area also acts as a safeguard to counteract the risk of failed detections of the pest in field surveys. In this paper, we present a method that assesses the suitability of preemptive quarantine measures at the level of small geographical subdivisions (U.S. counties). The cost of a preemptive quarantine in a given county is weighed against the protective benefit of delaying the spread of an outbreak to other neighboring counties. We demonstrate the approach with a decision support model that estimates the suitability of preemptive quarantine across multiple counties that surround areas infested with the emerald ash borer (Agrilus planipennis Fairmaire (EAB), Coleoptera: Buprestidae), an emerging major threat to ash tree species (Fraxinus spp.) in North America. The model identifies the U.S. counties where the installation of preemptive quarantine would most effectively slow the spread of EAB populations and reduce risk to high-value areas.

International audience | Given expectations for a booming usage of thiamethoxam and increasing availability of the promising biological agent Serangium japonicum for the control of Bemisia tabaci in China, an evaluation of their compatibility is crucial for integrated pest management (IPM). This study examined the lethal and sublethal effects of thiamethoxam on S. japonicum through three exposure routes. An acute toxicity bioassay showed that LC50 values of thiamethoxam for S. japonicum through residue contact, egg-dip, and systemic treatment were 6.65, 4.37, and 2.43 mg Al L-1, respectively. The prey consumption of S. japonicum given different densities of B. tabaci eggs under control, discontinuous, egg-dip and systemic exposure scenarios showed a good fit to a Type II functional response. Predation of S. japonicum was most affected under systemic exposure, followed by egg-dip, and discontinuous, which was only slightly affected. In all cases tested, however, predators recovered their predation capacity rapidly, either after 24 h of exposure or 24 h after the end of exposure. Thiamethoxam was highly toxic to S. japonicum regardless of exposure routes. Sublethal effects of thiamethoxam applied systemically or foliar both impaired the biological control of S. japonicum on B. tabaci. Therefore, thiamethoxam should be used with caution in IPM of B. tabaci.

peer reviewed | The saddle gall midge, Haplodiplosis marginata (von Roser), is a European crop pest whose larvae feed on cereal stems. Severe damage has been observed in some countries since 2010, sometimes after several decades without reports, renewing the interest of agronomists and entomologists in this sporadic pest. This review first focuses on the environmental factors influencing the life cycle of this pest and the damage it causes, as larval feeding can induce severe yield losses in the case of heavy infestation. This article also discusses the history of H. marginata outbreaks and hypotheses about its enigmatic population dynamics. This review finally presents the methods currently available to develop strategies for its integrated management. Precise monitoring of H. marginata populations appears to be an essential key to manage this pest and to understand the criteria leading to an outbreak. | The saddle gall midge, Haplodiplosis marginata (von Roser): risk assessment and developing tools for integrated pest management.

Hormesis, a biphasic dose response whereby exposure to low doses of a stressor can stimulate biological processes, has been reported in many organisms, including pest insects when they are exposed to low doses of a pesticide. However, awareness of the hormesis phenomenon seems to be limited among bee researchers, in spite of the increased emphasis of late on pollinator toxicology and risk assessment. In this commentary, we show that there are several examples in the literature of substances that are toxic to bees at high doses but stimulatory at low doses. Appreciation of the hormetic dose response by bee researchers will improve our fundamental understanding of how bees respond to low doses of chemical stressors, and may be useful in pollinator risk assessment. © 2015 Society of Chemical Industry