[show abstract][hide abstract] ABSTRACT: Citation: Baker RHA, Eyre D, Brunel S (2013) Matching methods to produce maps for pest risk analysis to resources. In: Kriticos DJ, Venette RC (Eds) Advancing risk assessment models to address climate change, economics and uncertainty. Abstract Decision support systems (DSSs) for pest risk mapping are invaluable for guiding pest risk analysts seek-ing to add maps to pest risk analyses (PRAs). Maps can help identify the area of potential establishment, the area at highest risk and the endangered area for alien plant pests. However, the production of detailed pest risk maps may require considerable time and resources and it is important to match the methods em-ployed to the priority, time and detail required. In this paper, we apply PRATIQUE DSSs to Phytophthora austrocedrae, a pathogen of the Cupressaceae, Thaumetopoea pityocampa, the pine processionary moth, Drosophila suzukii, spotted wing Drosophila, and Thaumatotibia leucotreta, the false codling moth. We demonstrate that complex pest risk maps are not always a high priority and suggest that simple methods may be used to determine the geographic variation in relative risks posed by invasive alien species within an area of concern. Keywords Pest risk mapping, area of potential establishment, area at highest risk, endangered area, Phytophthora austrocedrae, Drosophila suzukii, Thaumatotibia leucotreta, Thaumetopoea pityocampa Copyright Richard H.A. Baker et al. This is an open access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. A peer-reviewed open-access journal NeoBiota
[show abstract][hide abstract] ABSTRACT: This paper describes a decision-support scheme (DSS) for mapping the area where economically important loss is likely to occur (the endangered area). It has been designed by the PRATIQUE project to help pest risk analysts address the numerous risk mapping challenges and decide on the most suitable methods to follow. The introduction to the DSS indicates the time and expertise that is needed, the data requirements and the situations when mapping the endangered areas is most useful. The DSS itself has four stages. In stage 1, the key factors that influence the endangered area are iden-tified, the data are assembled and, where appropriate, maps of the key factors are produced listing any significant assumptions. In stage 2, methods for combining these maps to identify the area of potential establishment and the area at highest risk from pest impacts are described, documenting any assumptions and combination rules utilised. When possible and appropriate, Stage 3 can then be followed to show whether economic loss will occur in the area at highest risk and to identify the endangered area. As required, Stage 4, described elsewhere, provides techniques for producing a dynamic picture of the invasion process using a suite of spread models. To illustrate how the DSS functions, a maize pest, Diabrotica virgifera virgifera, and a freshwater invasive alien plant, Eich-hornia crassipes, have been used as examples.
[show abstract][hide abstract] ABSTRACT: The assessment of the suitability of the climate for pest establishment is an important part of pest risk analysis (PRA). This paper describes the work undertaken by the EU 7th Framework project PRA-TIQUE (Enhancements of Pest Risk Analysis Techniques) to develop guidance for this component of PRA. Firstly, there is a guide to rating the suitability of the climate in the PRA area using qualita-tive methods. Secondly, a Decision-support scheme (DSS) has been created to assist analysts in deciding whether to map climatic suitability, and to guide the selection of the most appropriate method from the large number available. The process of selecting a climatic mapping method is based on a review of the pest's climatic responses and distribution. A spreadsheet provides a compar-ison of the potential problems that can arise, depending on the mapping method and on the amount and quality of available data. Diagrams are provided to help choose the location data category that best represents the possible biases in the known distribution of the pest. A second spreadsheet pro-vides general information on the differences and similarities of each method in terms of categories such as functionality, ease of use and quality assurance. A variety of data, tools and supporting docu-ments are available as appendices to the DSS. All of the tools and guides are freely available online.
[show abstract][hide abstract] ABSTRACT: A CLIMEX model for Diabrotica virgifera virgifera (western corn rootworm), was initially fitted to the known range of this pest in the USA and Mexico under rain-fed agricultural situations.When this model was projected into Europe, it became clear that soil moisture thresholds for irrigation differed markedly between Central Europe and the USA. A second model was fitted using soil moisture parameters derived from theoretical expectations, and was found to fit the known distribution of all North American locations well, and all the European distribution records perfectly. Globally, the modelled potential range of D. v. virgifera covers approximately 64% of the global area of maize production. The highest nascent biosecurity risks to maize-producing areas posed by the western
corn rootworm are China, Japan, Argentina, South Africa and Australia. Biosecurity agencies concerned with managing D. v. virgifera invasion risks to Asia should adopt a regional approach to the problem, attempting to slow its spread through Eurasia. The sensitivity of D. v. virgifera’s modelled potential distribution to the inclusion of irrigated sites in the model training dataset highlighted the importance of carefully exploring the implications of land-use factors that might be practised in different ways in the model training area and the area of concern.
[show abstract][hide abstract] 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.
PLoS ONE 01/2012; 7(10):e43366. · 3.73 Impact Factor
[show abstract][hide abstract] ABSTRACT: Host area, potential pest impact and probability of pest presence are frequently displayed on maps by pest risk assessors. These variables can be mapped separately, but it is also important to map combinations of these variables in order to define the area of potential establishment and the endan-gered area to assist decision-making processes. This paper presents different methods for combining maps, and discusses their advantages and disadvantages. Different methods are shown that can be used to combine maps depending on whether the individual maps were derived from continuous quantitative variables or from discrete variables. The authors suggest combining maps derived from continuous variables using simple mathematical equations in order to compute expected invaded areas and expected potential impacts. Maps derived from discrete variables (e.g. scores) can be com-bined using a risk matrix, but the results may be highly dependent on the chosen matrix. The practi-cal interest of these methods is illustrated in a case study on Diabrotica virgifera virgifera. The authors recommend combining the original continuous variables when such variables are available. The combination of categories defined from continuous variables led to a loss of information and may decrease the values of the maps. Risk matrices should be used only if the individual variables are discrete and if the underlying continuous variables are not available.
[show abstract][hide abstract] ABSTRACT: Many distribution models developed to predict the presence/absence of invasive alien species need to be fitted to a training dataset before practical use. The training dataset is characterized by the number of recorded presences/absences and by their geographical locations. The aim of this paper is to study the effect of the training dataset characteristics on model performance and to compare the relative importance of three factors influencing model predictive capability; size of training dataset, stage of the biological invasion, and choice of input variables. Nine models were assessed for their ability to predict the distribution of the western corn rootworm, Diabrotica virgifera virgifera, a major pest of corn in North America that has recently invaded Europe. Twenty-six training datasets of various sizes (from 10 to 428 presence records) corresponding to two different stages of invasion (1955 and 1980) and three sets of input bioclimatic variables (19 variables, six variables selected using information on insect biology, and three linear combinations of 19 variables derived from Principal Component Analysis) were considered. The models were fitted to each training dataset in turn and their performance was assessed using independent data from North America and Europe. The models were ranked according to the area under the Receiver Operating Characteristic curve and the likelihood ratio. Model performance was highly sensitive to the geographical area used for calibration; most of the models performed poorly when fitted to a restricted area corresponding to an early stage of the invasion. Our results also showed that Principal Component Analysis was useful in reducing the number of model input variables for the models that performed poorly with 19 input variables. DOMAIN, Environmental Distance, MAXENT, and Envelope Score were the most accurate models but all the models tested in this study led to a substantial rate of mis-classification.
PLoS ONE 01/2011; 6(6):e20957. · 3.73 Impact Factor
[show abstract][hide abstract] ABSTRACT: Summary 1. Western corn rootworm (WCR), one of the most important maize pests in North America, and increasingly important in central Europe, has been found in the south east of England. The pathway by which WCR arrived in the UK has not been identified although there appears to be a link with international air transport. 2. WCR is primarily a pest of continuous maize. Approximately 120,000 ha of maize are grown each year for silage, of which an estimated 20% is continuous. A much smaller area of maize is also grown for grain production, sweetcorn, and as game cover. A small proportion of larvae can develop to adults when fed on cereals such as wheat and barley but more research is required to determine how fecund (fertile) females developing from these alternative hosts would be. 3. As the UK climate warms conditions are becoming increasingly suitable for WCR to establish in a larger portion of the UK maize crop. By 2050, all of the UK maize crop is likely to be vulnerable. 4. Although WCR can establish in southern England under current climatic conditions, population densities are likely to remain low unless the area of continuous maize increases from its current level. 5. Experiences in central Europe, where the summers are significantly warmer and WCR has been present for over ten years, suggest that significant economic impacts, due to larvae feeding on roots causing yield losses and crop lodging, only occur after several years of continuous maize cropping. Crop rotation is the most effective means of controlling WCR and in regions where WCR has caused significant damage some European farmers are now switching to growing maize in rotation. 6. A range of alternative management options for control or eradication of WCR have been used in areas where the pest occurs. Of the three insecticides approved for use in the UK only chlorpyrifos (an organophosphate) has been shown to be effective against WCR. However, the use of this chemical is under review in the UK and its future availability cannot be assured. January 2007