Likelihood of Extreme Early Flight of Myzus persicae (Hemiptera: Aphididae) Across the UK.

Myzus persicae (Sulzer, Hemiptera: Aphididae) is a major global crop pest; it is the primary aphid vector for many damaging viruses and has developed resistance to most insecticides. In temperate regions, the risk of widespread crop infection and yield loss is heightened following warm winters, which encourage rapid population growth and early flight. Estimates of the frequency and magnitude of warm winters are, therefore, helpful for understanding and managing this risk. However, it is difficult to quantify the statistical distribution of climate events, particularly extremes, because climate observations represent just a small sample of the possible climate variations in a region. The purpose of this study was to establish a large-scale relationship between temperature and M. persicae observations across the UK and apply this to a very large ensemble of climate model simulations, which better sample the variability in climate, to quantify the current likelihood of extreme early M. persicae flight across the UK. The timing of M. persicae flight was shown to be significantly related to January-February mean temperature, where a 1°C warmer/cooler temperature relates to about 12 d earlier/later flight. Climate model simulations predict 40% likelihood of experiencing a year with unprecedented early M. persicae flight during the next decade in the UK. Results from this method can help crop managers assess the long-term viability of crops and management practices across the UK and provide early warning information for targeting pest surveillance activities on the locations and timings at highest risk of early M. persicae flight.

A novel approach for exploring climatic factors limiting current pest distributions: A case study of Bemisia tabaci in north-west Europe and assessment of potential future establishment in the United Kingdom under climate change.

Bemisia tabaci (the tobacco whitefly) is an important agricultural pest of global significance primarily because of its ability to transmit multiple damaging plant viruses. To date, UK outbreaks of the whitefly have been restricted to glasshouses and there are no records of the whitefly establishing outdoors during the summer. This is despite the fact that annual degree-day models (that estimate accumulated warmth over the year above the development threshold), indicate that B. tabaci has the thermal potential for multiple summer generations in the UK. A set of 49 climate indices calculated using the present day climate (1986-2015) were therefore compared between the UK and the south of France, where B. tabaci is able to establish outdoors, to identify the factors limiting its establishment. The number of cold days and nights in summer, as well as the time spent within the whitefly's optimum temperature range, were most significantly different between the two areas. These indices may impact the development of B. tabaci and offer an explanation for the absence of the whitefly outdoors in the UK during the summer. Further analyses undertaken with climate projections suggest that in a 2-4°C warmer world this pest could pose a risk to outdoor UK crops in July and August. A clear south-north gradient can be demonstrated for these indices. Linking any possible northwards spread of B. tabaci populations outdoors in France with changes in these indices could therefore provide an important indicator of any change in the risks of outdoor populations of this species developing in the UK. The effectiveness of climate indices in pest risk analysis is compellingly demonstrated, and it is recommended that in-depth comparisons of climatic indices between areas of pest presence and absence are conducted in other situations where forecasting the risks of pest establishment are complex and challenging.

Variation in Inspection Efficacy by Member States of Wood Packaging Material Entering the European Union.

The use of wood packaging materials (WPMs) in international trade is recognized as a pathway for the movement of invasive pests and as the origin of most introductions of Asian longhorned beetle, Anoplophora glabripennis (Motschulsky) (Coleoptera: Cerambycidae) in Europe and North America. Following several pest interceptions on WPM associated with stone imports from China, the European Union (EU) agreed to survey certain categories of imports based on the EU Combined Nomenclature Codes for imports, which are based on the international Harmonized System. Between April 2013 and March 2015, 72,263 relevant consignments were received from China in the EU and 26,008 were inspected. Harmful organisms were detected in 0.9% of the consignments, and 1.1% of the imports did not have markings compliant with the international standard for treating WPM, ISPM 15. There were significant differences between the detection rates of harmful organisms among EU member states. In member states that inspected at least 500 consignments, the rate of detection ranged from 6.9% in Austria and France to 0.0% in Spain and Poland. If this difference in detection rate is the result of differences in the methods and intensity of inspection in different member states then an approximate sevenfold increase in the interception of harmful organisms may be achieved if all states were to achieve detection rates achieved by Austria and France. The EU data from 1999 to 2014 indicated an increasing number of interceptions of Bostrichidae and Cerambycidae since 2010. This study demonstrates that there is an ongoing threat of non-native forest pests being imported on WPM.

Prospects for the use of biological control agents against Anoplophora in Europe.

This review summarises the literature on the biological control of Anoplophora spp. (Coleoptera: Cerambycidae) and discusses its potential for use in Europe. Entomopathogenic fungi: Beauveria brongniartii Petch (Hypocreales: Cordycipitaceae) has already been developed into a commercial product in Japan, and fungal infection results in high mortality rates. Parasitic nematodes: Steinernema feltiae Filipjev (Rhabditida: Steinernematidae) and Steinernema carpocapsae Weiser have potential for use as biopesticides as an alternative to chemical treatments. Parasitoids: a parasitoid of Anoplophora chinensis Forster, Aprostocetus anoplophorae Delvare (Hymenoptera: Eulophidae), was discovered in Italy in 2002 and has been shown to be capable of parasitising up to 72% of A. chinensis eggs; some native European parasitoid species (e.g. Spathius erythrocephalus) also have potential to be used as biological control agents. Predators: two woodpecker (Piciformis: Picidae) species that are native to Europe, Dendrocopos major Beicki and Picus canus Gmelin, have been shown to be effective at controlling Anoplophora glabripennis Motschulsky in Chinese forests. The removal and destruction of infested and potentially infested trees is the main eradication strategy for Anoplophora spp. in Europe, but biological control agents could be used in the future to complement other management strategies, especially in locations where eradication is no longer possible.

Epitrix flea beetles: new threats to potato production in Europe.

Epitrix tuberis and E. cucumeris are major pests of potatoes in North America. E. tuberis causes the most serious damage because the larval feeding can cause superficial serpentine tunnelling on the surface of tubers as well as deeper pits. This damage can make crops unmarketable. By contrast, E. cucumeris mainly damages the foliage, and yield losses can occur when the adults reach high densities. In 2004, potato tuber damage characteristic of E. tuberis was seen in Portugal. In 2008, damage was more widespread and severe. E. cucumeris and a lesser known species, E. similaris, were recorded in affected fields. E. similaris has since been found across Galicia, Spain. E. similaris is thought to be the most likely cause of the tuber damage in Portugal, but it is possible that E. cucumeris or an as yet undetected Epitrix species is causing the damage. In 2010, a pest risk assessment for the Euro-Mediterranean area identified the movement of adults and pupae with seed or ware potatoes and associated soil as being the highest-risk pathways for the spread of Epitrix. In 2012, EU emergency measures were agreed to reduce the risk of further introductions and the rate of spread of these pests.

A suite of models to support the quantitative assessment of spread in pest risk analysis.

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.

Effects of the training dataset characteristics on the performance of nine species distribution models: application to Diabrotica virgifera virgifera.

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.