Quarantine measures to prevent insect invasions tend to focus on well-known pests but a large proportion of the recent invaders were not known to cause significant damage in their native range, or were not even known to science before their introduction. A novel method is proposed to detect new potential pests of woody plants in their region of origin before they are introduced to a new continent. Since Asia is currently considered to be the main supplier of insect invaders to Europe, sentinel trees were planted in China during 2007-2011 as an early warning tool to identify the potential for additional Asian insect species to colonize European trees. Seedlings (1-1.5 m tall) of five broadleaved (Quercus petraea, Q. suber, Q. ilex, Fagus sylvatica, and Carpinus betulus) and two conifer species (Abies alba and Cupressus sempervirens) were planted in blocks of 100 seedlings at two widely separated sites (one in a nursery near Beijing and the other in a forest environment near Fuyang in eastern China), and then regularly surveyed for colonization by insects. A total of 104 insect species, mostly defoliators, were observed on these new hosts, and at least six species were capable of larval development. Although a number of the insects observed were probably incidental feeders, 38 species had more than five colonization events, mostly infesting Q. petraea, and could be considered as being capable of switching to European trees if introduced to Europe. Three years was shown to be an appropriate duration for the experiment, since the rate of colonization then tended to plateau. A majority of the identified species appeared to have switched from agricultural crops and fruit trees rather than from forest trees. Although these results are promising, the method is not appropriate for xylophagous pests and other groups developing on larger trees. Apart from the logistical problems, the identification to species level of the specimens collected was a major difficulty. This situation could be improved by the development of molecular databases.

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Here we consider 274 alien Coleoptera species belonging to 41 of the 137 beetle families in Europe (Cerambycidae, Curculionidae sensu lato, Chrysomelidae sensu lato and Coccinelidae are treated separately elsewhere). Among the families we consider as having invaded the European fauna, Acanthocnemidae and Ptilodactylidae represent new arrivals. Many species-rich families have surprisingly few aliens, whereas some relatively minor families such as Dermestidae, Nitidulidae and Anobiidae have a relatively high representation of alien species. Since the start of the 19th century, the number of coleopteran aliens introduced into Europe has continued to increase. Alien species colonizing Europe derive from a wide range of geographic regions as well as ecozones, but the most important source area is Asia. Th e countries with the largest number of alien species established are France, Germany and Italy. Th e majority have been introduced accidentally via international transport mechanisms. Th e most important route for importation is stored products and crops, followed by transport of wood, then horticultural and ornamental plants. Most alien species in these families are found within anthropogenic habitats in Europe. Th e introduction of invasive alien beetles in these families has had signifi cant economic impacts, particularly as pests of stored foodstuff s, as well as serious ecological impacts. For example, the buprestid species Agrilus planipennis, recently recorded in Russia, is an important potential economic threat which may also impact the biodiversity associated with ash trees.

Mapping species spatial distribution using spatial inference and prediction requires a lot of data. Occurrence data are generally not easily available from the literature and are very time-consuming to collect in the field. For that reason, we designed a survey to explore to which extent large-scale databases such as Google maps and Google street view could be used to derive valid occurrence data. We worked with the Pine Processionary Moth (PPM) Thaumetopoea pityocampa because the larvae of that moth build silk nests that are easily visible. The presence of the species at one location can therefore be inferred from visual records derived from the panoramic views available from Google street view. We designed a standardized procedure allowing evaluating the presence of the PPM on a sampling grid covering the landscape under study. The outputs were compared to field data. We investigated two landscapes using grids of different extent and mesh size. Data derived from Google street view were highly similar to field data in the large-scale analysis based on a square grid with a mesh of 16 km (96% of matching records). Using a 2 km mesh size led to a strong divergence between field and Google-derived data (46% of matching records). We conclude that Google database might provide useful occurrence data for mapping the distribution of species which presence can be visually evaluated such as the PPM. However, the accuracy of the output strongly depends on the spatial scales considered and on the sampling grid used. Other factors such as the coverage of Google street view network with regards to sampling grid size and the spatial distribution of host trees with regards to road network may also be determinant.

Longhorned beetles (Cerambycidae) are the most diverse group of predominantly wood‐feeding (xylophagous) insects on Earth. Larvae of most species feed within tissues of plants made up of large amounts of plant cell wall (PCW), which is notoriously difficult to digest. To efficiently access nutrients from their food source, cerambycid larvae have to deconstruct PCW polysaccharides – such as cellulose, hemicelluloses and pectin – requiring them to possess a diversity of plant cell wall degrading enzymes (PCWDEs) in their digestive tract. Genomic data for Cerambycidae are mostly limited to notorious forest pests and are lacking for most of the taxonomic groups. Consequently, our understanding of the distribution and evolution of cerambycid PCWDEs is quite limited. We addressed the numbers, kinds and evolution of cerambycid PCWDEs by surveying larval midgut transcriptomes from 23 species representing six of the eight recognized subfamilies of Cerambycidae and each with very diverse host types (i.e., gymnosperms, angiosperms, xylem, phloem, fresh or dead plant tissues). Using these data, we identified 340 new putative PCWDEs belonging to ten carbohydrate active enzyme families, including two gene families (GH7 and GH53) not previously reported from insects. The remarkably wide range of PCWDEs expressed by Cerambycidae should allow them to break down most PCW polysaccharides. Moreover, the observed distribution of PCWDEs encoded in cerambycid genomes agreed more with phylogenetic relationship of the species studied than with the taxonomic origin or quality of the host plant tissues.