The number of alien species arriving within new regions has increased at unprecedented rates. Managing the pathways through which alien species arrive and spread is important to reduce the threat of biological invasions. Harmonising information on pathways across individual sectors and user groups is therefore critical to underpin policy and action. The European Alien Species Information Network (EASIN) has been developed to easily facilitate open access to data of alien species in Europe. The Convention on Biological Diversity (CBD) Pathway Classification framework has become a global standard for the classification of pathways. We followed a structured approach to assign pathway information within EASIN for a subset of alien species in Europe, which covered 4169 species, spanning taxonomic groups and environments. We document constraints and challenges associated with implementing the CBD Pathway Classification framework and propose potential amendments to increase clarity. This study is unique in the scope of taxonomic coverage and also in the inclusion of primary (independent introductions to Europe) and secondary (means of dispersal for species expansion within Europe, after their initial introduction) modes of introduction. In addition, we summarise the patterns of introduction pathways within this subset of alien species within the context of Europe. Based on the analyses, we confirm that the CBD Pathway Classification framework offers a robust, hierarchical system suitable for the classification of alien species introduction and spread across a wide range of taxonomic groups and environments. However, simple modifications could improve interpretation of the pathway categories ensuring consistent application across databases and information systems at local, national, regional, continental and global scales. Improving consistency would also help in the development of pathway action plans, as required by EU legislation.

Standardized tools are needed to identify and prioritize the most harmful non-native species (NNS). A plethora of assessment protocols have been developed to evaluate the current and potential impacts of non-native species, but consistency among them has received limited attention. To estimate the consistency across impact assessment protocols, 89 specialists in biological invasions used 11 protocols to screen 57 NNS (2614 assessments). We tested if the consistency in the impact scoring across assessors, quantified as the coefficient of variation (CV), was dependent on the characteristics of the protocol, the taxonomic group and the expertise of the assessor. Mean CV across assessors was 40%, with a maximum of 223%. CV was lower for protocols with a low number of score levels, which demanded high levels of expertise, and when the assessors had greater expertise on the assessed species. The similarity among protocols with respect to the final scores was higher when the protocols considered the same impact types. We conclude that all protocols led to considerable inconsistency among assessors. In order to improve consistency, we highlight the importance of selecting assessors with high expertise, providing clear guidelines and adequate training but also deriving final decisions collaboratively by consensus.

In this contribution, new data concerning the distribution of vascular flora alien to Italy are presented. It includes new records, confirmations, exclusions, and status changes for Italy or for Italian administrative regions of taxa in the generaAcalypha,Acer,Canna,Cardamine,Cedrus,Chlorophytum,Citrus,Cyperus,Epilobium,Eucalyptus,Euphorbia,Gamochaeta,Hesperocyparis,Heteranthera,Lemna,Ligustrum,Lycium,Nassella,Nothoscordum,Oenothera,Osteospermum,Paspalum,Pontederia,Romulea,Rudbeckia,Salvia,Sesbania,Setaria,Sicyos,Styphnolobium,Symphyotrichum, andTradescantia. Nomenclature and distribution updates, published elsewhere, and corrigenda are provided as supplementary material.

Early detection and rapid response are essential to deal effectively with new introductions of invasive alien species (IAS). Citizen science platforms for opportunistic recording of species are increasingly popular, and there is potential to harvest their data for early detection of IAS, but this has not been tested. We evaluated the potential of data from existing citizen science platforms for early detection of IAS by obtaining 687 first records of species from 30 European countries where there was both an official first record (i.e. published in scientific literature or by a government agency) and a record in a citizen science platform. We tested how the difference between the two (time lag) was related to species traits, popularity in citizen science platforms, public and research attention and regulatory status. We found that for 50% of the time lag records, citizen science platforms reported IAS earlier than or in the same year as the official databases. Although we cannot determine causality (the first official record could have been from a citizen science platform, or contemporaneous with it), this demonstrates that citizen science platforms are effective for IAS early detection. Time lags were largely affected by species traits. Compared with official records, vertebrates were more likely to have earlier records on citizen science platforms, than plants or invertebrates. Greater popularity of the IAS in citizen science platforms and its observation in neighbouring countries resulted in earlier citizen science reporting. In contrast, inclusion in the EU priority list resulted in earlier official recording, reflecting the efficacy of targeted surveillance programmes. However, time lags were not affected by the overall activity of citizen platforms per country. Synthesis and applications. Multi‐species citizen science platforms for reporting nature sightings are a valuable source of information on early detection of IAS even though they are not specifically designed for this purpose. We recommend that IAS surveillance programmes should be better connected with citizen science platforms, including greater acknowledgement of the role of citizen scientists and better data flow from smaller citizen science initiatives into global databases, to support efficient early detection. Read the free Plain Language Summary for this article on the Journal blog.