Current approaches to risk assessment in bees do not take into account co-exposures from multiple stressors. The European Food Safety Authority (EFSA) is deploying resources and efforts to move towards a holistic risk assessment approach of multiple stressors in bees. This paper describes the general principles of pesticide risk assessment in bees, including recent developments at EFSA dealing with risk assessment of single and multiple pesticide residues and biological hazards. The EFSA Guidance Document on the risk assessment of plant protection products in bees highlights the need for the inclusion of an uncertainty analysis, other routes of exposures and multiple stressors such as chemical mixtures and biological agents. The EFSA risk assessment on the survival, spread and establishment of the small hive beetle, Aethina tumida, an invasive alien species, is provided with potential insights for other bee pests such as the Asian hornet, Vespa velutina. Furthermore, data gaps are identified at each step of the risk assessment, and recommendations are made for future research that could be supported under the framework of Horizon 2020. Finally, the recent work conducted at EFSA is presented, under the overarching MUST-B project ("EU efforts towards the development of a holistic approach for the risk assessment on MUltiple STressors in Bees") comprising a toolbox for harmonised data collection under field conditions and a mechanistic model to assess effects from pesticides and other stressors such as biological agents and beekeeping management practices, at the colony level and in a spatially complex landscape. Future perspectives at EFSA include the development of a data model to collate high quality data to calibrate and validate the model to be used as a regulatory tool. Finally, the evidence collected within the framework of MUST-B will support EFSA's activities on the development of a holistic approach to the risk assessment of multiple stressors in bees. In conclusion, EFSA calls for collaborative action at the EU level to establish a common and open access database to serve multiple purposes and different stakeholders.

The rational control of harmful organisms for plants (pests) forms the basis of the integrated pest management (IPM), and is fundamental for ensuring agricultural productivity while maintaining economic and environmental sustainability. The high level of complexity of the decision processes linked to IPM requires careful evaluations, both economic and environmental, considering benefits and costs associated with a management action. Plant protection models and other decision tools (DTs) have assumed a key role in supporting decision-making process in pest management. The advantages of using DTs in IPM are linked to their capacity to process and analyze complex information and to provide outputs supporting the decision-making process. Nowadays, several DTs have been developed, tackling different issues, and have been applied in different climatic conditions and agricultural contexts. However, their use in crop management is restricted to only certain areas and/or to a limited group of users. In this paper, we review the current state-of-the-art related to DTs for IPM, investigate the main modelling approaches used, and the different fields of application. We also identify key drivers influencing their adoption and provide a set of critical success factors to guide the development and facilitate the adoption of DTs in crop protection.

The Asian tiger mosquito (Aedes albopictus) is one of the most invasive disease vectors worldwide. The species is a competent vector of dengue, chikungunya, Zika viruses and other severe parasites and pathogens threatening human health. The capacity of this mosquito to colonize and establish in new areas (including temperate regions) is enhanced by its ability of producing diapausing eggs that survive relatively cold winters. The main drivers of population dynamics for this mosquito are water and air temperature and photoperiod. In this paper, we present a mechanistic model that predicts the potential distribution, abundance and activity of Asian tiger mosquito in Europe. The model includes a comprehensive description of: i) the individual life-history strategies, including diapause, ii) the influence of weather-driven individual physiological responses on population dynamics and iii) the density-dependent regulation of larval mortality rate. The model is calibrated using field data from several locations along an altitudinal gradient in the Italian Alps, which enabled accurate prediction of cold temperature effects on population abundance, including identification of conditions that prevent overwintering of the species. Model predictions are consistent with the most updated information on species' presence and absence. Predicted population abundance shows a clear south-north decreasing gradient. A similar yet less evident pattern in the activity of the species is also predicted. The model represents a valuable tool for the development of strategies aimed at the management of Ae. albopictus and for the implementation of effective control measures against vector-borne diseases in Europe.

The fall armyworm, Spodoptera frugiperda (J.E. Smith), is an invasive pest threatening crop production and food security worldwide. High concerns are linked to the potential establishment of the species in Europe. The high migratory capacity of S. frugiperda causes concerns about the potential impacts of transient populations invading new areas from suitable hotspots. In the present work, we developed and used a physiologically-based demographic model to quantitatively assess the risks of S. frugiperda in Europe. The risks were assessed considering a best-, a median-, and a worst-case scenario. The Mediterranean coastal areas of Southern Europe resulted particularly suitable for the establishment of the species, with suitable areas reaching even higher latitudes, in the worst-case scenario. In Europe, up to four generations per year were predicted. The predicted yearly average number of moths per trap per week (± standard deviation) was 5 (± 4), 17 (± 5), and 139 (± 22) in the best, median-, and worst-case assessment scenarios, respectively. Model results showed that Southern and Central Europe up to the 48th parallel north might be exposed to the risk of transient populations. Depending on the latitude and on the period of arrival of the propagule, 1–2 transient generations per year might be expected. The model can be used to define strategies for reducing the risks of establishment of the pest at the country level. Predictions on the dynamics and phenology of the pest can also be used to support its management at the local level.