Hotspots for Plant Pests Introduction and quantitative pest risk assessment: HoPPI Project Final Report

Abstract Despite national and international efforts to prevent non‐indigenous species’ introductions, the spread of transboundary plant pests has increased dramatically in recent years, and it seems inevitable that many more species will enter the EU in the future. Identifying plant pests’ entry points may offer some early insights to prevent new plant pest invasions and support the surveillance activities carried out in the EU territory. This document was prepared in the context of the EFSA grant GP/EFSA/ENCO/2020/02 and represents the final report of the “HoPPI: Hotspots for plant pests introduction” project. The main objectives of the project were to: i) make an inventory of the pests introduced in the EU in the last two decades; ii) identify hotspots of pests introduction in the EU; iii) identify and analyse the factors that determine their occurrence; iv) understand the role of world trade in affecting risk of introduction using network analysis; v) develop a tool for standardising the pathway model used for the entry step of the quantitative pest risk assessments carried out by EFSA. To meet Objective i, a dataset containing a comprehensive list of pests’ first introduction records in the EU between 1999 and 2019, was compiled. The final database includes 278 pest species introduced in the EU, as well as detailed information on the specific species, their origin, and the pathways through which they might have entered the EU. The identification of hotspots and factors in Objective ii and iii was performed using two different methodologies, Getis G* and a Bayesian hierarchical spatial model, that pinpointed specific regions within the EU that are particularly vulnerable to plant pest introductions, uncovering environmental, climatic, and anthropogenic factors contributing to the introduction of pests in specific regions. The application of network analysis in Objective iv sheds light on the intricate connections between international trade routes and the introduction of plant pests into the EU. The results highlight key pathways and trade networks that pose a higher risk of facilitating pest entry. In pursuit of Objective v, an R package named “qPRAentry” was developed.