Hotspot mapping of pest introductions in the EU: A regional analysis of environmental, anthropogenic and spatial effects

Abstract

Plant pests may pose a significant threat to global agriculture, natural ecosystems and biodiversity, causing severe ecological and economic damage. Identifying regions more susceptible to pest introductions is crucial for developing effective prevention, early detection and outbreak response strategies. While historical data on pest introductions in the European Union (EU) exist, they are typically reported at the regional level. This broad aggregation has posed a challenge for accurate analysis in plant health research. This study addresses this gap by leveraging existing regional data to identify hotspots of pest introductions within the EU and the UK, through a Bayesian hierarchical spatial model. Specifically, we employed the Besag, York, and Mollié (BYM) model to identify higher risk regions (NUTS2) by incorporating covariates and spatial effects to consider information from neighbouring areas. The results showed a positive effect of annual average temperature, annual average precipitation, and human population density on the risk of pest introduction, highlighting the relevance of the spatial component. Our analysis pinpoints high-risk regions in southern Europe, particularly northern Italy. Additionally, the high human population density and documented pest introductions in the Netherlands contributed to its elevated risk. While limitations exist due to the regional nature of the data, this study represents a methodological advancement, demonstrating the effectiveness of spatial models and offering a robust framework for future studies using regional data. It also provides insights that can inform targeted prevention, early detection and preparedness strategies, ultimately contributing to safeguarding agriculture, natural ecosystems and biodiversity in the EU and UK.