Assessing the potential distribution of insect pests: case studies on large pine weevil (Hylobius abietis L) and horse‐chestnut leaf miner (Cameraria ohridella) under present and future climate conditions in European forests

Abstract

Forest insect pests represent a serious threat to European forests and their negative effects could be exacerbated by climate change. This paper illustrates how species distribution modelling integrated with host tree species distribution data can be used to assess forest vulnerability to this threat. Two case studies are used: large pine weevil (Hylobius abietis L) and horse‐chestnut leaf miner (Cameraria ohridella Deschka & Dimič) both at pan‐European level. The proposed approach integrates information from different sources. Occurrence data of insect pests were collected from the Global Biodiversity Information Facility (GBIF), climatic variables for present climate and future scenarios were sourced, respectively, from WorldClim and from the Research Program on Climate Change, Agriculture and Food Security (CCAFS), and distributional data of host tree species were obtained from the European Forest Data Centre (EFDAC), within the Forest Information System for Europe (FISE). The potential habitat of the target pests was calculated using the machine learning algorithm of Maxent model. On the one hand, the results highlight the potential of species distribution modelling as a valuable tool for decision makers. On the other hand, they stress how this approach can be limited by poor pest data availability, emphasizing the need to establish a harmonised open European database of geo‐referenced insect pest distribution data.