Nationwide mapping of pine mistletoe hotspots for adaptive management: MaxEnt modelling in Polish forests

Abstract Pine mistletoe (Viscum album subsp. austriacum) is increasingly recognized as a significant threat to Scots pine (Pinus sylvestris L.) forests across Europe. However, the factors driving the spread of mistletoe and its colonization of pine forests remain poorly understood. In this study, we applied species distribution modelling using MaxEnt to estimate the potential distribution of pine mistletoe across Poland. The model incorporated bioclimatic, environmental, and forest structure variables, sourced from national Polish datasets and a comprehensive survey conducted in 403 forest districts representing 93.7% of all such districts in the country, allowing for high-resolution predictions of mistletoe habitat suitability. Area under the curve of the model was 0.811, whereas true skill statistic was 0.62. The results indicated that mean summer temperature (48.1% of contribution), species richness in the upper forest layer (18.6%), and potential evapotranspiration (8.4%) were the most influential variables shaping mistletoe distribution. Furthermore, the analysis identified a pronounced spatial correlation between mistletoe presence and major river valleys, suggesting that certain riparian zones may act as key dispersal corridors with frugivorous birds responsible for seed transport. While climatic conditions remain a dominant factor, nonclimatic elements such as stand composition and habitat characteristics also play a significant role in mistletoe spread. Our transferable approach is suitable for assessing and predicting the spread of mistletoe in other regions and ecological contexts. Our results provide insights into the factors controlling the current and potential spread of pine mistletoe in Scots pine stands, highlighting the combined role of climatic, environmental, and forest structure variables. The strength of the approach applied in this study lies in the availability of an extensive, nation-wide field dataset, which enabled robust modelling of mistletoe distribution and the identification of key areas with elevated infestation risk that are relevant for forest management.