Improved prediction of the climate-driven outbreaks of Dendrolimus pini in Pinus sylvestris forests

Dendrolimus pini L. is a common and widespread moth in Europe, where severe outbreaks can defoliate Pinus sylvestris L. stands. Outbreaks are thought to be climate driven and may become more frequent and widespread with climate warming. The recent discovery of breeding populations of the moth in P. sylvestris plantations in Scotland has highlighted the importance of predicting outbreaks both within the core areas and at the margins of its current range. In this investigation, we used published data of damaging outbreaks plus historical climate data from Germany to build a relationship between climate conditions and outbreaks, and to develop a prediction model. Our analytical approach used principal component analysis and decision-tree data mining. German historical outbreaks showed relationships with climate variables, and provided evidence for a new damaging outbreak prediction model. The model uses the Seljaninov hydrothermal coefficient and decision-tree models on climate observations to predict where and when outbreaks may occur. The model was applied to European observed climate data and two climate projections using a GIS. In Europe, the model predicted future outbreaks in the Baltic States, Scandinavia, Russia and Scotland. In Scotland, more detailed analysis with probabilistic climate change projections showed an increasing risk of outbreaks through the twenty-first century.