Abstract
ABSTRACTAsh dieback, caused by the ascomycete fungus Hymenoscyphus fraxineus, has been rapidly expanding across Europe during the last two decades, posing a considerable threat to native ash populations. In this study, we applied regression-based models trained by field data, in conjunction with geographic information systems, to produce spatial predictions of ash dieback severity and environmental suitability for the disease in Czech forests. A model of actual ash dieback severity relates disease extent to silvicultural and environmental characteristics of forest stands and their neighbourhood, while a model of environmental suitability for the disease quantifies the relative susceptibility of sites to the disease, independent of the current silvicultural characteristics. The final predictive maps suggested that fertile lowlands and humid areas bordering Poland and Slovakia were the most endangered regions. Areas at the lowest risk of damage were concentrated in dry areas and in highland and mountain areas in the western part of the country, usually with poor soils on acid bedrock. Predictions of actual disease severity are an effective tool for guiding the current management of infested stands whereas predicting environmental suitability is useful for making long-term strategic decisions, e.g. identifying areas where future ash regeneration and cultivation may be unsuccessful.
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