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Climate is a major limiting factor for insect distributions and it is expected that a changing climate will likely alter spatial patterns of pest outbreaks. The Australian plague locust (APL) Chortoicetes terminifera, is the most economically important locust species in Australia. Invasions cause large scale economic damage to agricultural crops and pastures. Understanding the regional-scale and long-term dynamics is a prerequisite to develop effective control and preventive management strategies. In this study, we used a 32-year locust survey database to uncover the relationship between historical bioclimatic variables and spatial seasonal outbreaks by developing two machine learning species distribution models (SDMs), random forest and boosted regression trees. The explanatory variables were ranked by contribution to the generated models. The bio-dimate models were then projected into a future climate change scenario (RCP8.5) using downscaled 34 global climate models (GCMs) to assess how climate change may alter APL seasonal distribution patterns in eastern Australia. Our results show that the model for the distribution of spring outbreaks performed better than those for summer and autumn, based on statistical evaluation criteria. The spatial models of seasonal outbreaks indicate that the areas subject to APL outbreaks were likely to decrease in all seasons. Multi-GCM ensemble means show the largest decrease in area was for spring outbreaks, reduced by 93-94% by 2071-2090, while the area of summer outbreaks decreased by 78-90%, and 67-74% for autumn outbreaks. The bioclimatic variables could explain 78-98% outbreak areas change. This study represents an important step toward the assessment of the effects of the changing climate on locust outbreaks and can help inform future priorities for regional mitigation efforts in the context of global climate change in eastern Australia. (C) 2019 Elsevier B.V. All rights reserved.