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Abstract

Understanding the ecology of forest insect pests is challenging due to the complexity of population dynamics and species-interactions driven by environmental variability. Previous studies often focus on a single response in one species or a single set of environmental variables, neglecting species interactions and interacting mechanisms. However, understanding how environmental variability impacts forest pests is crucial for forest health managers to assess risks and adapt management plans. In this study, we examine the impacts of environmental heterogeneity on host-pathogen dynamics, range, and outbreak severity in Douglas-fir tussock moth (Orgyia pseudotsugata), an important forest pest. We also explore the projected effects of climate change on range and population dynamics of this pest insect. The Douglas-fir tussock moth inhabits a large geographic range in Western North America and feeds on different host trees throughout this range, making this an ideal study system for studying the impacts of environmental variation. The insect experiences cyclical high population density outbreaks, primarily terminated by high infection rates from a species-specific baculovirus (OpNPV), which has two morphotypes that vary in frequency across the tussock moth’s range. To study the impact of environmental variability on host-pathogen eco-evolutionary dynamics, we use a line search routine to fit a spatial two-pathogen model, parameterized by field experiments, to observational data on morphotype frequency. We demonstrate that population cycles and environmental variation, through a selection mosaic, are mechanisms supporting pathogen variation in this system. Additionally, we observe geographic variability in the outbreak severity of the Douglas-fir tussock moth, with some regions of the range experiencing high-severity outbreaks and significant defoliation, while others experience less severe outbreaks. To estimate the impact of weather and habitat variability on the range and outbreak severity of the Douglas-fir tussock moth, and make projections under climate change, we fit two Random Forest models to two extensive datasets collected by forest managers. The range model effectively captures the effects of contemporary climate change, identifying areas where Douglas-fir tussock moth populations may currently be undocumented. The outbreak severity model captures variation in population density due to habitat and weather variability. By combining the outbreak severity and range models with a climate change scenario from CMIP6, we projected future distributions and high-density outbreak locations for the Douglas-fir tussock moth. Our projections indicate a significant expansion in range and increased outbreak severity under worsening climate change. These findings have important implications for forest health and biodiversity, as increased defoliation due to the Douglas-fir tussock moth outbreaks damages forests and could exacerbate climate change by releasing sequestered carbon and undermining reforestation efforts.

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