Long-term studies of insect populations in the North American boreal forest have shown the vital importance of long-distance dispersal to the maintenance and expansion of insect outbreaks. In this work, we extend several concepts established previously in an empirically-based dispersal flight model with recent work on the physiology and behavior of the adult eastern spruce budworm (SBW) moth, Choristoneura fumiferana (Clemens). An outbreak of defoliating SBW in Quebec, ongoing since the mid-2000s, already covers millions of hectares of forests in eastern Canada and threatens to spread into neighboring areas through annual summertime episodes of long-distance dispersal. Such flight events in favorable conditions frequently include billions of SBW moths dispersing in the warm atmospheric boundary layer, typically starting around sunset and often lasting through several hours of wind-driven transport over hundreds of kilometers. Successful SBW dispersal to possibly distant host forest areas depends acutely on the weather. Here we describe the components and results of SBW–pyATM, an open-source individual-based modeling framework developed in Python for the simulation of these weather-driven SBW dispersal events. Using seasonal SBW phenology results from BioSIM at known outbreak locations and high-resolution Weather Research and Forecasting (WRF) model output, we focus on modeling dispersal flights over two successive nights in July 2013 in southern Quebec. Our flight model closely reproduces the SBW spatial patterns and motions observed by weather surveillance radar over the St. Lawrence estuary. With SBW–pyATM we can estimate landing locations for both male and female SBW and the resulting spatial patterns of egg distribution, allowing us eventually to forecast future larval defoliation activity in new locations where immigration could help overcome local limitations on SBW populations. This information could then support forest management decisions where SBW outbreaks threaten valuable resources.

对北美北方森林昆虫种群的长期研究表明，远距离传播对昆虫爆发的维持和扩大至关重要。在这项工作中，我们扩展了先前在基于经验的扩散飞行模型中建立的几个概念，以及最近关于成年东部云杉 budworm (SBW) 蛾Choristoneura fumiferana的生理学和行为的研究。（克莱门斯）。自 2000 年代中期以来，魁北克省爆发的落叶 SBW 已经覆盖了加拿大东部数百万公顷的森林，并有可能通过每年夏季的长距离传播事件蔓延到邻近地区。在有利条件下的此类飞行事件通常包括数十亿只 SBW 飞蛾散布在温暖的大气边界层中，通常在日落前后开始，通常持续数百公里的风驱动运输几个小时。SBW 能否成功散布到可能很远的寄主森林地区，很大程度上取决于天气。在这里，我们描述了 SBW-pyATM 的组件和结果，这是一个用 Python 开发的基于个体的开源建模框架，用于模拟这些天气驱动的 SBW 扩散事件。利用 BioSIM 在已知爆发地点的季节性 SBW 物候结果和高分辨率天气研究和预报 (WRF) 模型输出，我们专注于模拟 2013 年 7 月在魁北克南部连续两个晚上的扩散飞行。我们的飞行模型密切再现了天气监视雷达在圣劳伦斯河口上空观测到的 SBW 空间模式和运动。使用 SBW-pyATM，我们可以估计雄性和雌性 SBW 的着陆位置以及由此产生的卵子分布的空间模式，最终使我们能够预测未来新地点的幼虫落叶活动，移民可以帮助克服当地对 SBW 种群的限制。然后，这些信息可以支持 SBW 爆发威胁宝贵资源的森林管理决策。