The emergence of continental to global scale biodiversity data has led to growing understanding of patterns in species distributions, and the determinants of these distributions, at large spatial scales. However, identifying the specific mechanisms, including demographic processes, determining species distributions remains difficult, as large‐scale data are typically restricted to observations of only species presence. New remote automated approaches for collecting data, such as automated recording units (ARUs), provide a promising avenue towards direct measurement of demographic processes, such as reproduction, that cannot feasibly be measured at scale by traditional survey methods. In this study, we analyze data collected by ARUs from 452 survey points across an approximately 1500 km long study region to compare patterns in adult and juvenile distributions in great horned owl Bubo virginianus. We specifically examine whether habitat associated with successful reproduction is the same as that associated with adult presence. We postulated that congruence between these two distributions would suggest that all areas of the species' range contribute equally to maintenance of the population, whereas significant differences would suggest more specificity in the species' requirements for successful reproduction. We filtered adult and juvenile calls of the species for manual review using automated classification and constructed single season occupancy models to compare land cover and vegetation covariates which significantly predicted presence of each life stage. We found that habitat use by adults was significantly predicted by increasing amounts of forest cover, reduced forest basal area, and lower elevations; whereas juvenile presence was significantly predicted only by decreasing amounts of forest cover, a pattern opposite that of adults. These results show that presence of adult great horned owls is not a sufficient proxy for locations at which reproduction occurs, and also demonstrate a highly scalable workflow that could be used for similar analyses in other sound‐producing species.

中文翻译：

---

使用大型自动声学阵列评估模型鸟类栖息地利用和成功繁殖的预测因素


大陆到全球范围的生物多样性数据的出现使得人们对大空间范围内的物种分布模式以及这些分布的决定因素有了越来越多的了解。然而，确定具体机制（包括人口统计过程）、确定物种分布仍然很困难，因为大规模数据通常仅限于对物种存在的观察。用于收集数据的新远程自动化方法，例如自动记录单元（ARU），为直接测量人口统计过程（例如生殖）提供了一条有前途的途径，而传统调查方法无法大规模测量人口统计过程。在这项研究中，我们分析了 ARU 从大约 1500 公里长的研究区域的 452 个调查点收集的数据，以比较大角鸮 Bubo virginianus 的成年和幼年分布模式。我们特别检查与成功繁殖相关的栖息地是否与与成虫存在相关的栖息地相同。我们假设，这两种分布之间的一致性表明该物种分布范围的所有区域对种群的维持都有同等的贡献，而显着差异则表明该物种成功繁殖的要求更具特异性。我们使用自动分类过滤了该物种的成年和幼年叫声以进行人工审查，并构建了单季节占用模型来比较土地覆盖和植被协变量，这显着预测了每个生命阶段的存在。 我们发现，森林覆盖面积的增加、森林断面积的减少和海拔的降低可以显着预测成年人对栖息地的利用。而幼年的存在只能通过森林覆盖面积的减少来显着预测，这与成年的模式相反。这些结果表明，成年大角鸮的存在并不能充分代表繁殖发生的位置，并且还证明了高度可扩展的工作流程，可用于其他发声物种的类似分析。