Documenting and interpreting trends in the abundance and distribution of bird populations is critical to monitoring their status and setting conservation priorities. This process requires standardized monitoring and robust analytical techniques, which can resolve trends at spatial scales of management interest while disentangling the influence that various data collection protocols can have on the interpretation of results. We used a 19-year citizen-science-collected dataset (2001–2019), the Nocturnal Owl Survey, to assess abundance trends in Barred Owl (Strix varia), Northern Saw-whet Owl (Aegolius acadicus), and Great Horned Owl (Bubo virginianus) at both fine and broad-scales. To achieve this, we used a spatially explicit modeling approach that facilitates the borrowing of information across spatial boundaries, allowing for more robust trend estimates at finer spatial scales. Further, we assessed the potential influence of the call-playback protocol on trend estimates. At fine spatial scales, we found that a data collection protocol that includes call playbacks provided more precise results to assess relative changes in abundance (i.e., reduced uncertainty). At broader spatial scales, trend estimates were unaffected by data collection methodology (i.e., silent listening versus call playback). Specifically, at the scale of the region or province, we found that populations of focal owl species in the Maritimes of Canada have remained stable over the past 19 years. However, at finer scales, trends are more variable and may create opportunities to test alternative hypotheses about drivers of population change and the effects of management actions at scales amenable to conservation action. The statistical analyses are anticipated to form a national, publicly accessible framework for status assessments of owls in Canada and will provide resource managers and researchers a base from which to evaluate the influence of land management and conservation practices on owl populations across the nation.

中文翻译：

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加拿大沿海省份猫头鹰的空间显式种群趋势估计和呼叫回放的影响

记录和解释鸟类种群数量和分布的趋势对于监测其状况和确定保护重点至关重要。这个过程需要标准化的监测和强大的分析技术，这可以解决管理利益空间尺度的趋势，同时消除各种数据收集协议对结果解释的影响。我们使用了 19 年公民科学收集的数据集（2001-2019 年），即夜间猫头鹰调查，来评估斑鸮（Strix varia）、北锯齿鸮（Aegolius acadicus）和大角鸮（ Bubo virginianus）在精细和广泛的范围内。为了实现这一点，我们使用了一种空间显式建模方法，该方法有助于跨空间边界借用信息，允许在更精细的空间尺度上进行更稳健的趋势估计。此外，我们评估了呼叫回放协议对趋势估计的潜在影响。在精细的空间尺度上，我们发现包含呼叫回放的数据收集协议提供了更精确的结果来评估丰度的相对变化（即减少的不确定性）。在更广泛的空间尺度上，趋势估计不受数据收集方法（即静听与通话回放）的影响。具体而言，在地区或省的范围内，我们发现加拿大沿海地区的重点猫头鹰物种的种群在过去 19 年中保持稳定。然而，在更精细的尺度上，趋势更加多变，并可能创造机会来检验关于人口变化驱动因素的替代假设以及在保护行动范围内管理行动的影响。统计分析预计将形成一个全国性的、可公开访问的加拿大猫头鹰状况评估框架，并将为资源管理者和研究人员提供一个基础，以评估土地管理和保护做法对全国猫头鹰种群的影响。