Species distributional data from atlas projects collected by volunteers and professionals play an essential role in ecology and biodiversity conservation. Atlas data primarily allow evaluating longitudinal and latitudinal gradients in species distribution. However, the effects of additional factors such as elevation and associated climatic conditions and landscape structure are rarely assessed. We used the original data from the Atlas of birds breeding in the Czech Republic in terms of the presence and absence (0/1) of breeding occurrence of seven owl species in 604 mapping quadrates (each quadrate 12.0 × 11.1 km in size) to assess the effect of elevation (reaching from 100 to 1100 m a.s.l.) and temperature on the distributional patterns of the owls. Using a multivariate spatial analysis with latitude and longitude as space predictors and landscape structure as covariates, we found that elevation and temperature significantly affected owl distribution; the model explained 94.8% of the variability (p = 0.002). Only the boreal owl (Aegolius funereus) showed a clear preference for the highest elevation, and simultaneously, boreal and pygmy (Glaucidium passerinum) owls preferred the coldest environments. Eagle owl (Bubo bubo) and tawny owl (Strix aluco) most often occupied low and middle elevation of moderate temperatures. Barn owl (Tyto alba) and long-eared owl (Asio otus) inhabited the warmest areas in low elevations. Finally, little owl (Athene noctua) most often occurred in the lowest elevations of intermediate temperatures. We have documented that the elevation and associated climate conditions can work as an effective predictor to assess distributional preferences of owl species based on atlas data. The findings can be helpful when the management of owls' habitats is considered and implemented. For example, the results of our case study suggest that the boreal owl can be susceptible to global warming and intensive logging at high elevations.

志愿者和专业人士从地图集项目中收集的物种分布数据在生态和生物多样性保护中发挥着重要作用。Atlas 数据主要用于评估物种分布的纵向和纬度梯度。然而，很少评估诸如海拔和相关气候条件和景观结构等其他因素的影响。我们使用来自捷克共和国鸟类繁殖地图集的原始数据，根据 604 个测绘方阵（每个方阵 12.0 × 11.1 公里大小）中 7 种猫头鹰的繁殖发生率（0/1）来评估海拔（达到 100 至 1100 m asl）和温度对猫头鹰分布模式的影响。通过以经纬度为空间预测因子、景观结构为协变量的多元空间分析，我们发现海拔和温度显着影响了猫头鹰的分布；该模型解释了 94.8% 的变异性（p  = 0.002）。只有北方猫头鹰 ( Aegolius funereus ) 表现出对最高海拔的明显偏好，同时，北方和侏儒 ( Glaucidium passerinum ) 猫头鹰更喜欢最寒冷的环境。鹰鸮 ( Bubo bubo ) 和黄褐色猫头鹰 ( Strix aluco ) 最常栖息在中等温度的中低海拔地区。谷仓鸮（Tyto alba）和长耳鸮（Asio otus）栖息在低海拔最温暖的地区。最后，小猫头鹰（Athene noctua) 最常发生在最低海拔的中间温度。我们已经证明，海拔和相关的气候条件可以作为有效的预测指标，根据地图集数据评估猫头鹰物种的分布偏好。当考虑并实施猫头鹰栖息地的管理时，这些发现可能会有所帮助。例如，我们的案例研究结果表明，北方猫头鹰容易受到全球变暖和高海拔地区密集采伐的影响。