Abstract Habitat models are fundamental tools for designing evidence-based conservation measures, particularly for locating sites with high potential for promoting a species' recolonisation and occupancy. However, it remains challenging to respond to both the need for large-scale general rules, and for fine-scale information concurrently. Multi-level habitat models provide all-in-one surfaces that explicitly account for conditional dependencies among single-level selection probabilities. We integrated occurrence data obtained from citizen-science species observation data with radio-tracking data to develop multi-level resource selection functions for the little owl (Athene noctua), a species of conservation concern in Central Europe. The results of our habitat selection analyses confirmed that suitable little owl habitat is located in widely open agricultural landscapes that often exist in the vicinity of human settlements. We mapped habitats at fine resolution (40 × 40 m) over an area covering 77,313 km2 in Switzerland and Baden-Wurttemberg, Germany. We validated the models with external out-of-sample data, and we demonstrated good predictive ability and transferability over the broad landscape. Overall, a fifth of the modelled landscape was estimated to be suitable for little owls. Habitat suitability scores in Switzerland were generally lower than in Baden-Wurttemberg due to higher elevation, fewer orchards, and more forest patches. Extant populations currently occupy c. 15% of the potential suitable habitats in Baden-Wurttemberg, and 2% in Switzerland, suggesting that considerable space for recolonisation is available. However, while Baden-Wurttemberg offers vast open landscapes, lowlands in Switzerland show narrow swaths of habitat along valleys and lakes. We showed that the simultaneous integration of different levels of habitat selection behaviour into a multi-level habitat suitability map creates a promising tool for conservation planning of endangered species over large geographical areas. Our multi-level model allowed for identification of both large-scale habitat suitability patterns to develop conservation strategies, and fine-scale clusters of high quality habitats where conservation measures can be applied at once, thereby increasing relevance of such all-in-one habitat maps for policy makers, wildlife managers and conservations practitioners alike.

中文翻译：

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大景观中的小猫头鹰：使用多级资源选择功能通知保护

摘要 栖息地模型是设计循证保护措施的基本工具，特别是用于定位具有促进物种重新定殖和占有潜力的地点。然而，同时响应对大规模通用规则和精细信息的需求仍然具有挑战性。多级栖息地模型提供多合一表面，明确说明单级选择概率之间的条件依赖性。我们将从公民科学物​​种观察数据中获得的发生数据与无线电跟踪数据相结合，为小猫头鹰（Athene noctua）开发多级资源选择功能，这是一种在中欧受到保护的物种。我们的栖息地选择分析结果证实，合适的小猫头鹰栖息地位于人类住区附近经常存在的广泛开放的农业景观中。我们在瑞士和德国巴登-符腾堡州 77,313 平方公里的区域内以高分辨率 (40 × 40 m) 绘制了栖息地图。我们使用外部样本外数据验证了模型，并在广泛的领域展示了良好的预测能力和可转移性。总体而言，估计有五分之一的建模景观适合小猫头鹰。由于海拔较高、果园较少和森林斑块较多，瑞士的栖息地适宜性得分普遍低于巴登符腾堡州。现存人口目前占据 c。巴登符腾堡州 15% 的潜在适宜栖息地，瑞士的 2%，表明有相当大的重新殖民空间可用。然而，尽管巴登-符腾堡州拥有广阔的开阔地貌，但瑞士的低地却沿着山谷和湖泊呈现出狭长的栖息地。我们表明，将不同级别的栖息地选择行为同时整合到多级栖息地适宜性地图中，为大地理区域的濒危物种保护规划创造了一个有前途的工具。我们的多层次模型允许识别大规模栖息地适宜性模式以制定保护策略，以及可以立即应用保护措施的高质量栖息地的精细集群，从而增加这种多合一栖息地的相关性供决策者、野生动物管理者和保护从业者使用的地图。