Numerous organisms depend on the physical structure of their habitats, but incorporating such information into ecological niche analyses has been limited by the lack of adequate data over broad spatial extents. The increasing availability of high-resolution measurements from country-wide airborne laser scanning (ALS) surveys – a light detection and ranging (LiDAR) technology – now provides unprecedented opportunities for characterizing habitat structure. Here, we use country-wide ALS data in combination with presence–absence observations of birds from a national monitoring scheme in the Netherlands to quantify niche filling, niche overlap and niche separation of three closely-related wetland birds (great reed warbler, Eurasian reed warbler and Savi's warbler). We developed a workflow to derive LiDAR metrics capturing different aspects of vertical and horizontal vegetation structure and used a principal component analysis (PCA), niche equivalency and niche similarity tests to analyse the fine-scale breeding habitat niches of these warbler species in the Netherlands. The widespread Eurasian reed warbler almost completely filled the available wetland habitat space (93%) whereas the two other species showed considerably less niche filling (64% and 74%, respectively). Substantial niche overlap occurred among all species, but each species occupied a distinct part of the habitat space. The great reed warbler mainly occurred in tall and vertically complex wetland vegetation and was absent in areas with large proportions of reedbeds. The Eurasian reed warbler occupied all parts of the wetland habitat space, whereas the Savi's warbler mainly occurred in large homogenous reedbeds with low vegetation height. Our results demonstrate that broad-scale ecological niche analyses can incorporate the fine-scale 3D habitat preference of species with unprecedented detail (e.g. 10 m resolution), and thus go much beyond quantifying the climate niche and 2D habitat information from land cover maps. This is important to identify habitat features and priorities for biodiversity conservation in wetlands and other habitats.

中文翻译：

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机载激光扫描揭示湿地鸟类的生态位分离

许多生物依赖于其栖息地的物理结构，但由于缺乏广泛的空间范围内的足够数据，将此类信息纳入生态位分析受到限制。来自全国机载激光扫描 (ALS) 调查的高分辨率测量的日益普及——一种光探测和测距 (LiDAR) 技术——现在为表征栖息地结构提供了前所未有的机会。在这里，我们使用全国范围的 ALS 数据结合荷兰国家监测计划中鸟类的存在与否观察来量化三种密切相关的湿地鸟类（大芦苇莺、欧亚芦苇）的生态位填充、生态位重叠和生态位分离。莺和萨维的莺）。我们开发了一个工作流程来获取捕获垂直和水平植被结构不同方面的 LiDAR 指标，并使用主成分分析 (PCA)、生态位等效性和生态位相似性测试来分析荷兰这些莺物种的精细繁殖栖息地生态位。分布广泛的欧亚苇莺几乎完全填满了可用的湿地栖息地空间 (93%)，而另外两个物种的生态位填充量则要低得多（分别为 64% 和 74%）。所有物种之间都发生了大量的生态位重叠，但每个物种都占据了栖息地空间的不同部分。大芦莺主要栖息在高大、垂直复杂的湿地植被中，在芦苇比例大的地区不存在。欧亚苇莺占据了湿地栖息空间的所有部分，而萨维莺主要生活在低植被高度的大型同质芦苇丛中。我们的结果表明，广泛的生态位分析可以以前所未有的细节（例如 10 m 分辨率）结合物种的精细尺度 3D 栖息地偏好，因此远远超出了从土地覆盖图中量化气候生态位和 2D 栖息地信息。这对于确定湿地和其他栖息地生物多样性保护的栖息地特征和优先事项非常重要。因此，不仅仅是从土地覆盖图中量化气候生态位和二维栖息地信息。这对于确定湿地和其他栖息地生物多样性保护的栖息地特征和优先事项非常重要。因此，不仅仅是从土地覆盖图中量化气候生态位和二维栖息地信息。这对于确定湿地和其他栖息地生物多样性保护的栖息地特征和优先事项非常重要。