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激光雷达的植被结构解释了丹麦各地鸟类的局部丰富度。

Vegetation structure from LiDAR explains the local richness of birds across Denmark.

机构信息

Center for Macroecology, Evolution and Climate, Globe Institute, University of Copenhagen, Copenhagen, Denmark.

Section for Ecoinformatics & Biodiversity, Department of Biology, Aarhus University, Aarhus C, Denmark.

出版信息

J Anim Ecol. 2023 Jul;92(7):1332-1344. doi: 10.1111/1365-2656.13945. Epub 2023 Jun 3.

Abstract

Classic ecological research into the determinants of biodiversity patterns emphasised the important role of three-dimensional (3D) vegetation heterogeneity. Yet, measuring vegetation structure across large areas has historically been difficult. A growing focus on large-scale research questions has caused local vegetation heterogeneity to be overlooked compared with more readily accessible habitat metrics from, for example, land cover maps. Using newly available 3D vegetation data, we investigated the relative importance of habitat and vegetation heterogeneity for explaining patterns of bird species richness and composition across Denmark (42,394 km ). We used standardised, repeated point counts of birds conducted by volunteers across Denmark alongside metrics of habitat availability from land-cover maps and vegetation structure from rasterised LiDAR data (10 m resolution). We used random forest models to relate species richness to environmental features and considered trait-specific responses by grouping species by nesting behaviour, habitat preference and primary lifestyle. Finally, we evaluated the role of habitat and vegetation heterogeneity metrics in explaining local bird assemblage composition. Overall, vegetation structure was equally as important as habitat availability for explaining bird richness patterns. However, we did not find a consistent positive relationship between species richness and habitat or vegetation heterogeneity; instead, functional groups displayed individual responses to habitat features. Meanwhile, habitat availability had the strongest correlation with the patterns of bird assemblage composition. Our results show how LiDAR and land cover data complement one another to provide insights into different facets of biodiversity patterns and demonstrate the potential of combining remote sensing and structured citizen science programmes for biodiversity research. With the growing coverage of LiDAR surveys, we are witnessing a revolution of highly detailed 3D data that will allow us to integrate vegetation heterogeneity into studies at large spatial extents and advance our understanding of species' physical niches.

摘要

经典的生态研究强调了三维(3D)植被异质性对生物多样性模式的决定性作用。然而,在大面积范围内测量植被结构一直很困难。由于对大规模研究问题的日益关注,与更容易获得的栖息地指标(例如土地覆盖图)相比,局部植被异质性被忽视了。本研究使用新获得的 3D 植被数据,调查了栖息地和植被异质性对解释丹麦(42,394 平方公里)鸟类物种丰富度和组成模式的相对重要性。本研究使用了志愿者在丹麦各地进行的标准化、重复的鸟类点计数数据,以及土地覆盖图中的栖息地可用性指标和栅格化激光雷达数据(10 米分辨率)中的植被结构数据。本研究使用随机森林模型将物种丰富度与环境特征联系起来,并通过按筑巢行为、栖息地偏好和主要生活方式对物种进行分组来考虑特征特定的响应。最后,本研究评估了栖息地和植被异质性指标在解释当地鸟类组合组成中的作用。总体而言,植被结构与栖息地可用性对解释鸟类丰富度模式同样重要。然而,本研究没有发现物种丰富度与栖息地或植被异质性之间存在一致的正相关关系;相反,功能组对栖息地特征显示出个体响应。同时,栖息地可用性与鸟类组合组成模式的相关性最强。本研究结果展示了激光雷达和土地覆盖数据如何相互补充,以深入了解生物多样性模式的不同方面,并证明了将遥感和结构化公民科学计划相结合用于生物多样性研究的潜力。随着激光雷达调查的覆盖范围不断扩大,我们正在见证一场高度详细的 3D 数据革命,这将使我们能够将植被异质性纳入大空间尺度的研究中,并提高我们对物种物理小生境的理解。

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