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应用激光雷达技术探究北京地区乌鸦夜栖地选择机制

谢冰1, 杨海涛2, 曹吉鑫3, 李进宇3, 王茂良3, 张微4, 李建强1, 徐基良1*   

  1. 1. 北京林业大学生态与自然保护学院, 北京 100083 2. 海南大学生态学院, 海口 570228 3. 北京市园林绿化科学研究院, 北京 100102 4. 北京市西山试验林场管理处, 北京 100093
  • 收稿日期:2026-01-04 修回日期:2026-02-14 接受日期:2026-05-10
  • 通讯作者: 徐基良

LiDAR-based investigation of the mechanisms governing nocturnal roost selection by crows in the Beijing urban area

Bing Xie1, Haitao Yang2, Jixin Cao3, Jinyu Li3, Maoliang Wang3, Wei Zhang4, Jianqiang Li1, Jiliang Xu1*   

  1. 1 School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083, China 

    2 School of Ecology, Hainan University, Haikou 570228, China 

    3 Beijing Academy of Forestry and Landscape Architecture, Beijing 100102, China 

    4 Administration of Xishan Mountain Experimental Forest Farm, Beijing 100093, China

  • Received:2026-01-04 Revised:2026-02-14 Accepted:2026-05-10
  • Contact: Jiliang Xu

摘要: 城市鸟类夜栖地选择是其在人工环境中适应与生存的关键。现有研究多关注宏观生境或微生境, 对鸟类直接利用的栖枝信息缺乏精准的测量手段和研究。激光雷达技术的高精度数据测量能力使得对鸟类栖枝的三维结构研究成为可能。本研究以北京城区冬季夜栖乌鸦为研究对象, 于2023–2025年在北京市六环环线内乌鸦主要聚集区域开展调查。在采集36个夜栖样方和36个对照样方的18个生境因子数据的基础上, 进一步使用激光雷达技术测量了1,361个夜栖枝条和581个对照枝条的4个变量, 以分析影响乌鸦夜栖地选择的主要因子。结果表明: 夜栖样方的栖树高度、栖树冠幅、噪声和照度均显著大于对照样方; 夜栖枝条的高度、直径、长度均显著大于对照枝条, 角度显著小于对照枝条。广义线性混合模型和广义线性模型结果表明, 栖树树高和噪声及4个枝条变量均是影响北京城区乌鸦夜栖地选择的关键生境变量, 乌鸦倾向于选择树高更高、环境噪声更大的区域夜栖, 在栖枝上偏好高度较高, 角度平缓, 较短的粗枝条或较长的细枝条。研究揭示了北京城区乌鸦夜栖地选择机制, 为城市鸟类管理提供了一定的科学依据, 同时验证了通过激光雷达技术开展鸟类栖息地精细化研究的可行性。

关键词: 夜栖地选择, 地基激光雷达, 乌鸦, 栖枝结构, 城市鸟类

Abstract

Aim: The selection of nocturnal roosting sites represents a critical aspect of urban birds’ adaptation and survival within anthropogenic environments. While existing studies have predominantly focused on macrohabitat or microhabitat characteristics—such as vegetation characteristics, meteorological factors, and anthropogenic disturbances—few have delved into the three-dimensional structural attributes of branches within tree crowns and their association with avian roost-site selection. A major challenge lies in the efficiency and accuracy limitations of traditional field survey methods in capturing fine-scale crown architecture, even though structural features such as branch diameter and angle are directly linked to the suitability of perching positions. Recent advancements in LiDAR technology offer a novel pathway to overcome this challenge. In particular, terrestrial laser scanning (TLS), with its millimeter-level measurement precision and strong penetration capability, now enables the accurate quantification of the three-dimensional configuration of perching branches within tree canopies. As a typical urban-adapted species, crows often form large-scale aggregated roosting groups in cities in winter, triggering human-wildlife conflict issues. To explore the key factors influencing their nocturnal roost selection and verify the feasibility of lidar in the refined research of bird habitats, this study took winter roosting crows in urban Beijing as the focal species and conducted surveys in the main crow aggregation areas within the 6th Ring Road of Beijing from 2023 to 2025. 

Methods: Based on data collected on 18 habitat factors from 36 roosting quadrats and 36 control quadrats, we further employed terrestrial laser scanning to measure four variables for 1,361 roosting branches and 581 control branches. Among the control branches, 349 were from roosting trees and 232 from non-roosting trees. The Mann-Whitney U test were used to compare differences in the 18 habitat factors between roosting and control quadrats. The Kruskal-Wallis test was applied to examine pairwise differences among roosting branches, control branches on roosting trees, and control branches on non-roosting trees. Further, generalized linear mixed models (GLMM) and generalized linear models (GLM) were adopted to identify the key variables affecting crow nocturnal roost selection. 

Results: The results indicated that tree height, crown width, noise levels, and illuminance were significantly higher in roosting quadrats compared to control quadrats. Furthermore, the height, diameter, and length of nocturnal roosting branches were significantly greater than those of both control branch groups, while the branch angle was significantly smaller. Between the two control groups, only branch height showed a significant difference. Analyses using GLMM revealed that tree height, noise levels were key habitat factors affecting nocturnal roost selection. GLM analyses revealed that branch height, branch angle, the quadratic term of branch height, and the interaction between branch diameter and branch length all had significant effects on the nocturnal roosting site selection by crows.

Conclusion: Crows exhibited a clear preference for nocturnal roosting sites characterized by taller trees and higher ambient noise levels. At the branch scale, they selectively perched on branches positioned at greater heights with shallower angles, which were typically either long and moderately thick or short and thick. This study elucidates the nocturnal roosting selection mechanism of crows in urban Beijing and offers a scientific basis for evidence-based urban bird management. Furthermore, it demonstrates the feasibility and distinct advantages of employing LiDAR technology in fine-scale habitat research, highlighting its potential to advance urban ornithological studies.

Key words: nocturnal roost selection, terrestrial laser scanning, crows, roosting branch architecture, urban birds