AI声纹监测与人工样线调查在鸟类多样性监测中的差异比较: 以西溪国家湿地公园为例

doi:10.17520/biods.2025239

生物多样性 ›› 2026, Vol. 34 ›› Issue (4): 25239. DOI: 10.17520/biods.2025239 cstr: 32101.14.biods.2025239

• 研究报告: 动物多样性 • 上一篇下一篇

AI声纹监测与人工样线调查在鸟类多样性监测中的差异比较: 以西溪国家湿地公园为例

姚可侃¹^,², 余卉¹^,², 张巧玲¹^,², 陈琳¹^,²^,^*()

¹ 杭州西溪国家湿地公园服务中心(杭州西溪国家湿地公园生态文化研究中心), 杭州 310030
² 浙江西溪湿地生态系统定位观测研究站, 杭州 310030

收稿日期:2025-06-22 接受日期:2025-10-09 出版日期:2026-04-20 发布日期:2026-05-27
通讯作者: 陈琳
基金资助:
中央高校基本科研业务费专项资金(BFUKF202618);东亚-澳大利西亚迁飞路线中国候鸟保护网络建设(2023DOBZBF01)

Comparing AI voiceprint monitoring and line transect surveys for avian diversity: A case study of Xixi National Wetland Park

Kekan Yao¹^,², Hui Yu¹^,², Qiaoling Zhang¹^,², Lin Chen¹^,²^,^*()

¹ Hangzhou Xixi National Wetland Park Service Center (Hangzhou Xixi National Wetland Park Ecological and Cultural Research Center), Hangzhou 310030, China
² Zhejiang Xixi Wetland Ecosystem Observation and Research Station, Hangzhou 310030, China

Received:2025-06-22 Accepted:2025-10-09 Online:2026-04-20 Published:2026-05-27
Contact: Lin Chen
Supported by:
Fundamental Research Funds for the Central Universities(BFUKF202618);Construction of China Migratory Bird Conservation Network along East Asian-Australasian Flyway(2023DOBZBF01)

1. 附录.pdf(770KB)

摘要/Abstract

摘要：

鸟类多样性特征是评价湿地生态系统质量的重要指标。传统鸟类多样性调查多限于人工观测, 而近年来声纹监测技术逐步应用, 为鸟类多样性研究提供了新途径。为对比AI声纹监测与人工样线调查差异, 本研究于2024年1月(冬季)、4月(春季)、8月(夏季)和10月(秋季), 在杭州西溪国家湿地公园选取5处人工样线调查与声纹监测设备重合的样区开展同步监测。声纹监测选取77.5%作为置信阈值输出数据, 基于Simpson优势度指数(C)、Shannon-Wiener多样性指数(H′)、Pielou均匀度指数(J)和Margalef丰富度指数(M)等指标, 评估两种方法的适用性与局限性。结果表明: (1)四季累计, 声纹监测设备检测到鸟类105种, 人工样线记录鸟类89种; 声纹监测在物种丰富度(S)上表现更优。(2)按居留型看, 声纹监测对候鸟的检出更优, 人工样线则在留鸟的检出上更优; 声纹监测也能贡献区域新记录。(3)两种方法各指数的季节变化不完全一致, 声纹监测在C及M上多数季节较高, 更易捕捉优势物种信号且S表现更佳; 人工样线调查在H′及J上多数季节较高, 更能反映群落的综合多样性及物种分布的均衡程度。(4)按区域看, 声纹监测下绿堤/水下长廊的H′、J、M最高, 人工样线调查则以莲花滩最高。总体来看, 声纹监测适合长期、广时段的动态监测, 具有广阔前景, 可与人工样线调查互补, 建议建立识别置信度与质量控制阈值的评估体系, 提升方法准确性与可比性。

关键词: 鸟类多样性, 声纹监测, 人工样线调查, 西溪湿地, AI识别

Abstract

Aims: Traditional avian diversity surveys have largely relied on manual observations. However, in recent years, voiceprint monitoring technology has been gradually applied, providing a new approach for studying avian diversity. Avian diversity is a key indicator for assessing the quality of wetland ecosystems. This study aims to compare AI-based voiceprint monitoring with line transect surveys, offering a case reference for the application of bird voiceprint monitoring devices in wetland parks nationwide.
Methods: In January (winter), April (spring), August (summer), and October (autumn) of 2024, we conducted comprehensive and systematic avian diversity surveys at five sites within Xixi National Wetland Park in Hangzhou, Zhejiang, where line transect surveys and voiceprint monitoring devices overlapped. We applied a confidence threshold of 77.5% for output data. Based on Simpson dominance index (C), Shannon-Wiener diversity index (H′), Pielou evenness index (J), and Margalef richness index (M), the applicability and limitations of two methods were evaluated.
Results: (1) Voiceprint monitoring detected 105 bird species across four seasons, outnumbering the 89 species recorded by line transect surveys and demonstrating superior species richness (S) performance. (2) In terms of residency status, voiceprint monitoring showed higher detection efficiency for migratory birds, whereas line transect surveys performed better for resident birds; moreover, voiceprint monitoring also contributed new regional records. (3) The seasonal variations of the indices obtained by the two methods were not entirely consistent. The values of C and M were higher in most seasons under voiceprint monitoring, which performed better in capturing dominant species signals and reflecting S. By contrast, H′ and J were higher in most seasons in line transect surveys, better representing overall community diversity and the evenness of species distribution. (4) By region, the highest H′, J, and M values under voiceprint monitoring were observed at Lüdi/Shuixiachanglang area, whereas under line transect surveys, the highest values were recorded at Lianhuatan area.
Conclusion: Overall, voiceprint monitoring is suitable for long-term and wide time-scale dynamic monitoring, with broad application prospects, and can serve as a complement to line transect surveys. An evaluation system incorporating recognition confidence and quality control thresholds is recommended to enhance the accuracy and comparability of the method.

Key words: avian diversity, voiceprint monitoring, line transect surveys, Xixi Wetland, AI recognition

姚可侃, 余卉, 张巧玲, 陈琳 (2026) AI声纹监测与人工样线调查在鸟类多样性监测中的差异比较: 以西溪国家湿地公园为例. 生物多样性, 34, 25239. DOI: 10.17520/biods.2025239.

Kekan Yao, Hui Yu, Qiaoling Zhang, Lin Chen (2026) Comparing AI voiceprint monitoring and line transect surveys for avian diversity: A case study of Xixi National Wetland Park. Biodiversity Science, 34, 25239. DOI: 10.17520/biods.2025239.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2025239

https://www.biodiversity-science.net/CN/Y2026/V34/I4/25239

图/表 6

图1 西溪国家湿地公园人工样线调查路线及声纹监测设备点位

Fig. 1 Line transect survey routes and voiceprint monitoring sites in Xixi National Wetland Park

图2 声纹监测设备现场布设及声学识别流程图

Fig. 2 On-site deployment of voiceprint monitoring devices and acoustic recognition process

图3 各季节人工样线和声纹监测记录的鸟类数量

Fig. 3 Seasonal bird numbers recorded by line transect and voiceprint monitoring

图4 各季节基于人工样线和声纹监测计算的鸟类多样性指数

Fig. 4 Avian diversity indices calculated by line transect and voiceprint monitoring in each season

图5 各区域人工样线和声纹监测记录的鸟类数量。A: 莲花滩; B: 绿堤/水下长廊; C: 虾龙滩; D: 烟水渔庄/百家溇; E: 费家塘。

Fig. 5 Regional bird numbers recorded by line transect and voiceprint monitoring. A, Lianhuatan; B, Lüdi/Shuixiachanglang; C, Xialongtan; D, Yanshuiyuzhuang/Baijialou; E, Feijiatang.

图6 各区域人工样线和声纹监测计算的鸟类群落多样性指数。A: 莲花滩; B: 绿堤/水下长廊; C: 虾龙滩; D: 烟水渔庄/百家溇; E: 费家塘。

Fig. 6 Regional avian community diversity indices calculated by line transect and voiceprint monitoring. A, Lianhuatan; B, Lüdi/Shuixiachanglang; C, Xialongtan; D, Yanshuiyuzhuang/Baijialou; E, Feijiatang.

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AI声纹监测与人工样线调查在鸟类多样性监测中的差异比较: 以西溪国家湿地公园为例

Comparing AI voiceprint monitoring and line transect surveys for avian diversity: A case study of Xixi National Wetland Park

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