生物多样性

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鲸类动物声学监测研究进展

周冯祥1,2,3,鲁夕霞2,3,雍李明2,3,曾千慧2,3,杨亮亮1,李平1,张语克2,3*,王先艳2,3*   

  1. 1.汕头大学海洋灾害预警与防护广东省重点实验室,广东汕头,515063; 2. 自然资源部第三海洋研究所, 福建厦门 361005; 3.福建省海洋生态保护与修复重点实验室, 福建厦门 361005
  • 收稿日期:2024-12-11 修回日期:2025-06-03 接受日期:2025-06-19
  • 通讯作者: 张语克

Research progress on acoustic monitoring of cetaceans

Fengxiang Zhou1,2,3, Xixia Lu2,3, Liming Yong2,3, Qianhui Zeng2,3, Liangliang Yang1, Ping Li1, Yuke Zhang2,3*, Xianyan Wang2,3*   

  1. 1.Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Prevention, Shantou University, Shantou, Guangdong 515063 

    2.Third Institute of Oceanography, Ministry of Natural Resources, Xiamen, Fujian 361005 

    3.Fujian Provincial Key Laboratory of Marine Ecological Conservation and Restoration, Xiamen, Fujian 361005

  • Received:2024-12-11 Revised:2025-06-03 Accepted:2025-06-19
  • Contact: Yuke Zhang

摘要: 鲸类动物作为海洋生态系统的关键指示物种,其种群动态的有效监测对生物多样性保护至关重要。传统船基目视调查方法受制于海况条件、天气能见度及人力成本等因素,难以实现时空连续性的生态监测。被动声学监测(passive acoustic monitoring, PAM)技术通过布设水听器实时接收并记录鲸类声学信号及环境噪声等,突破了传统监测瓶颈,实现了鲸类动物的全天候、非侵入式立体化监测。本文系统梳理了2004年至2024年6月期间全球1089篇(英文1038篇,中文51篇)鲸类动物声学监测研究文献。相关研究呈现阶段性特征,2004−2010年为低速积累期(年发文量< 30篇),2016年后进入快速发展期(年发文量> 50篇),目前研究热度持续攀升。研究主题主要聚焦于:(1)设备发展与技术方法(19.9%)、(2)声学信号与通讯模式(18.7%)、(3)种群与空间生态学(38.0%)、(4)鲸类生态行为模式(15.1%)及(5)保护与管理应用(8.3%)。近年来,声学设备的种类与功能日益丰富,深度学习等先进技术的创新应用显著提升了海量声学数据的处理效率。声学监测研究已从传统的声信号识别拓展至种群动态分析、声景生态评估及行为模式解析等多元领域,成为鲸类动物保护与管理的重要工具。针对我国当前存在的鲸类声学监测体系尚不完善、声学数据库缺乏共享等问题,建议重点从构建综合性声学监测网络、建立标准化声学共享数据库等方面寻求突破。本文旨在明晰国内外鲸类动物声学监测研究动态与未来发展趋势,为我国鲸类保护实践提供理论依据与技术参考。

关键词: 鲸类动物, 声学监测, 深度学习, 种群动态, 栖息地利用, 保护管理

Abstract

Background & Aim: As key indicator species of marine ecosystems, effective monitoring of cetacean population dynamics is of great significance to biodiversity conservation. Traditional ship-based visual survey methods are constrained by multiple factors such as sea conditions, weather visibility and labor costs, making it difficult to achieve spatial and temporal continuity of ecological monitoring. Passive acoustic monitoring (PAM) breaks through the traditional monitoring bottleneck by deploying hydrophones to receive cetacean acoustic signals and environmental noise in real-time, achieving all-weather, non-invasive and three-dimensional monitoring of cetaceans. We conducted a systematic review of cetacean acoustic monitoring literature published between 2004 and June 2024, categorizing findings into five thematic areas. Our analysis identifies recent research achievements and persistent challenges, and proposes strategic recommendations for advancing acoustic monitoring applications in China. 

Review Results: Our meta-analysis identified 1,089 relevant papers, revealing limited publication output between 2004 and 2013 followed by exponential growth post-2016. The analyzed literature coalesces into five research domains: (1) equipment development and technical methods (19.9%), (2) acoustic signals and communication patterns (18.7%), (3) population and spatial ecology (38.0%), (4) ecological behavioral patterns of cetaceans (15.1%), and (5) conservation and management applications (8.3%). Technological convergence such as deep learning has revolutionized high-throughput acoustic data processing. Contemporary research extends beyond acoustic signal types to population dynamics, soundscape ecology and behavioral patterns, establishing acoustic monitoring as a critical tool in cetacean conservation and management. 

Perspectives: This review synthesizes contemporary advancements in cetacean bioacoustics and outlines strategic pathways for China's nascent research initiatives. We propose five evidence-driven priorities to advance both scientific understanding and conservation applications: (1) advance technological innovation by developing next-generation autonomous recording systems and intelligent analytical tools tailored to cetacean vocalizations; (2) implement holistic monitoring systems that synergize multi-dimensional acoustic data with environmental and behavioral datasets through sensor network integration; (3) establish unified national archives featuring standardized protocols for data sharing and collaboration, incorporating blockchain technology for traceability; (4) strengthen interdisciplinary capacity through specialized training programs integrating marine acoustics, ecology, and computational modeling; (5) expand participatory science frameworks via targeted science communication campaigns and citizen science platforms for coastal communities. These strategic priorities aim to bridge existing research gaps and advance evidence-based cetacean conservation.

Key words: cetaceans, acoustic monitoring, deep learning, population dynamics, habitat use, conservation management