兽类学报 ›› 2026, Vol. 46 ›› Issue (2): 264-277.DOI: 10.16829/j.slxb.151029

• 研究论文 • 上一篇    下一篇

我国东海附近海域鲸类分布及面临的威胁:基于地方生态知识(LEK)分析

邓健成1,2, 王思凯2,3(), 张洋2, 贾金涛2, 张婷婷2,3, 赵峰1,2,3()   

  1. 1.浙江海洋大学水产学院,舟山 316022
    2.中国水产科学研究院东海水产研究所,农业农村部东海渔业资源开发利用重点 实验室,上海 200090
    3.上海长江口渔业资源增殖和生态修复工程技术研究中心,上海 200090
  • 收稿日期:2024-11-25 接受日期:2025-05-08 出版日期:2026-03-30 发布日期:2026-03-06
  • 通讯作者: 王思凯,赵峰
  • 作者简介:邓健成(1998- ),男,硕士研究生,主要从事鲸豚类资源调查与保护研究.
  • 基金资助:
    国家重点研发计划项目(2024YFD2401401);中海油海洋环境与生态保护公益基金会项目(CF?MEEC/TR/2024?14);中国水产科学研究院中央级公益性科研院所基本科研业务费专项资金(2023TD14)

Distribution and threats of cetaceans near the East China Sea: an analysis based on local ecological knowledge (LEK)

Jiancheng DENG1,2, Sikai WANG2,3(), Yang ZHANG2, Jintao JIA2, Tingting ZHANG2,3, Feng ZHAO1,2,3()   

  1. 1.School of Fisheries, Zhejiang Ocean University, Zhoushan 316022, China
    2.Key Laboratory of East China Sea Fishery Resources Exploitation, Ministry of Agriculture and Rural Affairs, East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai 200090, China
    3.Shanghai Engineering Research Center of Fisheries Resources Enhancement and Ecological Restoration of the Yangtze Estuary, Shanghai 200090, China
  • Received:2024-11-25 Accepted:2025-05-08 Online:2026-03-30 Published:2026-03-06
  • Contact: Sikai WANG, Feng ZHAO

摘要:

对鲸类动物进行有效的保护和完善的管理需要详细的物种及其分布信息。地方生态知识 (local ecological knowledge,LEK) 通常可以提供关于重点物种和生物资源的丰富信息,并越来越多地用于评估海洋哺乳动物的研究中。本研究于2023年11—12月,在东海附近海域沿岸地区进行了大规模的LEK走访调查,分析鲸类动物的多样性和分布状况、种群变化趋势及其可能面临的威胁。调查共涉及到59个港口码头,走访了534名渔民。本次走访调查共访问到了11种鲸类,包括东亚江豚(Neophocaena sunameri)、瓶鼻海豚(Tursiops truncatus)、印太瓶鼻海豚(Tursiops aduncus)、中华白海豚(Sousa chinensis)、糙齿海豚(Steno bredanensis)、弗氏海豚(Lagenodelphis hosei)、热带点斑原海豚(Stenella attenuata)、伪虎鲸(Pseudorca crassidens)、小虎鲸(Feresa attenuata)、短肢领航鲸(Globicephala macrorhynchus)和虎鲸(Orcinus orca),没有收集到大型鲸类的记录。普遍认为8—9月是最常见到鲸类的时间段,目击热点区域主要在海州湾、东海大桥、长江口渔场中下部、洞头以及南麂列岛北部海域。有超一半(50.19%)的受访者认为鲸类动物数量正在下降。调查显示,20.22%的受访者曾经误捕过鲸类动物,主要使用的网具是拖网和刺网。这些结果为东海海域鲸类动物的分布状况和所面临的威胁提供了研究基础。

关键词: 地方生态知识(LEK), 鲸类, 东海, 时空分布

Abstract:

Effective conservation and management of cetaceans require detailed information on species composition and spatial distribution. Local ecological knowledge (LEK) has increasingly been recognized as a valuable tool for assessing key species and biological resources, particularly in marine mammal studies. From November to December 2023, a large-scale LEK survey was conducted in coastal areas adjacent to the East China Sea. The study aimed to investigate the diversity, distribution patterns, population trends, and potential threats faced by cetacean species in the region. A total of 534 fishermen were interviewed across 59 ports and docks. During the survey, 11 cetacean species were recorded based on local reports, including the East Asian finless porpoise (Neophocaena sunameri), common bottlenose dolphin (Tursiops truncatus), Indo-Pacific bottlenose dolphin (Tursiops aduncus), Chinese white dolphin (Sousa chinensis), rough-toothed dolphin (Steno bredanensis), Fraser’s dolphin (Lagenodelphis hosei), pantropical spotted dolphin (Stenella attenuata), false killer whale (Pseudorca crassidens), pygmy killer whale (Feresa attenuata), short-finned pilot whale (Globicephala macrorhynchus), and killer whale (Orcinus orca). No sightings of large baleen whales were reported. Most respondents indicated that cetacean sightings were most frequent during August and September, with key hotspots located in Haizhou Bay, the East China Sea Bridge area, the mid-lower section of the Yangtze Estuary fishing ground, Dongtou, and the northern waters of the Nanji Islands. About half (50.19%) of respondents believed that cetacean populations are declining. Additionally, 20.22% reported incidental bycatch of cetaceans, primarily associated with trawl and gillnet fisheries. These findings provide a foundational understanding of cetacean distribution and threats in the East China Sea and offer valuable insights for future conservation strategies.

Key words: Local ecological knowledge (LEK), Cetaceans, East China Sea, Spatio-temporal distribution

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