生物多样性 ›› 2026, Vol. 34 ›› Issue (6): 25339.  DOI: 10.17520/biods.2025339  cstr: 32101.14.biods.2025339

• 研究报告: 动物多样性 •    下一篇

泸沽湖鱼类群落结构特征及驱动因子

李开飞1,2, 龚进玲1, 胡飞飞1, 李学梅1, 卢昭远1, 罗鸣钟2*, 朱挺兵1*   

  1. 1. 农业农村部淡水生物多样性保护重点实验室, 中国水产科学研究院长江水产研究所, 武汉 430223; 2. 长江大学动物科学与技术学院, 湖北荆州 434020
  • 收稿日期:2025-08-22 修回日期:2026-03-04 接受日期:2026-06-30 出版日期:2026-06-20 发布日期:2026-07-30
  • 通讯作者: 罗鸣钟, 朱挺兵
  • 基金资助:
    农业农村部财政专项(西南重点水域渔业资源与环境调查); 中国水产科学研究院中央公益性科研院所基本科研业务费专项资金(2023TD61)

Fish community structure and driving factors in Lugu Lake, southwest China

Kaifei Li1,2, Jinling Gong1, Feifei Hu1, Xuemei Li1, Zhaoyuan Lu1, Mingzhong Luo2*, Tingbing Zhu1*   

  1. 1 Key Laboratory of Freshwater Biodiversity Conservation, Ministry of Agriculture and Rural Affairs, Yangtze River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Wuhan 430223, China 

    2 College of Animal Science and Technology, Yangtze University, Jingzhou, Hubei 434020, China

  • Received:2025-08-22 Revised:2026-03-04 Accepted:2026-06-30 Online:2026-06-20 Published:2026-07-30
  • Contact: Mingzhong Luo, Tingbing Zhu

摘要: 泸沽湖是我国西南地区重要的高原深水型湖泊, 其鱼类群落状况已多年未见报道。本研究于2023–2024年春季(5月)和秋季(10月)对泸沽湖鱼类群落共开展了4次现场调查, 并结合冗余分析(redundancy analysis, RDA)与聚类方法, 揭示了环境因子对鱼类群落时空分异的驱动机制。共采集到鱼类14种, 隶属2目4科, 其中鲤形目占绝对优势(85.71%)。土著鱼类仅采集到1种, 为泥鳅(Misgurnus anguillicaudatus)。外来鱼类共采集到13种, 占鱼类种类数的92.86%。相对重要性指数(index of relative importance, IRI)显示, 鲫(Carassius auratus, IRI = 8,509)和麦穗鱼(Pseudorasbora parva, IRI = 1,763)在所有调查季节均维持高出现频率, 为全年优势种。RDA表明, 不同季节环境因子对鱼类群落结构变异的影响程度和方式存在差异, 春季鱼类群落结构变异主要受NO3-N、pH值等环境因子影响, 而秋季鱼类群落结构变异主要受NO3-N、总氮(total nitrogen, TN)等环境因子影响。丰度生物量比较曲线(abundance-biomass comparison curve, ABC)显示秋季生物量曲线显著高于丰度曲线, 呈现出“秋季稳态-春季亚稳态”模式。针对当前泸沽湖鱼类群落面临的土著鱼类衰退、外来鱼类占据优势等突出问题, 建议加强土著鱼类保护研究、强化对污染和外来鱼类放生活动的管控, 并建立渔业资源长期监测体系。

关键词: 鱼类资源, 群落结构, 多样性指数, 时空分异

Abstract

Aims: Lugu Lake, a significant plateau deep-water lake in Southwest China, has not had its fish community reported in recent years. 

Methods: This study was conducted to investigate the current status of fish communities in Lugu Lake through four field surveys carried out in spring (May) and autumn (October) of 2023 and 2024. Redundancy analysis (RDA) and clustering methods were employed to elucidate the driving effects of environmental factors on the spatiotemporal patterns of fish community structure. 

Results: A total of 14 fish species were identified, categorized into 2 orders, 4 families, with Cypriniformes being the predominant order (85.71%). The only indigenous fish species recorded was Misgurnus anguillicaudatus, while 13 exotic fish species were recorded, constituting 92.86% of the total species, with Carassius auratus and Pseudorasbora parva being the most abundant. RDA revealed that fish community structure was influenced by NO3-N and pH in spring, and by NO3-N and total nitrogen in autumn. The abundance-biomass comparison curve (ABC) showed that the biomass curve in autumn was significantly higher than the abundance curve, presenting an “autumn stable–spring substable state” pattern. 

Conclusion: To address the challenges faced by the fish community in Lugu Lake, such as the decline of indigenous species and the prevalence of exotic species, we recommend focusing on conserving indigenous fish, enhancing pollution control, regulating the release of exotic species, and establishing a comprehensive long-term monitoring program.

Key words: fish resources, community structure, diversity index, temporal and spatial variation