海洋中大型浮游动物网具及船用设备探讨和展望

doi:10.19423/j.cnki.31-1561/u.2025.130

船舶 ›› 2025, Vol. 36 ›› Issue (05): 14-27.DOI: 10.19423/j.cnki.31-1561/u.2025.130

海洋中大型浮游动物网具及船用设备探讨和展望

沈悦¹, 周朦^1,2,3,4,*, 汤清之⁵

1.中国极地研究中心上海 200136;
2.上海交通大学海洋学院上海 200230;
3.上海交通大学海底科学与划界全国重点实验室上海 200240;
4.自然资源部极地科学重点实验室上海 200136;
5.中国船舶及海洋工程设计研究院上海 200011

收稿日期:2025-08-18 修回日期:2025-09-30 出版日期:2025-10-25 发布日期:2025-11-03
通讯作者: 周朦（1957-）,男,博士,讲席教授。研究方向：海洋动力学、生物种群动力学以及生态动力学;汤清之（1989-）,男,硕士,高级工程师。研究方向：海洋科考船、极地船舶设计。
作者简介:沈悦（1991-）,男,本科,工程师。研究方向：破冰船实验室建设以及极地大洋科考作业。
基金资助:
国家级自然科学基金（41941008）

Perspectives on Meso- and Macro-Zooplankton Sampling Nets and Marine Equipment

SHEN Yue¹, ZHOU Meng^1,2,3,4,*, TANG Qingzhi⁵

1. Polar Research Institute of China, Shanghai 200136, China;
2. School of Oceanography, Shanghai Jiao Tong University,Shanghai 200230, China;
3. State Key Laboratory of Submarine Geoscience, Shanghai Jiao Tong University, Shanghai 200240,China;
4. Key Laboratory of Polar Science, Ministry of Natural Resources, Shanghai 200136, China;
5. Marine Design & Research Institute of China, Shanghai 200011, China

Received:2025-08-18 Revised:2025-09-30 Online:2025-10-25 Published:2025-11-03

摘要/Abstract

摘要： 浮游动物网具是生物海洋学研究的基础工具,其取样质量直接影响种群结构与生态功能评估的准确性。该文回顾了浮游动物网具从早期垂直拖网到现代多联网系统（如MOCNESS与Multinet）的技术演进,指出其在机械控制、电子传感与分层取样方面的显著进步;分析了光学、声学及环境DNA等非接触式技术对传统网具的互补作用,并强调了网具取样在物种鉴定与数据验证中的不可替代性。文章进一步提出,未来浮游动物网具的发展应融合感知系统、人工智能与样品保真技术,构建“智慧网具”系统,以实现对中大型浮游动物的高效、低扰动、定量化的取样。

关键词: 海洋生物, 浮游动物网具, 种群结构, 人工智能

Abstract: Zooplankton nets are fundamental tools for biological oceanography, and their sampling quality directly affects the evaluation accuracy of species composition and ecological function. The technical evolution of zooplankton nets from early vertical hauls to modern multi-net platforms (such as MOCNESS and Multinet) has been reviewed to highlight significant advancements in mechanical control, telemetry, and depth-resolved sampling. It analyzes the complementary role of non-contact technologies, such as optics, acoustic, and environment DNA, to traditional nets, emphasizing the continuing necessity of net sampling in species identification and data verification. It is further proposed that the future development of zooplankton nets should integrate sensing systems, artificial intelligence, and sample-preservation technologies to develop a “smart net” system for efficient, low-bias and quantitative sampling of meso- and macro-zooplankton.

Key words: marine organism, zooplankton net, population structure, artificial intelligence

中图分类号:

沈悦, 周朦, 汤清之. 海洋中大型浮游动物网具及船用设备探讨和展望[J]. 船舶, 2025, 36(05): 14-27.

SHEN Yue, ZHOU Meng, TANG Qingzhi. Perspectives on Meso- and Macro-Zooplankton Sampling Nets and Marine Equipment[J]. Ship & Boat, 2025, 36(05): 14-27.

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海洋中大型浮游动物网具及船用设备探讨和展望

Perspectives on Meso- and Macro-Zooplankton Sampling Nets and Marine Equipment

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