Detecting fish community structure in open waters using environmental DNA: a case study from the central South China Sea

IF 3 2区 生物学 Q1 MARINE & FRESHWATER BIOLOGY Frontiers in Marine Science Pub Date : 2025-03-28 DOI:10.3389/fmars.2025.1544827
Ting Chen, Shuai Zhang, Peiwen Jiang, Zuozhi Chen, Jun Zhang, Shannan Xu, Min Li
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Abstract

Monitoring fish diversity in open ocean environments presents substantial challenges, particularly due to the limitations of traditional sampling methods such as trawling, which are costly, labor-intensive, and ineffective for deeper water layers. Environmental DNA (eDNA) technology offers an economical and efficient alternative, complementing conventional survey techniques. In this study, eDNA analysis was employed to characterize fish species composition and diversity in the central South China Sea (SCS). Additionally, generalized additive models (GAMs) were applied for the 5 m and 200 m depth layers to assess the influence of environmental variables on fish communities. A total of 190 fish species, spanning 32 orders, 68 families, and 135 genera, were detected across eight sampling sites. The 5 m and 200 m depth layers harbored 184 and 178 species, respectively, with 172 species common to both layers. α-and β-diversity analyses revealed no significant differences in fish species composition or diversity between the two depths (p &gt; 0.05). GAM results highlighted temperature as a key environmental driver of fish distribution, with significant effects on species abundance at both depths (p &lt; 0.05). These findings underscore the utility of eDNA for monitoring fish diversity and elucidating the ecological mechanisms shaping vertical species distribution in deep-sea ecosystems. Given the logistical constraints of traditional survey methods in deep-sea environments, eDNA-based approaches offer valuable insights for the sustainable management and conservation of fishery resources in the central SCS.
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利用环境DNA检测开放水域鱼类群落结构:以南海中部为例
在开放海洋环境中监测鱼类多样性面临着巨大的挑战,特别是由于传统的采样方法(如拖网捕鱼)的局限性,这些方法成本高昂,劳动密集型,而且对更深的水层无效。环境DNA (Environmental DNA, eDNA)技术提供了一种经济高效的替代方法,是传统调查技术的补充。本研究采用eDNA分析方法对南海中部鱼类的种类组成和多样性进行了研究。此外,在5 m和200 m深度层应用广义加性模型(GAMs)来评估环境变量对鱼类群落的影响。在8个采样点共检测到鱼类190种,隶属于32目68科135属。5 m和200 m层分别有184种和178种,两层共有172种。α-和β-多样性分析显示,两个深度之间的鱼类种类组成和多样性没有显著差异(p >;0.05)。GAM结果强调温度是鱼类分布的关键环境驱动因素,对两个深度的物种丰度都有显著影响(p <;0.05)。这些发现强调了eDNA在监测鱼类多样性和阐明深海生态系统中形成垂直物种分布的生态机制方面的作用。考虑到传统调查方法在深海环境中的后勤限制,基于edna的方法为南海中部渔业资源的可持续管理和保护提供了宝贵的见解。
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来源期刊
Frontiers in Marine Science
Frontiers in Marine Science Agricultural and Biological Sciences-Aquatic Science
CiteScore
5.10
自引率
16.20%
发文量
2443
审稿时长
14 weeks
期刊介绍: Frontiers in Marine Science publishes rigorously peer-reviewed research that advances our understanding of all aspects of the environment, biology, ecosystem functioning and human interactions with the oceans. Field Chief Editor Carlos M. Duarte at King Abdullah University of Science and Technology Thuwal is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, policy makers and the public worldwide. With the human population predicted to reach 9 billion people by 2050, it is clear that traditional land resources will not suffice to meet the demand for food or energy, required to support high-quality livelihoods. As a result, the oceans are emerging as a source of untapped assets, with new innovative industries, such as aquaculture, marine biotechnology, marine energy and deep-sea mining growing rapidly under a new era characterized by rapid growth of a blue, ocean-based economy. The sustainability of the blue economy is closely dependent on our knowledge about how to mitigate the impacts of the multiple pressures on the ocean ecosystem associated with the increased scale and diversification of industry operations in the ocean and global human pressures on the environment. Therefore, Frontiers in Marine Science particularly welcomes the communication of research outcomes addressing ocean-based solutions for the emerging challenges, including improved forecasting and observational capacities, understanding biodiversity and ecosystem problems, locally and globally, effective management strategies to maintain ocean health, and an improved capacity to sustainably derive resources from the oceans.
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