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<p>Coastal ecosystems are highly dynamic and increasingly affected by anthropogenic pressures and climate change, making effective biodiversity monitoring essential for their conservation and sustainable management. Environmental DNA (eDNA) metabarcoding has emerged as a powerful tool for assessing fish communities in complex coastal environments. In this study, we applied eDNA metabarcoding to investigate seasonal and spatial patterns of fish biodiversity in the coastal waters of Qingdao, China. A total of 57 water samples were collected from three coastal regions across three seasons, and seasonal variation and spatial differentiation in fish communities were examined using alpha and beta diversity analyses. Across all surveys, 110 fish species were detected, including 93 species in February, 33 in April, and 47 in July, with 18 species consistently detected in all three seasons. Diversity analyses revealed pronounced seasonal shifts in fish assemblage composition, along with detectable spatial differentiation among coastal areas. Overall, this study provides a multi-season eDNA dataset that contributes to coastal biodiversity research and supports resource management in temperate coastal systems.</p>

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Seasonal dynamics of fish communities in Qingdao coastal waters revealed by environmental DNA metabarcoding

  • 期刊论文

  • 发表日期：

    2026年4月27日

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  • Hui Jia,
  • Wenqiong Li,
  • Haoxuan Huang,
  • Hui Zhang

摘要

Coastal ecosystems are highly dynamic and increasingly affected by anthropogenic pressures and climate change, making effective biodiversity monitoring essential for their conservation and sustainable management. Environmental DNA (eDNA) metabarcoding has emerged as a powerful tool for assessing fish communities in complex coastal environments. In this study, we applied eDNA metabarcoding to investigate seasonal and spatial patterns of fish biodiversity in the coastal waters of Qingdao, China. A total of 57 water samples were collected from three coastal regions across three seasons, and seasonal variation and spatial differentiation in fish communities were examined using alpha and beta diversity analyses. Across all surveys, 110 fish species were detected, including 93 species in February, 33 in April, and 47 in July, with 18 species consistently detected in all three seasons. Diversity analyses revealed pronounced seasonal shifts in fish assemblage composition, along with detectable spatial differentiation among coastal areas. Overall, this study provides a multi-season eDNA dataset that contributes to coastal biodiversity research and supports resource management in temperate coastal systems.