| Issue |
E3S Web Conf.
Volume 617, 2025
2024 International Conference on Environment Engineering, Urban Planning and Design (EEUPD 2024)
|
|
|---|---|---|
| Article Number | 01014 | |
| Number of page(s) | 6 | |
| Section | Multi-dimensional Study on Ecological Environment and Resource Utilisation | |
| DOI | https://doi.org/10.1051/e3sconf/202561701014 | |
| Published online | 21 February 2025 | |
Study on the Community Structure and Diversity of Zooplankton in Dingzi Bay by Using Mathematical and Intelligent Analysis Tools
North China Sea Marine Forecasting and Hazard Mitigation Center of Ministry of Natural Resources, Qingdao 266061, China
* Corresponding author: 36302162@qq.com
In order to know the community structure and diversity of zooplankton in Dingzi Bay, based on the investigation data in April 2024(spring), the species composition, dominant species, community structure and the correlation between species diversity and environmental factors of zooplankton were analyzed by using computer systems and digital intelligent analysis tools. The results showed that the water quality at the bottom of Dingzi Bay was poor, and a tolal of 10 species and 5 taxa of zooplankton larvae were found. The average individual density of zooplankton was 387.0 ind/m3, and the average biomass (wet weight) was 188.6 mg/m3. The average Shannon-Wiener index (H'), Margalef's species richness diversity (d) and Pielou's evenness index (J') were 1.35, 0.92, 0.46, respectively. The dominant species were Calanus sinicus, Tortanus derjugini, Brachyura Zoea larva and fish egg. Cluster analysis showed that the zooplankton in the investigation area can be divided into 2 groups. The correlation analysis showed that water temperature was an important environmental factor affecting zooplankton indexes.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.