引用本文: | 叶华建,王冠华,陈乐乐,陈立婧,李晨虹,姜佳枚,潘宏博.崇明岛河道纤毛虫原生动物群落结构及对水环境的指示.湖泊科学,2024,36(6):1879-1887. DOI:10.18307/2024.0634 |
| Ye Huajian,Wang Guanhua,Chen Lele,Chen Lijing,Li Chenhong,Jiang Jiamei,Pan Hongbo.Community structure of ciliated protozoa in rivers of Chongming Island and its indication to the water quality. J. Lake Sci.2024,36(6):1879-1887. DOI:10.18307/2024.0634 |
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崇明岛河道纤毛虫原生动物群落结构及对水环境的指示 |
叶华建1, 王冠华2, 陈乐乐1, 陈立婧3, 李晨虹1,2, 姜佳枚1,2, 潘宏博1,2
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1.上海海洋大学, 海洋动物系统分类与进化上海高校重点实验室, 上海 201306;2.上海海洋大学, 环境DNA技术与水生态健康评估工程中心, 上海 201306;3.上海农林职业技术学院, 上海 201699
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摘要: |
浮游纤毛虫原生动物是真核微型生物的重要类群,在微食物环中扮演着物质和能量转换的关键角色,可作为水环境质量的指示生物。但传统沉降计数法对纤毛虫的鉴定分辨率较低,常造成多样性被低估。为此本研究在2020年7月-2021年5月期间利用可获得更高分类分辨率的定量蛋白银法(QPS),对崇明岛河道浮游纤毛虫的多样性和群落结构进行调查,同时用多元统计方法分析环境因子对其影响,并筛选潜在指示种。结果共检出纤毛虫131种,隶属于3纲11目,其中寡毛目相对丰度最高,是全年优势类群。Shannon-Wiener指数为1.53±0.06(范围为0.16~2.62),Pielou指数为0.75±0.02(范围为0.18~1.00),Margalef指数为1.07±0.06(范围为0.13~2.98),呈现明显的季节变化,与硝酸盐和叶绿素a浓度均呈显著相关。ANOSIM检验发现4个季节的纤毛虫群落结构差异极显著,存在明显演替过程。dbRDA分析显示,营养盐、叶绿素a、溶解氧和降水量是影响全年纤毛虫群落结构变化的主要环境因子,盐度对其无显著影响;而各季节纤毛虫群落结构的异质性也均与水质指标呈显著相关,盐度仅在秋季对纤毛虫群落结构有显著影响。12种纤毛虫对群落结构的累积贡献率达90%以上,以食藻性和杂食性种类为主,它们与富营养化指标显著相关。优势种中奇异海游虫(Pelagostrombidium mirabile)和透明裂隙虫(Rimostrombidium hyalinum)不易受盐度影响,可作为崇明岛水质状况的潜在指示生物。 |
关键词: 崇明岛 浮游原生动物 纤毛虫 群落结构 定量蛋白银法 |
DOI:10.18307/2024.0634 |
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基金项目:国家自然科学基金项目(32170533)和上海市科学技术委员会部分地方院校能力建设项目(19050501900)联合资助。 |
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Community structure of ciliated protozoa in rivers of Chongming Island and its indication to the water quality |
Ye Huajian1, Wang Guanhua2, Chen Lele1, Chen Lijing3, Li Chenhong1,2, Jiang Jiamei1,2, Pan Hongbo1,2
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1.Shanghai Key Laboratory for the Systematic Classification and Evolution of Marine Animals, Shanghai Ocean University, Shanghai 201306, P. R. China;2.Center for Environmental DNA Technology and Aquatic Ecological Health Assessment Engineering, Shanghai Ocean University, Shanghai 201306, P. R. China;3.Shanghai Vocational College of Agriculture and Forestry, Shanghai 201699, P. R. China
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Abstract: |
Planktonic ciliates play a vital role in the cycle of matter and energy transfer within the microbial food web. They are usually used to monitor water quality. However, the Utermöhl method, a popular quantitative method for plankton, cannot reveal the ciliature, which usually results in a low taxonomic resolution of ciliates and the underestimation of the ciliate richness. In this study, we applied the quantitative protargol stain method (QPS) to explore the diversity and community composition of planktonic ciliates in the rivers of Chongming Island from July 2020 to May 2021. This method could offer a higher taxonomic resolution than the Utermöhl method. We identified a total of 131 ciliate species, classified into 3 classes and 11 orders. Oligotrichida was the predominant order throughout the study period. The Shannon-Wiener index was 1.53±0.06 (ranged from 0.16 to 2.62), the Pielou index was 0.75±0.02 (ranged from 0.18 to 1.00), and the Margalef index was 1.07±0.06 (ranged from 0.13 to 2.98). All indices showed seasonal variations and were significantly correlated with nitrate and chlorophyll-a. The community structures between seasons showed significant differences as well, indicating a significant seasonal succession. Nutrients, chlorophyll-a, dissolved oxygen, and precipitation were the primary environmental factors that influenced the ciliate communities throughout the year. The heterogeneity of the ciliate communities in each season was significantly correlated with the water quality index. Except for the ciliate communities in the autumn, salinity had no notable impact on both annual communities and seasonal ones. Twelve species had more than 90% cumulative contributions to the community structure, which were mainly algivorous or omnivorous species. Since two dominant species, Pelagostrombidium mirabile and Rimostrombidium hyalinum, were significantly affected by water quality index rather than salinity, they could be used as potential indicators of the water quality of Chongming Island. |
Key words: Chongming Island planktonic protozoa ciliates community structure quantitative protargol stain method |
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