| 青海湖浮游植物群落时空格局及其环境驱动因子 |
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| 引用本文： | 孙兴,蒋小明,宋高飞,郑鹏,张昆,高海鹏,窦筱艳,艾雪.青海湖浮游植物群落时空格局及其环境驱动因子[J].湖泊科学,2023,35(2):540-552. |
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| 作者姓名： | 孙兴 蒋小明 宋高飞 郑鹏 张昆 高海鹏 窦筱艳 艾雪 |
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| 作者单位： | 西安理工大学省部共建西北旱区生态水利国家重点实验室, 西安 710048;中国科学院水生生物研究所, 淡水生态与生物技术国家重点实验室, 武汉 430072;青海省生态环境监测中心, 国家环境保护青藏高原生态环境监测与评估重点实验室实验室, 青海省生态环境监测与评估重点实验室, 西宁 810007 |
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| 基金项目： | 青海省咸水湖、盐湖水体监测体系能力建设项目资助。 |
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| 摘 要： | 为了解青海湖浮游植物群落结构特征、时空分布格局及其关键环境驱动因子,于2020年5月(春)、8月(夏)、10月(秋)对青海湖进行系统调查,分析浮游植物群落在3个季度和4个区域(湖滨带、进水区、浅水区和深水区)间的差异。3次调查共检出浮游植物6门39属65种,物种组成以硅藻(36种,占总物种数的55.38%)、绿藻(17种,26.15%)和蓝藻(7种,10.76%)为主。4个区域间的浮游植物丰度存在显著差别,其中深水区丰度显著高于其他区域,主要原因可能在于深水区的环境较为稳定。3个季节间,浮游植物丰度和生物量具有较大差异:夏季和秋季的丰度、生物量均为春季的近10倍;浮游植物的优势类群和种类也发生了较大的变化:春季最具优势类群为硅藻门,优势种也主要隶属于硅藻门,而夏、秋两季则以蓝藻门种属占据主要优势。春季浮游植物的Pielou均匀度和Simpson多样性指数显著高于夏、秋两季,秋季Margalef指数和Shannon-Wiener多样性指数高于夏季。PERMANOVA分析和NMDS分析显示,青海湖浮游植物群落结构在不同区域和不同季节间具有显著差异。此外,dbRDA分析表明:盐度、水温和总磷...
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| 关 键 词： | 青海湖 浮游植物 群落结构 环境因子 |
| 收稿时间： | 2022/6/17 0:00:00 |
| 修稿时间： | 2022/7/11 0:00:00 |
Spatio-temporal patterns of phytoplankton communities and their driving environmental factors in Lake Qinghai |
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| Sun Xing,Jiang Xiaoming,Song Gaofei,Zheng Peng,Zhang Kun,Gao Haipeng,Dou Xiaoyan,Ai Xue.Spatio-temporal patterns of phytoplankton communities and their driving environmental factors in Lake Qinghai[J].Journal of Lake Science,2023,35(2):540-552. |
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| Authors: | Sun Xing Jiang Xiaoming Song Gaofei Zheng Peng Zhang Kun Gao Haipeng Dou Xiaoyan Ai Xue |
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| Institution: | State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi''an University of Technology, Xi''an 710048, P. R. China;State Key Laboratory of Fresh Water Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, P. R. China;Qinghai Eco-Environment Monitoring Center, State Environmental Protection Key Laboratory of Tibetan Plateau Eco-Environmental Monitoring and Assessment, Qinghai Key Laboratory of Eco-Environmental Monitoring and Assessment, Xining 810007, P. R. China |
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| Abstract: | To understand the spatio-temporal of phytoplankton communities and their key environmental drivers in the Lake Qinghai, we conducted a systematic survey during May (Spring), August (Summer), and October (Autumn) in 2020, and examined how phytoplankton communities varied among three seasons and four regions (lakeshore zone, inlet zone, shallow zone, and deep zone). A total of 65 species belonging to 39 genera and 6 phyla were identified, with Bacillariophyta (36 species, accounting for 55.38% of the total species) being the species-richest class, followed by Chlorophyta (17 species, 26.15%), and Cyanophyta (7 species, 10.76%). The abundance of phytoplankton differed significantly among four regions, with significantly higher values in deep zone than other zones, probably due to the more stable environment in deep zone. There were also significant differences in abundance and biomass of phytoplankton among the three seasons. The abundance and biomass of phytoplankton in summer and autumn were nearly 10 times higher than those in spring, and the dominant groups and species of phytoplankton also changed greatly. The most dominant class in Spring was Bacillariophyta, and the dominant species were also belonged to Bacillariophyta, while the dominant group and species in Summer and Autumn became Cyanophyta and its subset species. The Pielou''s evenness and Simpson diversity indices of phytoplankton in Spring were significantly higher than those in Summer and Autumn, and the Margalef and Shannon-Wiener indices showed higher values in Autumn than in Summer. PERMANOVA and NMDS both indicated that the structure of phytoplankton communities varied significantly among different regions and seasons in the Lake Qinghai. In addition, the dbRDA analysis showed that salinity, water temperature and total phosphorus were the key environmental factors affecting the phytoplankton patterns in the Lake Qinghai. Compared with the historical surveys, this study indicated that the main dominant groups of phytoplankton community in Lake Qinghai gradually changed from Bacillariophyta to Cyanophyta. This study reveals the spatio-temporal pattern and key driving factors of phytoplankton communities in the Lake Qinghai, which can provide theoretical support for the subsequent protection and management of the Lake Qinghai. |
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| Keywords: | Lake Qinghai phytoplankton community structure environmental factors |
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