| 引用本文: | 季雨来,吴召仕,张京,刘鹏,裴鹏娜,张帅,黄佳聪.太湖流域平原农业区典型圩塘浮游植物群落特征及其影响因子.湖泊科学,2024,36(5):1380-1391. DOI:10.18307/2024.0514 |
| Ji Yulai,Wu Zhaoshi,Zhang Jing,Liu Peng,Pei Pengna,Zhang Shuai,Huang Jiacong.Quantifying the dynamics of phytoplankton communities and its driving factors: An example from an agricultural pond within a lowland polder in Lake Taihu Basin. J. Lake Sci.2024,36(5):1380-1391. DOI:10.18307/2024.0514 |
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| 太湖流域平原农业区典型圩塘浮游植物群落特征及其影响因子 |
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季雨来1,2, 吴召仕2, 张京1,2, 刘鹏2, 裴鹏娜2,3, 张帅1,2, 黄佳聪2,4
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1.中国科学院大学, 北京 101408;2.中国科学院南京地理与湖泊研究所, 湖泊与流域水安全重点实验室, 南京 210008;3.河海大学港口海岸与近海工程学院, 南京 210024;4.中国科学院南京地理与湖泊研究所, 鄱阳湖湖泊湿地综合研究站, 九江 332899
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| 摘要: |
| 浮游植物是淡水生态系统的重要初级生产者,具有生长周期短、对环境变化敏感等特征,可很好地指示水生态环境状态,而现有研究主要集中于河流湖库等大水面水域,对小微水体关注较少。本研究选择太湖流域平原农业区的典型圩塘,开展浮游植物与气象、水文、营养等相关环境因子的周年(2022年1—12月)动态变化监测,分析浮游植物群落的季节变化规律,构建浮游植物与环境因子之间的结构方程模型,解析浮游植物对环境因子的响应规律,并比较其与河流湖库等大水面水域浮游植物群落影响因子的差异。研究结果表明:1)圩塘共检测出浮游植物7门55属73种,裸藻在生物量上占据优势,与常见的蓝藻门、裸藻门占优势的河流湖库存在差异;2)浮游植物可归纳为22个功能群,其中优势功能群4个(P、J、W1和W2),表明圩塘生境具有富营养化、浑浊、混合作用强烈等特征,Q指数计算结果为0.63≤Q≤2.38,与水质监测结果(V类,年均总磷为0.16 mg/L,总氮为1.73 mg/L)总体一致;3)浮游植物群落多样性变化主要受温度控制,而浮游植物功能群变化主要受水深控制,与大水面水体不同,圩塘浮游植物受营养影响较小。本研究有利于深化认识平原农业区典型圩塘的浮游植物动态变化规律,为提升平原农业区小微水体生态健康提供理论支撑。 |
| 关键词: 浮游植物 氮磷 多样性 功能群 结构方程模型 |
| DOI：10.18307/2024.0514 |
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| 基金项目:国家自然科学基金项目(42222104,42371116)、江苏省碳达峰碳中和科技创新专项(BK20220042)和中国科学院南京地理与湖泊研究所自主部署科研项目(NIGLAS2022GS10)联合资助。 |
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| Quantifying the dynamics of phytoplankton communities and its driving factors: An example from an agricultural pond within a lowland polder in Lake Taihu Basin |
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Ji Yulai1,2, Wu Zhaoshi2, Zhang Jing1,2, Liu Peng2, Pei Pengna2,3, Zhang Shuai1,2, Huang Jiacong2,4
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1.University of Chinese Academy of Sciences, Beijing 101048, P. R. China;2.Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P. R. China;3.College of Harbour Coastal and Offshore Engineering, Hohai University, Nanjing 210024, P. R. China;4.Poyang Lake Wetland Research Station, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Jiujiang 332899, P. R. China
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| Abstract: |
| As essential primary producers in freshwater ecosystems, phytoplankton offers insights into aquatic ecology due to its short growth cycles and sensitivity to environmental changes. However, previous publications paid most attention to phytoplankton in large water bodies (e.g., rivers, lakes and reservoirs). Limited attention was paid to smaller water bodies. This study selected a typical agricultural pond within a lowland polder in Lake Taihu Basin, and conducted one-year measurement (2022) including phytoplankton, meteorological, hydrological and nutrient conditions. Based on the measured dataset, the season pattern of phytoplankton dynamics was analyzed. A structural equation model was developed to explore the cause-effect relationship between phytoplankton and environmental factors. The relationship in the unique agriculture pond was compared with that in other large water bodies. Our investigation revealed that a total of 73 species from 55 genera and 7 phyla of phytoplankton were detected in the studied pond, with the dominant phylum of Euglenophyta. The dominant phylum in the studied pond was different from that (Cyanophyta and Chlorophyta) in large water bodies. Phytoplankton species were categorized into 22 functional groups, with 4 dominant groups of P, J, W1, W2, and an Q index of 0.63-2.38. These results revealed the characteristics of eutrophication, turbidity, and strong water mixing within the pond, and were generally consistent with water quality monitoring results (belonging to class V, with an annual average of TP=0.16 mg/L and TN=1.73 mg/L). Temperature was found to be a critical factor influencing the diversity of phytoplankton communities, while water depth was identified as a crucial factor affecting changes in phytoplankton functional groups. These driving factors was distinct from that (e.g., light and nutrient conditions) in larger water bodies. This study enhanced our understanding of phytoplankton dynamics in typical agricultural ponds within the lowland areas, and provided fundamental support to improve ecological health of small water bodies in lowland agricultural areas. |
| Key words: Phytoplankton nitrogen and phosphorus diversity functional group structural equation model |
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