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引用本文:白宁静,陈丽,蒋伊能,张涛,刘术,刘晓曦,李天丽,赵帅营,陈光杰.阳宗海砷污染背景下浮游植物的时空分布特征及其驱动因子解析.湖泊科学,2019,31(1):147-158. DOI:10.18307/2019.0114
BAI Ningjing,CHEN Li,JIANG Yineng,ZHANG Tao,LIU Shu,LIU Xiaoxi,LI Tianli,ZHAO Shuaiying,CHEN Guangjie.Spatio-temporal characteristics of phytoplankton distribution and the identification of driving factors in the arsenic-contaminated Yangzong Lake. J. Lake Sci.2019,31(1):147-158. DOI:10.18307/2019.0114
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阳宗海砷污染背景下浮游植物的时空分布特征及其驱动因子解析
白宁静1, 陈丽1, 蒋伊能1, 张涛1, 刘术1, 刘晓曦1, 李天丽2, 赵帅营1, 陈光杰1
1.云南师范大学旅游与地理科学学院, 高原地理过程与环境变化省重点实验室, 昆明 650500;2.中国科学院水生生物研究所, 武汉 430072
摘要:
人类活动导致的重金属污染是湖泊水体面临的主要环境压力之一.云南高原湖泊阳宗海于2008年暴发了砷污染事件且水体砷浓度目前仍然超过生活饮用水卫生标准,严重影响了水安全和生态系统健康.本研究于2015年4月-2016年2月每两月对阳宗海南、中、北部湖区进行采样调查及分析,共鉴定出浮游植物7门44属68种,绿藻门种数最多.蓝藻门占绝对优势,其中伪鱼腥藻(Pseudoanabaena sp.)、浮丝藻(Planktothrix sp.)、束丝藻(Aphanizomenon sp.)为全年的优势种,这与已有调查显示的阳宗海砷污染后浮游植物群落中蓝藻占优的基本特征一致.方差分析结果表明浮游植物生物量在时间尺度上呈现显著的变化特征,最大值出现在8月(14.06 mg/L),最小值出现在12月(1.23 mg/L),而空间差异不显著.Pearson相关分析显示,浮游植物总生物量与水温、pH呈显著正相关.而与砷、透明度、锰、钠、钾和总磷浓度呈显著负相关,冗余分析结果表明,水温、砷、钙、锰、钾共同解释了阳宗海浮游植物群落结构变化的57.18%.方差分解的结果进一步表明,水温、钙离子和砷三者作用共同解释了浮游植物群落结构变化的32.05%,其中水温和钙离子分别独立解释了群落变化的12.45%和8.28%,水体砷浓度仅独立解释了2.33%,但与水温共同作用解释了9.46%.因此,我们推测水温的季节性波动导致了湖泊水体热力分层的明显变化,其中水体混合作用的增强可能会促进底泥释放过程并增加表层水体的砷浓度,进而影响了浮游植物群落的季节性变化.研究结果有利于评价重金属污染对湖泊的长期生态效应,并为砷污染湖泊的环境修复提供重要的科学依据.
关键词:  阳宗海  砷污染  浮游植物  群落结构  环境因子
DOI:10.18307/2019.0114
分类号:
基金项目:国家自然科学基金项目(41461096,41771239,31460131)、2017年中西部高等学校青年骨干教师国内访问学者项目和云南省应用基础研究计划项目面上项目(2018FB077)联合资助.
Spatio-temporal characteristics of phytoplankton distribution and the identification of driving factors in the arsenic-contaminated Yangzong Lake
BAI Ningjing1, CHEN Li1, JIANG Yineng1, ZHANG Tao1, LIU Shu1, LIU Xiaoxi1, LI Tianli2, ZHAO Shuaiying1, CHEN Guangjie1
1.Provincial Key Laboratory of Plateau Geographical Processes and Environmental Change, School of Tourism and Geography, Yunnan Normal University, Kunming 650500, P. R. China;2.Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, P. R. China
Abstract:
Heavy metal pollution induced by human activities is widely regarded as a major environmental stressor for many lakes. Yangzong Lake, one of the nine largest plateau lakes in Yunnan Province, has experienced severe arsenic contamination since 2008. Monitoring data further showed that lake-water arsenic concentration consistently exceeded the standards for drinking water quality, posing severe risk for water safety and ecosystem health. A spatial survey and analysis of surface water quality and phytoplankton in Yangzong Lake was conducted bimonthly from April 2015 to February 2016, covering the south, central and north parts of the lake basin, respectively. A total of 68 algal taxa were identified, with the largest number of taxa belonging to Chlorophyta. However, Cyanophyta was absolutely dominant throughout the study period, and consisted of Pseudoanabaena, Planktothrix and Aphanizomenon. These results were consistent with previous surveys of phytoplankton from this lake, confirming the cyanobacteria-dominated community structure after the occurrence of arsenic pollution. The analysis of variance demonstrated that the phytoplankton biomass exhibited a significant seasonal fluctuation, with a maximum value found in August (14.06 mg/L) and a minimum biomass occurring in December (1.23 mg/L), while no significant spatial variation was observed. The Pearson correlation analysis showed that phytoplankton total biomass was significantly and positively correlated with water temperature and pH, but negatively correlated with arsenic concentration, water transparency, manganese concentration, sodium concentration, potassium concentration and total phosphorus concentration. Redundancy analysis displayed that water temperature, arsenic concentration, calcium concentration, manganese concentration and potassium concentration altogether accounted for 57.18% of the community variation in Yangzong Lake. The variation partitioning further showed that the water temperature, calcium concentration and arsenic concentration accounted for 32.05% of the spatio-temporal variation of phytoplankton community in Yangzong Lake, while the water temperature, calcium concentration and arsenic concentration independently accounted for 12.45%, 8.28% and 2.33% of the total variance, respectively. The coupling of arsenic concentration and water temperature explained 9.46% of the community variation. Therefore, we infer that seasonal fluctuation of water temperature may have caused the change in lake stratification and the increased water mixing under lower temperature may promote the sediment release of arsenic, resulting in higher lake-water arsenic concentration and stronger community turnover of phytoplankton. This study will help to evaluate the long term ecological effect of heavy metals on lakes and provide scientific evidence for restoration of arsenic polluted plateau lakes.
Key words:  Yangzong Lake  arsenic contamination  phytoplankton  community structure  environmental factor
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