建塘江浮游植物群落结构特征及与环境因子的关系
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摘要
为探明浙江省建塘江水质及浮游植物群落结构特征,2017年5—10月,对建塘江水质现状和浮游植物组成进行逐月采样调查。用水质综合指数法对建塘江污染情况进行评价和分析。建塘江水质评价结果处于重污染到严重污染状态,其中总氮、总磷和高锰酸盐指数为主要的超标因子。浮游植物调查结果显示,本次调查共检出浮游植物6门20科38属48种。其中绿藻门22种,蓝藻门10种,硅藻门10种,裸藻门3种,甲藻门2种,隐藻门1种。建塘江浮游植物丰度为86.00×10~4～635.00×10~4个/L,平均丰度为310.00×10~4个/L;生物量为0.14～2.34 mg/L,平均生物量为0.96 mg/L。丰富度指数为1.02～1.68,属于α-中污;香农维纳多样性指数在各采样断面均处于2.00～3.00,属于β-中污;辛普森多样性指数与香农维纳多样性指数基本一致。相关性分析结果显示,浮游植物丰度与温度正相关,而生物量与氨氮呈现显著负相关关系。典范对应分析显示,温度在第1排序轴和第2排序轴上均有较高的贡献率;蓝藻门与温度和总磷含量正相关,表明蓝藻能够适应较高的水温;绿藻门在各个象限均有分布,第2象限包含绿藻门种类最多,说明绿藻门浮游植物能适应高氮营养盐;硅藻门主要分布在第1、2、4象限,与温度呈负相关,说明高温抑制了硅藻的生长。
Water quality and phytoplankton species composition were monthly surveyed in water of Jiantangjiang River from May to October, 2017, and water quality was evaluated by a pollution index method to explore the pollution status of water quality and phytoplankton community structure in Jiantangjiang River. It was found that the water quality in Jiantangjiang exceeded the class V environmental quality standard of surface water, the levels of total nitrogen(TN), total phosphorus(TP) and COD being the main exceeding factors. A total of 48 species(38 genera) of phytoplankton were identified over a total cultured period, belonging to six major functional groups, i.e., Chlorophyta(22 species), Bacillariophyta(10 species), Cyanophyta(10 species), Euglenophyta(3 species), Pyrrophyta(2 species), and Cryptophyta(1 species), with phytoplankton abundance of 86×10~4—635×10~4 cell/L(average 310.00×10~4 cell/L) and phytoplankton biomass of 0.14—2.34 mg/L(average 0.96 mg/L). The Margalef index(D) was applied to evaluate the sampled water as α-moderately polluted, and variational trend of Shannon-Wiener diversity index(H′) was ranged from 2.00 to 3.00, showing a β-moderate pollution. Simpson′s diversity index showed a same trend as Shannon-Wiener diversity index(H′). The Pearson correlation coefficient revealed that phytoplankton abundance showed a positive correlation to the water temperature, while the biomass was negatively associated with NH~+_4-N content. Canonical correspondence analysis(CCA) indicated that temperature had a big contribution on both the first and the second ordination biplot. Cyanophyta showed a positive correlation with temperature and TP level, indicating that Cyanophyta adapt for high water temperature. Chlorophyta was mainly distributed in the second quadrant, indicating a good adaptability to high level of nitrogen. However, Bacillariophyta displayed a negative correlation with temperature, indicating that high temperature can inhibit growth of Bacillariophyta.
Water quality and phytoplankton species composition were monthly surveyed in water of Jiantangjiang River from May to October, 2017, and water quality was evaluated by a pollution index method to explore the pollution status of water quality and phytoplankton community structure in Jiantangjiang River. It was found that the water quality in Jiantangjiang exceeded the class V environmental quality standard of surface water, the levels of total nitrogen(TN), total phosphorus(TP) and COD being the main exceeding factors. A total of 48 species(38 genera) of phytoplankton were identified over a total cultured period, belonging to six major functional groups, i.e., Chlorophyta(22 species), Bacillariophyta(10 species), Cyanophyta(10 species), Euglenophyta(3 species), Pyrrophyta(2 species), and Cryptophyta(1 species), with phytoplankton abundance of 86×10~4—635×10~4 cell/L(average 310.00×10~4 cell/L) and phytoplankton biomass of 0.14—2.34 mg/L(average 0.96 mg/L). The Margalef index(D) was applied to evaluate the sampled water as α-moderately polluted, and variational trend of Shannon-Wiener diversity index(H′) was ranged from 2.00 to 3.00, showing a β-moderate pollution. Simpson′s diversity index showed a same trend as Shannon-Wiener diversity index(H′). The Pearson correlation coefficient revealed that phytoplankton abundance showed a positive correlation to the water temperature, while the biomass was negatively associated with NH~+_4-N content. Canonical correspondence analysis(CCA) indicated that temperature had a big contribution on both the first and the second ordination biplot. Cyanophyta showed a positive correlation with temperature and TP level, indicating that Cyanophyta adapt for high water temperature. Chlorophyta was mainly distributed in the second quadrant, indicating a good adaptability to high level of nitrogen. However, Bacillariophyta displayed a negative correlation with temperature, indicating that high temperature can inhibit growth of Bacillariophyta.
引文
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[21] 王瑜,刘录三,舒俭民,等.白洋淀浮游植物群落结构与水质评价[J].湖泊科学,2011,23(4):575-580.
[22] 陈悦,刘晶晶,高月鑫,等.三门湾网采浮游植物季节变化及影响因素[J].海洋与湖沼,2017,48(1):101-112.
[23] 王雨,项鹏,叶又茵,等.金门岛北部海域浮游植物的季节变动及与环境的关联[J].水生生物学报,2017,41(3):712-723.
[24] 邓希海.养殖水体中pH值的作用及调节[J].河北渔业,2008(2):4-6.
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[26] 王崇明,张岩,麻次松.对虾池塘浮游植物与主要水质因子的关系[J].海洋科学,1993,17(4):10-12.
[27] 赵先富,于军,葛建华,等.青岛棘洪滩水库浮游藻类状况及水质评价[J].水生生物学报,2005,29(6):639-644.
[28] 胡忠军,莫丹玫,周小玉,等.千岛湖浮游植物群落结构时空分布及其与环境因子的关系[J].水生态学杂志,2017,38(5):46-54.
[29] 任辉,田恬,杨宇峰,等.珠江口南沙河涌浮游植物群落结构时空变化及其与环境因子的关系[J].生态学报,2017,37(22):7729-7740.
[30] 胡俊,郑金秀,池仕运,等.苏皖交界河网区浮游植物群落结构及其与环境因子关系的研究[J].长江流域资源与环境,2017,26(2):282-288.
[2] Verasztó C,Kiss K T,Sipkay C,et al.Long-term dynamic patterns and diversity of phytoplankton communities in a large eutrophic river (the case of River Danube,Hungary)[J].Applied Ecology & Environmental Research,2010,8(4):329-349.
[3] 肖小雨,龙婉婉,柳正葳,等.吉安地区典型景观湖泊浮游植物群落特征及其与水环境因子的关系[J].生态学杂志,2016,35(4):934-941.
[4] 余员龙.千岛湖浮游植物群落结构时空分布格局及其与主要环境因子的关系[D].上海:上海海洋大学,2010.
[5] 赖俊翔,许铭本,庄军莲,等.广西北部湾近岸海域春季浮游植物群落结构特征及与环境因子的关系[J].海洋技术学报,2017,36(6):65-70.
[6] 孙慧慧,刘西汉,孙西艳,等.莱州湾浮游植物群落结构与环境因子的时空变化特征研究[J].海洋环境科学,2017,36(5):662-669.
[7] 秦雪,徐宾铎,杨晓改,等.黄河口及其邻近水域夏季浮游植物群落结构及其与环境因子的关系[J].水产学报,2016,40(5):711-720.
[8] 周彦锋,宋江腾,刘凯,等.怀洪新河浮游植物群落结构与水环境因子的关系研究[J].生态科学,2017,36(1):35-42.
[9] 国家环境保护总局.水和废水监测分析方法[M].北京:中国环境科学出版社,2002.
[10] 陈晓宏.水环境评价与规划[M].北京:中国水利水电出版社,2007.
[11] 胡鸿钧,魏印心.中国淡水藻类——系统、分类及生态[M].北京:科学出版社,2006.
[12] Margalef R.Information theory in ecology[J].General Systems,1958,3(1):36-71.
[13] Shannon C E,Wiener W J.The Mathematical Theory of Communication[M].Urbana:University of Illinois Press,1963:1-65.
[14] Pielou E C.The measurement of diversity in different types of biological collection[J].J Theoretic Biol,1967,15(1):131-144.
[15] Hunter P R,Gaston M A.Numerical index of the discriminatory ability of typing systems:an application of Simpson′s index of diversity[J].J Chin Microbiol,1998,26(11):2465-2466.
[16] 李喆,姜作发,霍堂斌,等.黑龙江中游浮游植物多样性动态变化及水质评价[J].中国水产科学,2012,19(4):671-678.
[17] 陈洋,胡晓东,张建华,等.太湖不同区域浮游植物群落结构特征及其与环境因子的关系[J].水生态学杂志,2017,38(3):38-44.
[18] 李共国,屠霄霞,王佩儿,等.杭州湾滩涂湿地浮游生物群落特征及与环境因子的关系[J].生态学杂志,2013,32(10):2764-2771.
[19] 刘明典,李鹏飞,曾泽国,等.长江干流安庆段浮游植物群落结构特征[J].淡水渔业,2017,47(4):29-36.
[20] 唐毅,郑永华,刘建虎,等.横江中下游春季浮游植物群落结构及多样性分析[J].淡水渔业,2016,46(1):51-58.
[21] 王瑜,刘录三,舒俭民,等.白洋淀浮游植物群落结构与水质评价[J].湖泊科学,2011,23(4):575-580.
[22] 陈悦,刘晶晶,高月鑫,等.三门湾网采浮游植物季节变化及影响因素[J].海洋与湖沼,2017,48(1):101-112.
[23] 王雨,项鹏,叶又茵,等.金门岛北部海域浮游植物的季节变动及与环境的关联[J].水生生物学报,2017,41(3):712-723.
[24] 邓希海.养殖水体中pH值的作用及调节[J].河北渔业,2008(2):4-6.
[25] 赵光强,毕蓉,南春蓉,等.3种赤潮微藻生长过程中pH的变化及其耐受力研究[J].海洋环境科学,2010,29(5):679-682.
[26] 王崇明,张岩,麻次松.对虾池塘浮游植物与主要水质因子的关系[J].海洋科学,1993,17(4):10-12.
[27] 赵先富,于军,葛建华,等.青岛棘洪滩水库浮游藻类状况及水质评价[J].水生生物学报,2005,29(6):639-644.
[28] 胡忠军,莫丹玫,周小玉,等.千岛湖浮游植物群落结构时空分布及其与环境因子的关系[J].水生态学杂志,2017,38(5):46-54.
[29] 任辉,田恬,杨宇峰,等.珠江口南沙河涌浮游植物群落结构时空变化及其与环境因子的关系[J].生态学报,2017,37(22):7729-7740.
[30] 胡俊,郑金秀,池仕运,等.苏皖交界河网区浮游植物群落结构及其与环境因子关系的研究[J].长江流域资源与环境,2017,26(2):282-288.
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