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引用本文:张又,蔡永久,张颖,高俊峰,李宽意.河流大型底栖动物对环境压力的响应:以太湖、巢湖流域为例.湖泊科学,2021,33(1):204-217. DOI:10.18307/2021.0111
Zhang You,Cai Yongjiu,Zhang Ying,Gao Junfeng,Li Kuanyi.The response of benthic macroinvertebrate communities to environmental pressures in streams and rivers: A case study of Taihu and Chaohu Basins. J. Lake Sci.2021,33(1):204-217. DOI:10.18307/2021.0111
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河流大型底栖动物对环境压力的响应:以太湖、巢湖流域为例
张又1, 蔡永久1, 张颖2, 高俊峰1, 李宽意1,3
1.中国科学院南京地理与湖泊研究所, 湖泊与环境国家重点实验室, 南京 210008;2.江苏省水利工程规划办公室, 南京 210029;3.中国科学院大学中丹学院, 北京 100049
摘要:
为了解河流大型底栖动物对环境压力的响应关系,以人类干扰程度不同的太湖流域和巢湖流域为研究区,系统调查区域内河流大型底栖动物,结合水体、沉积物理化数据及生境质量状况,运用空间分析和多元统计分析等方法,探讨了大型底栖动物多样性及典型物种对关键环境因素的响应规律.结果表明,太湖流域和巢湖流域的环境质量和大型底栖动物群落结构均差异较大,巢湖流域的生境质量优于太湖流域,巢湖流域平原区部分点位的水体营养盐(特别是氮浓度)高于太湖流域平原区.巢湖流域丘陵区的敏感型物种(主要为水生昆虫)密度远高于太湖流域丘陵区,太湖流域丘陵区的耐污型物种(寡毛纲)平均密度稍高于巢湖流域丘陵区,而巢湖流域平原区的寡毛纲霍甫水丝蚓(Limnodrilus hoffmeisteri)和苏氏尾鳃蚓(Branchiura sowerbyi)平均密度远高于太湖流域平原区.广义加性模型建立的响应关系曲线表明,栖境多样性和总氮浓度可以作为生物多样性的指示因子.铜锈环棱螺(Bellamya aeruginosa)、椭圆萝卜螺(Radix swinhoei)、河蚬(Corbicula fluminea)、霍甫水丝蚓、苏氏尾鳃蚓、黄色羽摇蚊(Chironomus flaviplumus)等特征物种与特定环境因子的响应关系显著,这些物种也可以作为环境监测的指示物种.底栖动物-环境梯度的响应曲线能够定量地描述底栖动物群落对环境因子的响应关系,有利于深入了解水体水质、营养状态及生境质量与大型底栖动物群落结构的相关关系,进而预测不同人为干扰下大型底栖动物群落结构的变化趋势和演替过程.
关键词:  太湖流域  巢湖流域  大型底栖动物  响应曲线  广义加性模型
DOI:10.18307/2021.0111
分类号:
基金项目:国家自然科学基金项目(31930074,32001156,31670466)、中国科学院科技服务网络计划区域重点项目(KFJ-STS-QYZD-156)、江苏省水利科技项目(2018003)和中国科学院南京地理与湖泊研究所引进人才启动项目(NIGLAS2019QD02)联合资助.
The response of benthic macroinvertebrate communities to environmental pressures in streams and rivers: A case study of Taihu and Chaohu Basins
Zhang You1, Cai Yongjiu1, Zhang Ying2, Gao Junfeng1, Li Kuanyi1,3
1.State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P. R. China;2.Water Resources Planning Bureau of Jiangsu Province, Nanjing 210029, P. R. China;3.Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
Abstract:
This study seeks to clarify the response of benthic macroinvertebrate communities to environmental pressures in streams and rivers, and two regions with different degrees of human disturbance, i.e. Taihu Basin and Chaohu Basin, were chosen as the study area. Benthic macroinvertebrate communities in these two regions were investigated, as well as the physicochemical conditions of the water and sediment and habitat condition. Spatial analysis and multivariate statistical analysis were used to explore how macroinvertebrates respond to the environmental variables. The results showed that the environmental quality and the benthic macroinvertebrate communities were significantly different in these two basins, indicating that different disturbance intensities had different effects on the ecological environment and benthic macroinvertebrates. The habitat quality of Chaohu Basin was better than that of Taihu Basin. Besides, nutritional concentrations in the plain area of Chaohu Basin, especially the nitrogen concentration were higher than that in the plain area of Taihu Basin. The hilly area of Chaohu Basin has more sensitive species (e.g. aquatic insects) and less pollution-tolerant species (e.g. oligochaetes) than Taihu Basin, and the plain area of Chaohu Basin has much higher abundance of oligochaetes (mainly Limnodrilus hoffmeisteri and Branchiura sowerbyi) than Taihu Basin. Based on generalized additive model, response curves showed that habitat diversity and total nitrogen can be used as indicators for taxa richness and biodiversity. Characteristic species, such as Bellamya aeruginosa, Radix swinhoei, Corbicula fluminea, L. hoffmeisteri, B. sowerbyi, Chironomus flaviplumus, could be used as environmental monitoring indicators due to their response to specific environmental factors. The response curves can reveal the relationship between benthic macroinvertebrate communities and water quality, nutritional status and habitat quality, which can be used to predict benthic macroinvertebrate communities and succession process under different human disturbances.
Key words:  Taihu Basin  Chaohu Basin  benthic macroinvertebrate  response curves  generalized additive models
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