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引用本文:牛海玉,陈纯,韩博平.基于浓缩法的浮游植物定量数据稳定性与可靠性分析.湖泊科学,2015,27(5):776-782. DOI:10.18307/2015.0503
NIU Haiyu,CHEN Chun,HAN Boping.Quality and reliability of quantifying phytoplankton abundance and biomass data based upon the concentrated water sample method. J. Lake Sci.2015,27(5):776-782. DOI:10.18307/2015.0503
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基于浓缩法的浮游植物定量数据稳定性与可靠性分析
牛海玉1, 陈纯1, 韩博平1,2
1.暨南大学生态学系, 广州 510632;2.广东省水库蓝藻水华防治中心, 广州 510632
摘要:
浮游植物是水生生态系统中重要的初级生产者,相对准确地定量它们的数量是进一步进行水质评价和生态功能分析的基础.通过采集处于不同营养状态的水库和不同处理的围隔中的浮游植物,研究影响浓缩法定量浮游植物的因素,了解如何通过浓缩法来合理地定量浮游植物.分析浓缩倍数、样品的显微镜计数量、水体营养状态对浮游植物丰度、生物量及群落多样性等定量参数稳定性的影响,同时比较单个不同水体中重复(或平行)样品之间浮游植物丰度的差别.结果表明,基于浮游植物的显微镜计数效率与定量数据稳定性的综合考虑,选择计数4 片×10格/片即可基本保证定量数据的稳定性;在保证正常镜检的基础上,考虑水体营养状态适当增加浓缩倍数能够提高定量数据的可靠性;在特别依赖生物量或稀有种进行水质评价时,处于不同营养水平的水体均需要增加样品的平行数来提高定量数据的可靠性.
关键词:  浮游植物  计数  丰度  生物量  多样性  浓缩法
DOI:10.18307/2015.0503
分类号:
基金项目:国家重点基础研究发展计划“973”项目(2012CB956104)和广东省水利科技创新项目(201102)联合资助.
Quality and reliability of quantifying phytoplankton abundance and biomass data based upon the concentrated water sample method
NIU Haiyu1, CHEN Chun1, HAN Boping1,2
1.Department of Ecology, Jinan University, Guangzhou 510632, P. R. China;2.Guangdong Center for Protection and Control of Cyanobacterial Blooms in Reservoirs, Guangzhou 510632, P. R. China
Abstract:
Phytoplankton is a main primary producer, especially in pelagic ecosystems. Thus it needs to be well quantified for measuring its function and assessing water quality. To explore data quality of phytoplankton by the concentrated water sample method which has been widely applied in China and other developing countries, phytoplankton samples were collected from three reservoirs with distinct trophic levels and three treatment groups of experimental enclosures. The potential effects of the concentration ratios of water samples, counting volumes, replicates of water samples on the data quality were statistically analyzed. To balance the stability of data and counting efficiency under microscopy, we recommend to count 4 plates ×10 lattices for each plate. In the range of clearly and easily counting, increasing the concentration ratios of the water samples can improve precision and reliability of the quantitative data. When collecting multiple samples for counting is possible, especially those used for assessing the water quality, replicates of water samples are strongly recommended to be collected in order to reduce the standard deviation.
Key words:  Phytoplankton  counting  abundance  biomass  diversity of species  concentrated water sample method
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