珠三角河网浮游植物生物量的时空特征
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中国水产科学研究院珠江水产研究所,中国水产科学研究院珠江水产研究所,中国水产科学研究院珠江水产研究所,中国水产科学研究院珠江水产研究所,中国水产科学研究院珠江水产研究所,中国水产科学研究院珠江水产研究所,中国水产科学研究院珠江水产研究所

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全国渔业环境监测网珠江生态监测与评价项目(2009-);广东省海洋渔业科技专项(A2011009);广西省自然科学基金重大项目(2013GXNSFEA053003)


Temporal and spatial pattern of the phytoplankton biomass in the Pearl River Delta
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Pearl River Fisheries Research Institute,Chinese Academy of Fishery Science,,Pearl River Fisheries Research Institute,Chinese Academy of Fishery Science,,,,

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    摘要:

    珠三角河网水域是珠江之水流入南海的必经之地,对2012年该水域浮游植物生物量的时空特征及其影响因素进行系统阐析。调查期间共发现浮游植物7门,383种(包括变种、变型),其中硅藻和绿藻是最主要类群,其次是裸藻和蓝藻。颗粒直链藻原变种是调查水域的本底物种,也是最优势种;而变异直链藻和网球藻分别是枯水季节和丰水季节的指示物种。从季节变动看,浮游植物总生物量呈现枯水季节高、丰水季节低的特征,主要与径流导致的稀释作用和透明度升高引发的沉降损失有关。从空间分布看,总生物量呈现自西南向东北升高的趋势,主要与营养盐的空间分布格局有关,而且空间分布格局无季节差异。从不同类群的相对组成上看,硅藻占据绝对优势地位,绿藻和裸藻次之,这与20世纪80年度初的调查结果基本一致。硅藻在枯水季节占据绝对优势地位,而在丰水季节由于绿藻和裸藻优势的明显增大,导致硅藻的优势下降,这与流域中一些死水区域如水库、浅滩中的蓝绿藻和裸藻在丰水期涌入干流有关,PCA分析结果也证明了这一点。此外,不同站位在相对组成上的季节变动还受盐度的影响。综上,物理因子包括与径流相关的稀释作用和与透明度相关的沉降损失不仅影响总生物量的季节变动,也影响不同类群的相对组成;而化学因素如营养盐含量是决定总生物量空间分布的关键因素,与河口潮汐作用相关的盐度变化对类群相对组成的空间分布起到一定的影响作用。

    Abstract:

    To test the hypothesis that species composition and persistence of phytoplankton communities in nutrient rich lowland rivers mainly depended on physical factors, the temporal and spatial patterns of the phytoplankton biomass were studied seasonally in the Pearl River Delta during 2012a. And its correlation with physical and chemical variables was analyzed to evaluate the key factors and then to display the interaction mechanisms. Samples were differentiated by nutrient level using self-organizing map (SOM), and two apparent different water qualities were found in the present finding. One was characterized by worse than level Ⅴ of water quality and mainly composed by Zhujiangqiao、Lianhuashan and Shiqiao where located near Guangzhou city, and the other was characterized by falling between level Ⅱ and Ⅳ of water quality and composed by the other sites. During the investigation, the 383 taxonomic species (including variant and derivative) from 7 groups were identified. The results showed that the diatom (Bacillariophyaceae) and Chlorophytes were most abundant and they were 41.78% and 29.24% to the total numbers, respectively. The Euglenophyta and Cyanobacteria were subsidiary. This structure pattern was similar to that of the downstreams of Xijiang River and other large rivers in the world. 39 dominant species were listed in Table 2, and Aulacoseira was the base member of phytoplankton communities around the studied area, for its domination throughout the whole year. Only 3 species showed both high biomass contribution and high occurrence, and Aulacoseira granulata var. granulata was predominant, and the benthic diatom Melosira varians and lentic green algae Dictyosphaeria cavernosa were indicator species of drought period and flood period respectively. Seasonal distribution patterns of total biomass were high in drought period and low in flood period, which was mainly related to the dilution by water flow and the sedimentation lost accompanied with high transparency. The spatial distribution pattern showed increasing trend from southwest to northeast, which was in accordance with the spatial pattern of nutrient level and the spatial pattern did not show seasonal difference. For the relative contribution of different groups, diatom was predominant and contributing 80.56% to the total biomass, Chlorophytes and Euglenophyta were subsidiary. Diatom seasonally predominated in drought period, but it was challenged by Chlorophytes and Euglenophyta in flood period since their influx into main stream from dead zones, such as reservoirs and shallow waters in the river basins. PCA analysis also showed that Chlorophytes and Euglenophyta were not correlated with nutrients but chemical factors. In addition, seasonal variations of relative contribution in different sites were also influenced by salinity. In conclusion, physical factors, including water flow and transparency, could not only influence the seasonal variations of the total phytoplankton abundance, but also impact the relative contribution of different groups in the community, while chemical factors mainly determined the spatial distribution pattern. In addition, salinity could also affect the communities of several sites.

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王超,李新辉,赖子尼,曾艳艺,高原,刘乾甫,杨婉玲.珠三角河网浮游植物生物量的时空特征.生态学报,2013,33(18):5835~5847

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