Effects of seasonal succession and water pollution on the protozoan community structure in an eutrophic lake

Jiang, Jian-Guo; Wu, Sheng-Gui; Shen, Yin

doi:10.1016/j.chemosphere.2006.05.042

Cited by 74 publications

(53 citation statements)

References 31 publications

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“…Cluster analysis, as one type of multivariate statistics, provide a classification algorithm to link together objects sufficiently similar to each other and then amalgamate successively larger clusters, typically illustrated by the structure of a hierarchical tree with distinct branches (Hansel-Welch et al, 2003;Jiang et al, 2007). Hereby, to characterize the community structures of protozoa with various treatment processes, tree clustering on the amalgamation rule of unweighted pair-group average was conducted.…”

Section: Statistical Analysesmentioning

confidence: 99%

“…By way of compiling and classifying these high-dimensional factors simultaneously, PCA was considered appropriate for recovering a vector space of lower dimension and displaying the important information derived from the measured data compacted in a complex data set (Kalin et al, 2001;Yoo et al, 2003;Hansel-Welch et al, 2003;Jiang et al, 2007). Furthermore, to facilitate its visual interpretability, via the correlation matrix of active variables, 2D plots of factor coordinates were produced in this paper.…”

Section: Statistical Analysesmentioning

confidence: 99%

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Comparative study of protozoan communities in full-scale MWTPs in Beijing related to treatment processes

Liu

Yang

et al. 2008

Water Research

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Community structure Municipal wastewater Treatment processCluster analysis Principal components analysis a b s t r a c tThe potential influence of process principles and system conditions on shaping protozoan community structures in eight full-scale municipal wastewater treatment systems in Beijing, including four process types, i.e., anaerobic/anoxic/aerobic or anoxic/anaerobic/ aerobic process (A2O), anoxic/aerobic or anaerobic/aerobic process (AO), oxidation ditch (OD) and sequencing batch reactor (SBR), was evaluated with the aid of cluster analysis and principal components analysis (PCA). The species richness and abundance distribution of protozoa varied significantly with the process types: the A2O ecosystems harbored more diverse protozoan communities with higher relative abundance of crawling and sessile ciliates than the other systems. Cluster analysis revealed that the protozoan community structures were in high coordination with the process types, i.e., different systems with the same process principles exhibited similar community structures. The A2O processes displayed a distinctively higher similarity of protozoan community structures than the AO processes, suggesting that the A2O ecosystems were more stable than those of AO. The PCA analyses demonstrated that swimming and carnivorous ciliates were correlated with poor settleability of sludge, and that amoebae were sensitive to DO level. We therefore concluded that protozoan community structures were primarily shaped by treatment process principles, whilst they were also modified by system conditions in terms of operational properties and water quality.

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Section: Statistical Analysesmentioning

confidence: 99%

Section: Statistical Analysesmentioning

confidence: 99%

Comparative study of protozoan communities in full-scale MWTPs in Beijing related to treatment processes

Liu

Yang

et al. 2008

Water Research

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“…It has been considered a better index for depicting the response of a phytoplankton community to environmental change than the commonly used biodiversity indices (Jiang and Shen, 2003). The CPV index has been used to monitor and evaluate freshwater pollution in River Wulong, Lake Jiajiahu, River Hanjiang and Lake Donghu in China (Jiang and Shen, 2005;Jiang, 2006;Jiang et al, 2007). We adopted CPV index in this study to analyze the influence of species compositional change on community structure and function of a freshwater phytoplankton.…”

Section: Introductionmentioning

confidence: 99%

A comparative study of the impact of species composition on a freshwater phytoplankton community using two contrasting biotic indices

Guo

Liu

et al. 2010

Ecological Indicators

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“…These techniques should be employed together because they are subject to different sources of distortion (Jiang et al, 2007). The use of ordination techniques has provided insights into the temporal changes in phytoplankton communities (Bettinetti et al, 2000), and NMDS has proved to be a useful tool for this purpose, allowing reliable identification and description of pathways in the chronological succession of phytoplankton (Salmoso, 1996;Bettinetti et al, 2000).…”

Section: Discussionmentioning

confidence: 99%

Temporal changes of phytoplankton community at different depths of a shallow hypertrophic reservoir in relation to environmental variables

Kwon

Hwang

Park

et al. 2009

Ann. Limnol. - Int. J. Lim.

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-We characterized phytoplankton community succession at different depths of a shallow hypertrophic reservoir in relation to physical and chemical environmental variables. The phytoplankton community was sampled biweekly at three different water depths (surface, middle and bottom) in the reservoir from November 2002 to February 2004. A range of 18 environmental variables including temperature, electrical conductivity (EC), total phosphorus (TP) and total nitrogen (TN) were measured to assess their influence on phytoplankton community succession. As well, combined multivariate analyses with a cluster analysis and a nonmetric multidimensional scale (NMDS) were conducted. Microcystis aeruginosa was the dominant species in all seasons except spring. Thus, Cyanophyceae was a dominant taxonomic group. In spring, Bacillariophyceae dominated, followed by Cryptophyceae and Chlorophyceae. The succession was relatively delayed at the middle and bottom layers compared with at the surface layer. Abundance and species richness of phytoplankton were also higher in the surface layer than in the bottom layer. Cluster analysis classified the phytoplankton community into four clusters at each depth, and the changes were also well reflected in the NMDS ordination. Each cluster showed seasonal patterns characterized by indicator species, as well as environmental variables such as temperature, conductivity, and nutrients including N and P. Seasonal dynamics of the phytoplankton community was the strongest at the surface layer and weakest at the bottom layer. These depth-variable environmental variables are likely to be the key factors driving changes in the phytoplankton community composition.

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Effects of seasonal succession and water pollution on the protozoan community structure in an eutrophic lake

Cited by 74 publications

References 31 publications

Comparative study of protozoan communities in full-scale MWTPs in Beijing related to treatment processes

Comparative study of protozoan communities in full-scale MWTPs in Beijing related to treatment processes

A comparative study of the impact of species composition on a freshwater phytoplankton community using two contrasting biotic indices

Temporal changes of phytoplankton community at different depths of a shallow hypertrophic reservoir in relation to environmental variables

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