The seasonal and spatial variations of phytoplankton community and their correlation with environmental factors in a large eutrophic Chinese lake (Lake Chaohu)

Jiang, Yu-Jiao; He, Wei; Liu, Wenxiu; Qin, Ning; Ouyang, Haibin; Wang, Qingmei; Kong, Xiangzhen; He, Qing; Yang, Chen; Yang, Bin; Xu, Fu-Liu

doi:10.1016/j.ecolind.2014.01.006

Cited by 222 publications

(117 citation statements)

References 18 publications

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“…The most extensive bloom coverage occurred in August and September, after which the blooms receded to the northern area of the west lake section. The elevated algal bloom coverage in the west section is consistent with the results of the distribution of pigments and nutrients [13,14]. The western region of Lake Chaohu is near the city of Hefei, which is the capital of Anhui Province, where elevated population and industry activities are present.…”

Section: Bloom Frequencysupporting

confidence: 73%

“…In the 1980s, cyanobacterial blooms occurred throughout the lake from May to November each year [10]. The cyanobacteria were up to 98.8% of total phytoplankton biomass in 1984 [11], 94.4% in 1987-1988 [10], 88.7% in 2002-2003 [12,13], 99.4% in 2011-2012 [14], and 99.3% in 2012-2013 (authors' unpublished data). As a result of increasing eutrophication and the reoccurrence of cyanobacteria-dominated blooms, the water supply for Hefei City was changed to Dongpu Reservoir in 2007 [9].…”

Section: Introductionmentioning

confidence: 99%

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Fourteen-Year Record (2000–2013) of the Spatial and Temporal Dynamics of Floating Algae Blooms in Lake Chaohu, Observed from Time Series of MODIS Images

Zhang

et al. 2015

Remote Sensing

106

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Abstract:As the fifth largest freshwater lake in China, Lake Chaohu has drawn increasing attention due to the decline in water quality and the occurrence of massive algal blooms. We applied an algae pixel-growing algorithm to MODIS Terra or Aqua data (2100 images) to characterize surface floating algae bloom dynamics from 2000 to 2013 with respect to meteorological and lake nutrient conditions. The results show an increase in surface algal bloom coverage, frequency, and duration with a trend toward earlier bloom formation. Importantly, spatial and temporal patterns in the historically less compromised eastern and middle lake areas show that water quality conditions are deteriorating. This has occurred at the same time as lake management has made a catchment scale effort to reduce impact. Our results show that nutrient concentrations were not the main driver of inter-annual bloom variations. Local meteorological conditions, in particular wind speed and temperature, played an important role in the dynamics of floating algal bloom. This highlights the important challenges for lake management.

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Section: Bloom Frequencysupporting

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Fourteen-Year Record (2000–2013) of the Spatial and Temporal Dynamics of Floating Algae Blooms in Lake Chaohu, Observed from Time Series of MODIS Images

Zhang

et al. 2015

Remote Sensing

106

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“…The higher density and biomass of phytoplankton in summer could be attributed to the higher water temperature and the deterioration of water quality (Table 3), and a similar result was obtained in Lake Chaohu [29]. This indicated that the density and biomass of phytoplankton made a rapid response to the variation of water quality.…”

Section: Seasonal Variations Of Plankton and Zoobenthos In 2015supporting

confidence: 68%

Differentiated Responses of Plankton and Zoobenthos to Water Quality Based on Annual and Seasonal Analysis in a Freshwater Lake

Jin

Miao

et al. 2017

Pol. J. Environ. Stud.

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In order to reveal the differentiated responses of plankton and zoobenthos to water quality on both annual and seasonal time scales, an ecological study on plankton and zoobenthos community was conducted during 2011 to 2015 in Nansi Lake in northern China. Different dynamics were found among phytoplankton, zooplankton, and zoobenthos in terms of density, biomass, and biodiversity. On an annual time scale and with deterioration of water quality, density and biomass of plankton and zoobenthos showed different variations, while phytoplankton (density, biomass, and biodiversity) changed significantly when water quality improved. On a seasonal time scale, density and biomass of phytoplankton showed significant differences between spring and summer. Results of Pearson's correlation analysis revealed that phytoplankton, zooplankton, and zoobenthos were significantly affected by different environmental factors. Our study demonstrated that phytoplankton was more sensitive to water quality changes than zooplankton and zoobenthos. These results suggest that density and biomass of phytoplankton could rapidly reflect water quality, whereas biodiversity of phytoplankton could indicate long-term status of water quality combined with the physico-chemical parameters of water. The results could contribute to predicting the dynamics of plankton and zoobenthos in freshwater lakes and to selecting effective bio-indicators for ecosystem health assessment of freshwater lakes.

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“…It perturbs ecosystem services of the aquatic systems and decreases biodiversity [3][4][5]. The total amount of phytoplankton in a sample is a good biological indicator of the trophic state since algae are ubiquitous, abundant and respond quickly to environmental changes in the ecosystem [6][7][8][9]. But the total amount of algal provides little information regarding the processes governing their spatial and temporal distribution.…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Variations in Environmental Variables in Relation to Phytoplankton Community Structure in a Eutrophic River-Type Reservoir

Zhao

Jiao

et al. 2017

Water

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This study assesses spatial and temporal variation in environmental variables in relation to phytoplankton community size and composition in a typically eutrophic river reservoir (Hai River, northern China). The aim is to identify environmental parameters governing spatial and temporal differences in phytoplankton density and composition. Physicochemical parameters, including nutrient concentrations, were determined in monthly surface water samples from 2015. The average concentration of key eutrophication indexes (i.e., total phosphorous (TP: 0.24 ± 0.11 mg·L −1 ), total nitrogen (TN: 2.96 ± 1.60 mg·L −1 ), and Chlorophyll a (Chl a: 38.5 ± 11.5 mg·m −3 )) substantially exceeded threshold values for eutrophic streams. Moreover, the eutrophication increased significantly downstream along the river reservoir as a consequence of an increasing fraction of agricultural and industrial land-use in the watershed. 103 phytoplankton species were identified, of which Chlorophyta was the dominated phylum (47 species), followed by Bacillariophyta (23 species) and Cyanophyta (18 species). No spatial difference in species distribution (ANOVA, p > 0.05) were found, while the temporal differences in species composition exhibited significant heterogeneity (ANOVA, p < 0.001). Phytoplankton abundance was highest in early summer (June and July), with maximum values increasing from 1.78 × 10 8 and 2.80 × 10 8 cells·L −1 in upstream and middle reaches, respectively, to 4.18 × 10 8 cells·L −1 furthest downstream. Cyanophyta, also known as Cyanobacteria and commonly referred to as blue-green algal, are known to constitute algae bloom in eutrophic systems. Common species are Microcystis marginata, Microcystis flos-aquae, and Oscillatoria sp. This was the dominant phyla during summer months, especially in the middle and lower reaches of the stream reservoir where it accounted for 88.9% of the phytoplankton community. Shannon weaver index (H') and Pielous's evenness index (J') were extremely low (1.91-2.43 for H' and 0.39-0.45 for J') in samples collected from the lower part of the stream during the period of algal bloom, indicating an imbalance in the phytoplankton communities. Canonical correspondence analysis (CCA) indicated that water temperature (WT) and possible pH, along with nitrate (NO 3 -N) and nitrite (NO 2 -N), were the most important explanatory parameters in regard to phytoplankton composition. This research provides an understanding of the role of physicochemical water quality parameters in governing algal blooms and phytoplankton composition in river reservoirs.

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The seasonal and spatial variations of phytoplankton community and their correlation with environmental factors in a large eutrophic Chinese lake (Lake Chaohu)

Cited by 222 publications

References 18 publications

Fourteen-Year Record (2000–2013) of the Spatial and Temporal Dynamics of Floating Algae Blooms in Lake Chaohu, Observed from Time Series of MODIS Images

Fourteen-Year Record (2000–2013) of the Spatial and Temporal Dynamics of Floating Algae Blooms in Lake Chaohu, Observed from Time Series of MODIS Images

Differentiated Responses of Plankton and Zoobenthos to Water Quality Based on Annual and Seasonal Analysis in a Freshwater Lake

Spatial and Temporal Variations in Environmental Variables in Relation to Phytoplankton Community Structure in a Eutrophic River-Type Reservoir

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