scholarly journals Spatial heterogeneity and seasonal succession of phytoplankton functional groups along the vertical gradient in a mesotrophic reservoir

2017 ◽  
Vol 53 ◽  
pp. 129-141 ◽  
Author(s):  
Tuğba Ongun Sevindik ◽  
Kemal Çelik ◽  
Luigi Naselli-Flores
Author(s):  
Xu Sun ◽  
Patteson Chula Mwagona ◽  
Isaac Ekyamba Shabani ◽  
Wenjiu Hou ◽  
Xiaoyu Li ◽  
...  

The present study was carried out in the biggest tributary of Ussuri River of boundary between China and Russia. The Muling River basin has undergone a long-term dredging works, and waterbody became seriously turbid. The succession of phytoplankton functional groups succession and environmental factors in the river were sampled in 2015. We totally identified 83 species, belonging to 17 functional groups which 5 were predominant, including group F, M, MP, P and Y. The seasonal succession of phytoplankton functional groups was M/P-F/MP/P-MP/P. Results of Spearman correlation analysis and canonical correspondence analysis (CCA) revealed that phytoplankton functional groups were mainly influenced by nutrient concentrations and light availability including total nitrogen (TN), ammonium nitrogen (NH4+–N), nitrate nitrogen (NO3−–N), N:P ratio (N:P), water depth (D) and transparency (SD) in the basin.


Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1167 ◽  
Author(s):  
Lingai Yao ◽  
Xuemin Zhao ◽  
Guang-Jie Zhou ◽  
Rongchang Liang ◽  
Ting Gou ◽  
...  

Freshwater phytoplankton communities can be classified into a variety of functional groups that are based on physiological, morphological, and ecological characteristics. This classification method was used to study the temporal and spatial changes in the phytoplankton communities of Gaozhou Reservoir, which is a large municipal water source in South China. Between January 2015 and December 2017, a total of 155 taxa of phytoplankton that belong to seven phyla were identified. The phytoplankton communities were classified into 28 functional groups, nine of which were considered to be representative functional groups (relative biomass > 10%). Phytoplankton species richness was greater in the summer and autumn than in the winter and spring; cyanobacterial blooms occurred in the spring. The seasonal succession of phytoplankton functional groups was characterized by the occurrence of functional groups P (Staurastrum sp. and Closterium acerosum) and Y (Cryptomonas ovata and Cryptomonas erosa) in the winter and spring, and functional groups NA (Cosmarium sp. and Staurodesmus sp.) and P (Staurastrum sp. and Closterium acerosum) in the summer and autumn. The temperature, nitrogen, and phosphorus levels were the main factors driving seasonal changes in the phytoplankton communities of Gaozhou Reservoir. The functional group M (Microcystis aeruginosa) dominated the community during the cyanobacterial blooms in spring 2016, with the maximum algal cell density of 3.12 × 108 cells L−1. Relatively low temperature (20.8 °C), high concentrations of phosphorus (0.080–0.110 mg L−1), suitable hydrological and hydrodynamic conditions (e.g., relatively long retention time), and relatively closed geographic location in the reservoir were the key factors that stimulated the cyanobacterial blooms during the early stages.


2014 ◽  
Vol 40 (4) ◽  
pp. 859-869 ◽  
Author(s):  
Henglun Shen ◽  
Bin Li ◽  
Qinghua Cai ◽  
Qingxiang Han ◽  
Yuan Gu ◽  
...  

Author(s):  
Jing Dong ◽  
Chenlu Li ◽  
Dujuan Dai ◽  
Shuangshuang Yao ◽  
Sen Li ◽  
...  

The concept of phytoplankton functional groups was proposed based on data from numerous European lakes and has been widely used in lakes, reservoirs, rivers worldwide. However, the application of this concept to subtropical plateau lakes has rarely been reported. In this study, 16 sampling sites were selected across the entirety of Lake Fuxian, Yunnan, China. Eighteen phytoplankton functional groups (F, G, J, X2, X1,T, P, MP, D, C, H1, LO, S1, M, Y, E, W1 and W2) were classified according to the investigation of surface water and gradient depth samples. Nine of these groups, namely LO, H1, C, MP, P, T, X1, J and F, were identified as dominant species (>5% total biomass). Furthermore, LO, H1 and T were considered predominant (accounting for the maximum percentage of biomass in each month). The sampling showed that the seasonal succession of predominant assemblages in surface water was T (October) to H1 (January) to H1 (April) to Lo (July) and T+Lo (October) to T (January) to H1 (April) to Lo (July) in the gradient depth water. Redundancy analysis (RDA) combined with the indicator function of the phytoplankton groups suggested that WT and TN/TP were important factors in driving the succession of predominant assemblages all year around.


2018 ◽  
Vol 30 (0) ◽  
Author(s):  
Maria da Conceição de Souza ◽  
Luciane Oliveira Crossetti ◽  
Vanessa Becker

Abstract Aim Our study aimed to evaluate changes in the phytoplankton functional groups brought about by increases in temperature and nutrients predicted by the Intergovernmental Panel on Climate Change (IPCC) scenario for semi-arid regions. Methods Two experiments were performed, one in the rainy season and another in the dry season. The nutrient enrichment was based on the annual mean values (August 2012-August 2013) of soluble reactive phosphorus and nitrate verified in the reservoir. The microcosms were exposed to two different temperatures, the five-year average of air temperature in the reservoir (control) and 4°C above the control temperature (warming). The experiment was conducted over 12 days; every three days water samples of approximately 60 mL in volume were taken from the reservoir for chemical and phytoplankton analysis. All species were classified by Reynolds Functional Groups (RFG). Results The functional groups H1, X1, LO and S1 were the most representative in both seasons (rainy and dry). Our results showed that bloom-forming cyanobacteria, in particular the species of functional groups H1 and M, commonly reported in reservoirs in semi-arid regions of Brazil, were not significantly benefited by the warming and nutrient enrichment. The recruitment of other blue-green species, as well as diatoms and green algae, could be observed. Conclusions The effects of warming and/or nutritional enrichment can change the structure of the phytoplankton community. However, as not expected as the pessimist scenario, in our study the bloom-forming phytoplankton functional groups did not show changes in relative biomass. Instead, the recruitment of diatoms and green algae currently found in enriched environments was verified, specifically in the rainy period, when nutrient dilution typically occurs.


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