Community Structures Of Phytoplankton And Comparison On Them Between Two Identification Methods In Lake Qiandaohu

Temporal variations of phytoplankton community structure are of great significance for water ecosystem stability, which is affected by various natural and non-natural factors. Four seasons are relatively distinct in subtropical regions, algae is affected by season and shows obvious succession. However, due to geographical differences, differences are more obvious in different water bodies, even if at the same water inlet, central area and the outlet, also showed some spatial differences in different hydrological environment. For Lake Qiandaohu which is a deep and mountain-valley type reservoir and Environment Protection Oriented Fishery(AEPO) was carried out, its special conditions will inevitably lead to changes in algal community structure different from other lakes, and the impact of environmental factors on algae may also have difference. In this study, the changes in phytoplankton community between different sampling sites were analyzed and the relevant research was done with environmental factor in Lake Qiandaohu during 2013-2014. It provides data accumulation for the long-term monitoring of ecosystems in Lake Qiandaohu, but also data support for Environment Protection Oriented Fishery to implement successfully. Microscopy and high-throughput sequencing on algae were done respectively in this study during May to December, 2010, and analysis of the differences between the two methods was also made. The purpose is to explore that whether the high-throughput sequencing method is suitable for the research of phytoplankton community, and provide theoretical support for the application.The main results and conclusions are as follows:1. Monthly monitoring on phytoplankton in Lake Qiandaohu during 2013-2014, a total of 363 taxa of planktonic algae was recorded, which belonged to 107 genera of 8 phyla(include deformation and variation of algae). The primary phyla were Cyanophyta(18 genera and 42 species), Chlorophyta(47 genera and 155 species) and.Bacillariophyta(28 genera and 129 species). S1 has the most abundant number, followed by the S4, addition is S9, mixing the sample points the minimum number of species in S3 and S8(which are mixed sample points). Chlorophyta species is the largest, followed by Bacillariophyta and Cyanobacteria at each site. The total dominant species of the two years were 19 species(9 species in Cyanophyta, 2 species in Chlorophyta, 7 species in Bacillariophyta, and 1 species in Cryptophyta), and the species with relative high dominance in 2013 were Anabaena flos-aquae and Cyclotella meneghiniana, in 2014 were Lyngbya limnetica and Anabaena flos-aquae. The mean values of phytoplankton biomass and density were 15.54±2.31mg/L and 5153.95±130.81×104cell/L(for 2013: 6.62±1.93mg/L and 203.51±75.72×104cell/L; for 2014: 24.45±5.21mg/L and 8244.39±1163.10×104cell/L). Vertical variation of biomass and density had differences in two years(2013: showed a slow decrease with depth, 2014: presented a brief rise at 0-8m depth and fall rapidly after 8m).2. Water temperature showed significant periodicity, the highest in summer and peaked in August and September, the lowest in winter, and the emergence of the lowest value in February in Lake Qiandaohu. The highest value of dissolved oxygen in March, the lowest in September in 2013, and the amount of dissolved oxygen is more stable, does not appear significantly higher and lower in 2014. Since the fast perennial flow speed, high content of water sediment, organic matter and other suspended solids, transparency is significantly lower than other sites, and less all the year round in S1(outfall). Transparency(SD) is at a minimum on August, and below average in 2014. Concentration of TN(1.37 ± 0.015), TP(0.03 ± 0.001) and CODMn(1.38 ± 0.013) were significantly higher in S1 compared with other sites, and with the direction of flow tended, the content decrease(S1> S3> S4> S8> S9). Seasonal variation of algae biomass and density were significantly positively correlated with transparency(R = 0.637, R = 0.646), water temperature(R = 0.592, R = 0.607) and CODMn(R = 0.772, R = 0.789) in Lake Qiandaohu. Cyanophyta, Chlorophyta, and Bacillariophyta showed significant correlation with SD, water temperature and CODMn. Besides, the density ratio of Bacillariophyta was correlated with ammonia nitrogen(NH3-N)(R=0.459,P<0.05), the density ratio of Chlorophyta was correlated with TN(R=0.471,P<0.05). In spatial distribution of each sampling sites, biomass and density of algae were associated with SD, water temperature and CODMn in S3, S4, S8 and S9, and S1 only showed a correlation with temperature(R = 0.482, P <0.05; R = 0.516, P <0.05). Furthermore a significant positive correlation with the density and TN(R = 0.492, P <0.01) in S4, and biomass, density and total nitrogen present a significant positive correlation with ammonia nitrogen(R = 0.492, P < 0.01) in S8. Biomass and density but also has a significant positive correlation with NO3--N and NH3-N(R = 0.472, R = 0.511; R = 0.534, R = 0.506), and the density has a significant positive correlation with TP(R = 0.424, P <0.05) in S9.3. Planktonic algae samples were identified respectively with high-throughput sequencing and microscopy during May to December, 2010. The sequencing results identified eight phyla of algae which Cyanophyta is largest(62%), a total of 63 taxa of planktonic algae, with the most species in Chlorophyta(23), 16 species in Cyanophyta, 10 species in Bacillariophyta; the total dominant species were 5 species and the species with relative high dominance was Cyanobium sp. Microscopy results identified eight phyla of algae and the primary phyla were Cyanophyta(41%), Bacillariophyta(32%) and Chlorophyta(23%); a total of 86 taxa of planktonic algae, with the most species in Chlorophyta(40), 21 species in Bacillariophyta, 16 species in Cyanophyta; the total dominant species were 8 species and the species with relative high dominance was Anabaena flos-aquae. By contrast, the two identification results have a significant difference. That the high-throughput sequencing method is stable to save time, does not rely on the integrity of the sample and can identify the species which cannot be cultured separately. In addition to these advantages, the algae samples cannot be qualitative and quantitative at the same time, and there is a big difference with the examination results comparing with the results of microscopy method.