Green algae outcompete cyanobacteria in a shallow lake, Longhu Lake

Cyanobacterial blooms, a global environmental issue, widely occur in various freshwater, leading to the depletion of dissolved oxygen, the deterioration of water quality, and severe disruption of ecosystem functions (Briland et al. 2020; Amorim & Moura 2021). The algal toxins released by cyanobacteria have seriously affected the safety of the water supply and the health of urban residents worldwide (Olokotum et al. 2020). Green algae (Chlorophyte), also widely distributed in various freshwater, are the food of aquatic animals and do not produce algal toxins (Paerl et al. 2001). Compared with cyanobacteria, green algae are more healthy algal communities. Green algae and cyanobacteria have similar favorable growth conditions, and they are natural competitors (Jensen et al. 1994; Yang et al. 2018). Using green algae to inhibit cyanobacteria is a potential environmentally friendly strategy to control cyanobacterial blooms. However, the strategy is only at the stage of imagination. Understanding the competitive mechanism between green algae and cyanobacteria and the conditions favoring the dominant growth of green algae is an important prerequisite to realizing this strategy.

It is commonly believed that temperature, nitrogen and phosphorus nutrients, nitrogen to phosphorus ratio, and water depth are important factors affecting the shift of dominance between cyanobacteria and green algae. Green algal blooms usually occur at a water temperature of 20–32 °C (Zhou et al. 2019), and the optimal water temperature of cyanobacteria is 25–35 °C (Paerl & Huisman 2008). The lakes or reservoirs with deep water have higher water stability, which is easy to form the vertical stratification of water temperature in summer (Anderson et al. 2021). Cyanobacteria, especially Microcystis, take advantage of the vertical stratification to form dominance and bloom in summer (Paerl & Huisman 2008), while green algae are more likely to become dominant algae and form blooms in shallow non-stratified lakes (Jensen et al. 1994). Nitrogen and phosphorus nutrients are important triggers causing algal blooms (Huisman et al. 2018). Cyanobacteria like to grow in water with higher phosphorus and low nitrogen to phosphorus (N/P) ratio, while green algae prefer to grow in water with low silicon and high N/P ratio (Smith 1983). Smith found that when N/P < 29, cyanobacteria are easy to form dominant advantages and bloom; when N/P > 29, green algae easily become the dominant algae (Smith 1983). So the N/P ratio is considered to be an important factor affecting the dominant succession of cyanobacteria and green algae. However, some studies indicate that the N/P ratio cannot perfectly explain the dominant shift from cyanobacteria to green algae under different water quality conditions. Green algae is the first dominant algae in some eutrophic-hypertrophic shallow lakes even under conditions favoring the growth of cyanobacteria with a low N/P ratio (Jensen et al. 1994; Zhou et al. 2019). The absolute concentration of nitrogen and phosphorus has a greater impact on Microcystis aeruginosa (cyanobacteria) and Scenedesmus obliquus (green algae) than the N/P ratio, and green algae grow more rapidly than cyanobacteria in water with higher nitrogen and phosphorus (Xu et al. 2011). Although we understand the growth characteristics of cyanobacteria and green algae, we still lack knowledge of the competition mechanism between them.

Quantitative polymerase chain reaction (qPCR) is a molecular quantitative method that adds fluorescent molecules to the PCR reaction system. It has been widely used in the quantitative analysis of cyanobacteria and other algae (Fortin et al. 2010). qPCR has the advantages of accurate quantification, less pollution, and high throughput (Heid et al. 1996). There are seven common phyla of algae in freshwater, including Cyanophyta, Chlorophyta, Euglenophyta, Diatoma, Dinoflagellata, Cryptophyta, and Chrysophyta (Zhang et al. 2019; Zhang et al. 2021). In our previous study, we established a quantitative analysis method of seven phyla of common freshwater algae based on qPCR, which was used as a useful tool for quantifying algal density in lakes and reservoirs (Li et al. 2022). The standard curves of qPCR were established with genomic DNA extracted from pure cultured algae with known cell density, which was counted by a light microscope. The qPCR results are the algal cell density of the actual sample in cells/mL.

We know less about the competitive mechanism between green algae and cyanobacteria and the conditions favoring the dominant growth of green algae in shallow lakes. Our purpose is to try to find the answer to explain why green algae have a competitive advantage over cyanobacteria in shallow lakes. In this study, we used qPCR to quantify the cell density of green algae, cyanobacteria, and other phyla of freshwater algae in Longhu Lake, to monitor the dynamics of cyanobacteria and green algae. Longhu Lake, a shallow non-stratified lake in Jinjiang City, China, is the drinking water source for local people in Jinjiang City and Kinmen, Taiwan (Zeng 2016). In recent years, eutrophication in Longhu Lake has been increasing, and the risk of algal blooms has increased sharply. Longhu Lake was chosen as the study area to identify conditions favoring the dominating growth of green algae in shallow lakes. The relationship between algal cell density and water quality factors in Longhu Lake was analyzed through correlation analysis and redundancy analysis (RDA), which could help to confirm the key environmental factors affecting the competition between green algae and cyanobacteria. The results of this study could improve our understanding of the mechanism of green algae dominating cyanobacteria in shallow lakes.

Longhu Lake is located in the subtropical marine monsoon climate zone and is easily affected by typhoon surges in summer and autumn, and typhoons often land in midsummer. The annual average temperature is 24 °C, the monthly average maximum temperature is 28.3 °C, and the monthly average minimum temperature is 11.9 °C. The annual average wind speed is 3.9 m/s, and the maximum wind speed is 27 m/s. Affected by the subtropical monsoon, the precipitation is concentrated in the flood season from April to September, accounting for about 75% of the whole year. The dry season is from October to March in Longhu Lake.

A total of four sampling sites were set up in Longhu Lake, which was located at the Yinglin water pump station (L1), the Longhu water pump station (L2), the center of the reservoir (L3), and the end of the reservoir (L4) (Figure 1). From June 2016 to August 2017 (14 months), 5 L of water samples were collected with a water sampler on the water surface (at a depth of 0.5 m) at each sampling site at the same period (13:00–15:00) of a day once a month. Water temperature, pH, and DO were measured on-site using a multi-parameter water quality analyzer (WTW, Germany, Multi 3420). The water samples were shipped to the laboratory within 3 h. Three hundred milliliters of each water sample was filtered through a 0.45 μm mixed cellulose ester (MCE) filter membrane (Jinteng, China) with the triplicate, which was stored at −80 °C before DNA extraction. The total DNA of water samples was used to measure the cell density of seven phyla of freshwater algae, including Chlorophyta, Cyanophyta, Bacillariophyta, Dinophyta, Chrysophyta, Cryptophyta, and Euglenophyta. The rest water samples were used for the determination of the water quality indexes, including ammonia nitrogen (⁠-N), total organic nitrogen (TON), nitrate nitrogen (⁠-N), nitrite-nitrogen (⁠-N), total nitrogen (TN), TP, total organic carbon (TOC), chlorophyll-a (Chl-a), permanganate index (COD_Mn), turbidity (TUB), and chromaticity (Chroma), according to the Chinese standard methods (Wei et al. 2002). The standard limit of TP, TN, and ammonia nitrogen is 0.025, 0.5, and 0.5 mg/L, respectively, according to the standard limit of Class II water in ‘Environmental quality standards for surface water (GB3838-2002)’ in China (MEEC 2002).

Scenedesmus obliquus FACHB-12 (Chlorophyta), Microcystis sp. 7806 FACHB-915 (Cyanophyta), Cyclotella meneghiniana FACHB-1031 (Bacillariophyta), Peridinium umbonatum var. inaequale FACHB-329 (Dinophyta), Synura sp. FACHB-1977 (Chrysophyta), Cryptomonas obovata FACHB-1301 (Cryptophyta), and Euglenophyta gracilis FACHB-848 (Euglenophyta) were selected as the standard reference algae for seven phyla of common freshwater algae (Li et al. 2022). The cell number of algae was counted by light microscopy (Nikon E200, Japan), and the algal samples were diluted into the order of 10⁶ cells/L for subsequent DNA extraction. Three hundred milliliters of the diluted reference algae were filtered through a 0.45 μm MCE filter membrane (Jinteng, China) with the triplicate, which was stored at −80 °C. The filter membranes of the diluted reference algae and all water samples were taken out and cut into pieces, and the total DNA of the membrane was extracted using the FastDNA SPIN Kit for Soil (MP bio, USA). The extracted DNA samples were stored at −20 °C for subsequent qPCR experiments.

The DNA samples of standard reference algae were diluted by 10× gradient dilution with sterile ultrapure water to prepare standard DNA samples. Using seven pairs of universal primers for seven phyla of algae (Supplementary Table S1) (Li et al. 2022), qPCR was performed on the Quant Studio 6 Flex (Applied Biosystems, USA) with the SYBR Green Pro Taq HS Premix (AG, China). Three independent replicates were performed on each sample.

Twenty microliters of qPCR reaction mix included 10 μL of 2× SYBR Green Pro Taq HS master mix (AG, China), 0.4 μL of 10 μM forward primer, 0.4 μL of 10 μM reverse primer, 8.2 μL of sterile distilled water, and 1 μL of DNA template. The reaction procedure was as follows: pre-denaturation at 94 °C for 30 s, followed by 40 cycles of 94 °C for 5 s and 60 °C for 34 s. The standard curves were established based on the relationship between the log value of algal cell density and the Ct value corresponding to the standard DNA sample (Supplementary Figure S2). The cell densities of seven phyla of freshwater algae were calculated by substituting the Ct value of the water samples into the linear equation of the standard curves.

The Spearman correlation analysis was performed to analyze the correlation between water quality factors and the cell density of seven phyla of algae in Longhu Lake via the GraphPad Prism 8.0.2 software. We also used GraphPad Prism 8.0.2 software to analyze the multicollinearity of the data set. RDA was performed using Canoco 5.0 after removing the variables with variance inflation factors (VIF) greater than 10, to identify the environmental factors favoring the growth of seven phyla of algae in Longhu Lake.

The results showed that the TP concentration of the L1–L4 sites was 0.046–0.205, 0.019–0.064, 0.072–0.156, and 0.020–0.119 mg/L, respectively (Figure 4(c)). The TP concentration of most water samples exceeded the standard limit for surface water (TP 0.025 mg/L) (GB 3838-2002). The annual average TP of the four sampling points was 0.067–0.082 mg/L, and the annual average TN was 2.554–3.268 mg/L (Supplementary Figure S7). The above results showed the concentration of TN and TP in Longhu Lake exceeded the standard limit seriously, which might come from the upstream rivers.

The N/P ratio in Longhu Lake was high with an annual average of 39.20 (Figure 4(d)). Before the occurrence of green algal blooms, the N/P ratio of each point was greater than 40, and the N/P ratio of the L3 site reached the highest of 170.53. In August 2016, the massive growth and reproduction of algae consumed a lot of nitrogen, resulting in a sharp decrease in the concentrations of TN in the water (Figure 4(a)). The TP concentration also showed a downward trend, but only a slight drop. So the N/P ratio of each point dropped during the occurrence of green algal blooms (Figure 4(d)), indicating that green algae may have a higher demand for nitrogen than phosphorus, which was consistent with the previous research results (Xu et al. 2011). After blooms subsided, the N/P of all sampling sites began to rise again in September 2016. The change in the concentration of either TN or TP will cause a change in the N/P ratio. The N/P ratio in 2017 decreased compared with that in 2016. The results showed that the high concentration of TN leads to a high N/P ratio in Longhu Lake during the sampling period.

The results indicated that water temperature, ammonia nitrogen, and TON may be the impact factors that lead to green algal blooms in Longhu Lake. The rapid reproduction of green algae consumed nitrogen and phosphorus, resulting in a decrease in the concentrations of nitrate nitrogen and TP. In addition, green algae, the first dominant algae, were the most sensitive to water quality factors. All water quality factors related to cyanobacteria, the second dominant algae in summer, are also related to green algae, which indicated cyanobacteria and green algae had a competitive relationship in Longhu Lake.

All water quality factors were screened step by step using forward selection. Six water quality factors, including water temperature (F = 17.4, P = 0.002) and TON (F = 5.1, P = 0.004), -N (F = 3.4, P = 0.022), COD_Mn (F = 3.1, P = 0.016), and TOC (F = 2.7, P = 0.026), had significant effects on the composition of seven phyla of freshwater algae (P < 0.05). Water temperature (50.3%) and TON (13.7%) were two important factors that had the most significant effect on the algal community structure.

The results of RDA analysis showed that the water quality factors with significant positive correlation with green algae and cyanobacteria were the same, including water temperature, chromaticity, ammonia nitrogen, TOC, COD_Mn, TON, and N/P, and the significant negative correlations were DO, TP, and pH (Figure 6). The results suggested that warm water temperature, high-concentration ammonia nitrogen, high-concentration TON, and high N/P ratio may be environmental factors favoring the growth of cyanobacteria and green algae.

The monitoring results showed that the spatiotemporal sequence of green algal blooms was consistent with the spatiotemporal sequence of the spread of TON. The peak of ammonia nitrogen appeared immediately after TON pollution input, which may be the degradation product of TON and accelerated the overall outbreak of green algal blooms in Longhu Lake. Our results indicated that TON and ammonia nitrogen were the main nitrogen sources for the growth of green algae during the bloom and TON pollution was the key trigger cause for green algal blooms in Longhu Lake.

Published studies showed that dissolved organic nitrogen (DON) was closely related to the cell density of dinoflagellate Alexandrium and the increase in DON concentration was an important cause of red tide under optimal water temperatures (Ning et al. 2012). Previous studies confirmed that three different species of green algae Selenastrum capricornutum, Chlamydomonas reinhardtii, and Chlorella vulgaris directly utilized 80% of DON in wastewater under sterile conditions (Sun & Simsek 2017). A published paper showed that two species of dinoflagellate preferred organic nitrogen (urea) to ammonia nitrogen, and uptake rates of urea were higher than that of ammonium, whereas uptake of nitrate was negligible (García-Portela et al. 2020). More evidence indicated that except for urea, dissolved free amino acids and peptides could serve as a nitrogen source for phytoplankton, including harmful algae (Moschonas et al. 2017; Krausfeldt et al. 2019). It is increasingly clear that organic nitrogen is closely linked to algal blooms.

In addition, the organic nitrogen can be decomposed and hydrolyzed by heterotrophic bacteria into inorganic nitrogen, such as ammonia nitrogen and nitrate nitrogen, which can be utilized by phytoplankton (Tan et al. 2019). Organic nitrogen is confirmed to be the critical factor for the occurrence of green algal blooms in this study. However, the currently implemented ‘Environmental quality standards for surface water’ (GB3838-2002) in China do not set a limit on the concentration of TON in external sewage (MEEC 2002). High-concentration TON pollution input has the potential risk of deteriorating water quality. Therefore, relevant water quality management departments should set a limit on the emission concentration of TON to reduce the risk of water pollution.

The concentration of nitrogen and phosphorus nutrients may be an important factor affecting the dominant competition between cyanobacteria and green algae. Our results indicated that sufficient nitrogen and phosphorus nutrients favored the growth of green algae in Longhu Lake. Previous experiments confirmed that green alga Scenedesmus had a more competitive advantage when the nitrogen and phosphorus concentration was high, and the cyanobacterium Microcystis aeruginosa had a more competitive advantage when the nitrogen and phosphorus concentration was low (Lei et al. 2007). Some evidence shows that green algae often are the dominant algae in hypereutrophic lakes (Zhou et al. 2019). The growth of green algae requires a higher concentration of nitrogen and phosphorus than cyanobacteria (Xu et al. 2006, 2008). Under a high concentration of nitrogen and phosphorus nutrients, green algae grow faster than cyanobacteria (Xu et al. 2011).

The N/P ratio seems to play an important role in the dominant competition of green algae. The average annual N/P ratio of Longhu Lake was 39.2 (Figure 4(d)). Correlation analysis (Figure 5) and RDA analysis (Figure 6) showed that there was a significant positive correlation between green algal cell density and N/P. The N/P ratio of four sampling sites dropped significantly in August 2016 when green algal blooms outbreak overall in Longhu Lake, suggesting that green algae consumed more nitrogen than phosphorus during proliferation, which may explain why green algal density was positively correlated with the N/P ratio. The growth of green algae had a higher requirement for nitrogen than cyanobacteria (Xu et al. 2011). However, green algae have dominant advantages in some eutrophic-hypertrophic shallow lakes even with a low N/P ratio (Jensen et al. 1994; Zhou et al. 2019). Some studies indicate that the N/P ratio cannot perfectly explain the dominant competition between cyanobacteria and green algae under the nitrogen and phosphorus load that exceeds the absorption capacity of phytoplankton (Paerl et al. 2001). The limitation of nutrients on algal growth is only judged from the N/P ratio, ignoring the effect of the absolute concentration of nutrients on algae growth (Xu et al. 2011). When the concentration of nitrogen and phosphorus is lower than the threshold required for algae growth, even if the N/P ratio is suitable for the growth of cyanobacteria or green algae, the algae can only maintain a relatively low growth rate. When both nitrogen and phosphorus are sufficient, the growth of algae is no longer limited by the N/P ratio. Therefore, the ratio of nitrogen to phosphorus may not be an essential factor determining the dominance of green algae.

Another factor that may affect the formation of green algae dominance is the high concentration of nitrate-nitrogen. Studies have shown that green algae are easier to utilize nitrate-nitrogen as a nitrogen source than cyanobacteria, and green algae have more competitive advantages with high nitrate-nitrogen (Liu et al. 2006). Green algae had a stronger competitive advantage over cyanobacteria in the summer of 2017 than that in the summer of 2016. Nitrate-nitrogen was the main component of TN from November 2016 to July 2017 (Supplementary Figure S5), and the concentration of nitrate-nitrogen in the summer of 2017 was higher than in the summer of 2016 (Supplementary Figure S6), which may help why the competitive advantage of green algae in the summer of 2017 is stronger than that in the summer of 2016.

Therefore, our results imply that sufficient nitrogen and phosphorus may provide more favorable competitive conditions for the rapid growth of green algae. The N/P ratio may have no selective effect on cyanobacteria and green algae, and the high concentration of nitrate-nitrogen may increase the competitive advantage of green algae in the algal community.

The annual water temperature of Longhu Lake was in the range of 14–36 °C (Supplementary Figure S8), which was favorable for the growth of green algae. Green algae had a competitive advantage over cyanobacteria and other algae throughout the year. Although higher water temperatures are conducive to the growth of green algae, cyanobacteria also prefer to grow at rising water temperatures (Paerl & Huisman 2008). We speculated that high water temperature is an important factor for the growth of green algae, but may have no selection effects on green algae and cyanobacteria. Their dominant competition could be determined by multiple environmental factors rather than a single one.

Some researchers believe that shallow water without stratification is one of the important conditions for the formation of green algal blooms (Jensen et al. 1994; Zhou et al. 2019). Green algae have a higher demand for phosphorus than cyanobacteria (Xu et al. 2011). Shallow lakes are non-stratified and have high sediment release rates, which makes phosphorus not a limiting factor for the growth of algae. Green algae are likely to dominate in small shallow lakes with a higher concentration of phosphorus (Zhou et al. 2019). Longhu Lake is a shallow lake with an average water depth of 2.5 m with a high concentration of phosphorus, providing a sufficient source of phosphorus for the growth of green algae. Sediment is the main source of phosphorus required for phytoplankton growth in shallow lakes, while nutrients lost by sedimentation in stratified lakes are trapped in the hypolimnion (Jensen & Andersen 1992; Jensen et al. 1994). Cyanobacteria, especially Microcystis, have more competitive in stratified deep lakes or reservoirs because they can resist phosphorus deficiency stress through the formation of polyphosphates (Wan et al. 2019). Green algae obtain inorganic phosphorus by secreting extracellular alkaline phosphatase, but do not have the ability to tolerate low phosphorus stress (Cao et al. 2010). The different tolerance ability to phosphorus deficiency may explain why cyanobacteria are more dominant in stratified lakes, while green algae are more dominant in non-stratified lakes.

However, cyanobacterial blooms often occur in some shallow lakes, such as Taihu Lake (mean depth ∼2 m) (Xu et al. 2015) and Chaohu Lake (mean depth ∼3 m) (Zhou et al. 2023). Why are some shallow lakes prone to form cyanobacterial blooms, while others are prone to form green algal blooms? By comparing the water retention time, we found the difference between them. The water retention time of Taihu Lake and Chaohu Lake is 180 days and 168 days (0.46 year) (Xu et al. 2015; Zhou et al. 2023), however, the counterpart of Longhu Lake is 10.6 days. Fast retention time may be favorable for the dominant growth of green algae with a faster growth rate, while cyanobacteria may require a longer retention time to form blooms due to their small growth rate. Water retention time may have an important selective effect on the species of dominant algae, which may explain why green algal blooms often occur in small shallow lakes and flowing rivers, while cyanobacterial blooms often occur in static lakes and reservoirs.

Light, nutrients, and water temperature are the basic requirements for algal growth, and none is dispensable. Hydrological conditions, including water depth, flow velocity, and water retention time, may have a selection effect on the dominant species. This study implies the combined effects of high-concentration nitrogen and phosphorus nutrients, high water temperature, non-stratification, and short water retention time in Longhu Lake may lead to green algae being the first dominant algae.

This study investigated the relationship between environmental factors and the dominating growth of green algae in Longhu Lake. Our results showed that green algae were the first dominant algae in Longhu Lake, accounting for an average of 71.80–80.31% during the sampling year. The temporal and spatial dynamic of TON was consistent with green algal blooms, which implies TON pollution may be the key trigger of green algal blooms. The nitrogen and phosphorus nutrients were excessive in Longhu Lake, and the highest peak of ammonia nitrogen occurred during the blooms, implying that ammonia nitrogen may also play a role in stimulating the outbreak of green algal blooms. Our results indicated that the combination conditions of higher water temperature, sufficient nitrogen and phosphorus, non-stratification, and short water change cycle may determine the competitive growth of green algae over cyanobacteria in shallow lakes. This study improves our knowledge about dominating advantages of green algae over cyanobacteria in shallow lakes. Undoubtedly, algal blooms are the result of a combination of multiple factors. Light, nutrients, and water temperature are the core-inducing factors that trigger algal blooms, and none of them are indispensable. Other factors such as water depth, flow velocity, and water retention time may play important regulatory roles in the formation of algal blooms and the selection of dominant algae. We know less about the impact and selective effects of these hydrological factors on the competition of cyanobacteria and green algae, which is worth further research.

This work was supported by the National Natural Science Foundation of China (Nos. 41703074, 51678551, and U2005206) and the Fujian Provincial Department of Science and Technology (No. 2018T3003).

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.