Co-occurrence patterns and environmental factors associated with rapid onset of Microcystis aeruginosa bloom in a tropical coastal lagoon

Light-driven differences in bacterial networks and organic matter decomposition: Insights from an analysis of the harmful cyanobacterium Microcystis aeruginosa PCC 7806

Freshwater systems are critical yet often underestimated components of global carbon cycling, functioning both as carbon sinks and sources. Cyanobacteria play a key role in this cycle by capturing atmospheric carbon dioxide through photosynthesis. The captured carbon is either released back into the atmosphere or sequestered in sediments following organismal decay. This study examines the pivotal role of cyanobacteria, specifically Microcystis aeruginosa PCC 7806, in the biogeochemical cycling of carbon in freshwater ecosystems, with a focus on how light influences the degradation of cyanobacteria-derived organic matter. Using a combination of 16S rDNA sequencing and excitation-emission matrix coupled with parallel factor (EEM-PARAFAC) analysis, we conducted a 50-day experiment to investigate the dynamics of dissolved organic matter (DOM) and lysate organic matter (LOM) derived from M. aeruginosa PCC 7806 under light and dark conditions. Our results demonstrate that light significantly impacts bacterial community composition, gene functionality, and the decomposition of organic matter. The findings emphasize the crucial role of light in facilitating microbial adaptation, stabilizing microbial networks and driving organic substrate transformation. These insights underscore the influence of light on microbial community dynamics and organic matter degradation, revealing shifts in microbial populations under varying light conditions. This suggests a strong link between photochemical processes and microbial activity, with significant ecological implications.

Daily process and key characteristics of phytoplankton bloom during a low-water level period in a large subtropical reservoir bay

Reservoirs, heavily influenced by artificial management, often harbor phytoplankton assemblages dominated by cyanobacteria or dinoflagellates, triggering significant changes in aquatic ecosystems. However, due to limited sampling frequency and insufficient attention to species composition, the bloom processes and key characteristics of phytoplankton community structure have not been systematically elucidated. During the low-water level period when blooms are most likely to occur (June to September) in a tributary bay of the Three Gorges Reservoir, daily sampling was conducted to investigate phytoplankton community composition, identify significant environmental factors, and evaluate important structure characteristics of phytoplankton community. The results showed that Microcystis aeruginosa maintained a clear dominance for almost a month in stage 1, with low Shannon and evenness but a high dominance index. Phytoplankton total density and biomass decreased drastically in stage 2, but Microcystis aeruginosa still accounted for some proportion. The highest Shannon and evenness but the lowest dominance index occurred in stage 3. Peridiniopsis niei occurred massively in stage 4, but its dominant advantages lasted only one to two days. NH4-N was responsible for the dominance of Microcystis aeruginosa, while TP and PO4-P was responsible for the dominance of Peridiniopsis niei; however, precipitation contributed to their drastic decrease or disappearance to some extent. The TN : TP ratio could be considered as an important indicator to determine whether Microcystis aeruginosa or Peridiniopsis niei dominated the phytoplankton community. Throughout the study period, physiochemical factors explained more variation in phytoplankton data than meteorological and hydrological factors. Pairwise comparisons revealed an increase in average β diversity with stage progression, with higher β diversities based on abundance data than those based on presence/absence data. Repl had a greater effect on β diversity differences based on presence/absence data, whereas RichDiff had a greater effect on β diversity differences based on species abundance data. Co-occurrence networks for stage 1 showed the most complex structure, followed by stage 4, while the network for stage 3 was relatively sparse, although the overall community division remained compact. This study provides a useful attempt to explore the status and changes in phytoplankton community structure during the bloom process through high-resolution investigation.

Spatio-temporal structuring and assembly of abundant and rare bacteria in the benthic compartment of a marginally eutrophic lagoon

The investigations on ecological processes that structure abundant and rare sub-communities are limited from the benthic compartments of tropical brackish lagoons. We examined the spatial and temporal patterns in benthic bacterial communities of a brackish lagoon; Chilika. Abundant and rare bacteria showed differences in niche specialization but exhibited similar distance-decay patterns. Abundant bacteria were mostly habitat generalists due to their broader niche breadth, environmental response thresholds, and greater functional redundancy. In contrast, rare bacteria were mostly habitat specialists due to their narrow niche breadth, lower environmental response thresholds, and functional redundancy. The spatial patterns in abundant bacteria were largely shaped by stochastic processes (88.7 %, mostly dispersal limitation). In contrast, rare bacteria were mostly structured by deterministic processes (56.4 %, mostly heterogeneous selection). These findings provided a quantitative assessment of the different forces namely spatial, environmental, and biotic that together structured bacterial communities in the benthic compartment of a marginally eutrophic lagoon.

Synthesis of Cu2+ doped biochar and its inactivation performance of Microcystis aeruginosa: Significance of synergetic effect

The harmful cyanobacteria bloom is frequently occurring in the aquatic environment and poses a tremendous threat to both aquatic organisms and ecological function. In this study, a series of Cu2+ doped biochar (BC) composites (Cu-BCs) with different loading ratios (0.1 %-5 wt %) (Cu-BC-0.1/0.5/1/2.5/5) was successfully fabricated through a one-step adsorption method for in-situ inactivation of Microcystis aeruginosa and simultaneous removal of microcystin-LR (MC-LR). Compared with the single BC/CuSO4 and other Cu-BCs composites, the Cu-BC-2.5 exhibited the best algae inactivation performance with the lowest 72 h medium effective concentration (EC50) value of 0.34 mg/L and highest chlorophyll α degradation efficiency of 8.31 g/g. Notably, the as-prepared Cu-BC-2.5 maintained good inactivation performance in the near-neutral pH (6.5-8.5), and the presence of humic acid and salts such as Na2CO3 and NaCl. The outstanding inhibitory effect of the Cu-BC-2.5 could be explained by the synergetic effect between biochar and Cu2+, which greatly elevated reactive oxygen species (ROS) intensity and in turn led to severe membrane damage and collapse of the antioxidant system. Additionally, the Cu-BC-2.5 could simultaneously remove the released microcystin-LR (MC-LR) throughout the inactivation process and prevent secondary pollution, thus offering a new insight into the alleviation of harmful cyanobacteria in aquatic environment.

Growth prediction of Microcystis aeruginosa based on a secondary decomposition integration model

Microcystis aeruginosa is the dominant species in the blooms of eutrophic lakes such as Taihu Lake in China. Chlorophyll-a is one of the most common indicators to characterize its biomass. The nonlinearity and unsteadiness of the chlorophyll-a sequence decrease the prediction accuracy. In this paper, a secondary decomposition prediction method based on the integration of wavelet decomposition, variational modal decomposition, and gated recurrent unit (WD-VMD-GRU) is proposed. First, the original sequence is decomposed once using wavelet decomposition (WD). Then, the components with higher sample entropy values are decomposed using variational modal decomposition (VMD). Finally, each component is predicted using a gated recurrent unit (GRU), and the final prediction results are obtained by reconstructing each component result. The decomposition effect is ranked as VMD > WD > CEEMDAN > EMD. The WD-VMD-GRU model has a significant advantage compared to the basic model, with an increase of over 6.5% in R2. The secondary decomposition reduces the difficulty of predicting GRU components and has better prediction performance. The RMSE, MAE, and R2 were 1.752, 1.450, 0.969 at 2-day prediction, and 3.169, 2.711, 0.908 at 6-day prediction. Therefore, the WD-VMD-GRU model is superior in accuracy to other methods and can provide a scientific basis for the growth prediction research of M. aeruginosa.