Cyanobacterial bloom intensities determine planktonic eukaryote community structure and stability

Identification of key feature variables and prediction of harmful algal blooms in a water diversion lake based on interpretable machine learning

Harmful algal blooms (HABs) as an increasing environmental problem in lakes, and water diversion has become a common and effective strategy for mitigating HABs. Early and accurate identification of the occurrence of HABs in lakes is essential for scientific guidance of water diversion. Furthermore, the inevitable changes of hydrodynamic and water environment in the receiving area during water diversion make it more challenging to identify the important environmental features of HABs. Therefore, we constructed a machine learning modelling framework suitable for predicting HABs with favorable performance in both non-water diversion and water diversion states. In this study, we collected data from three monitoring sites for the years 2008-2020 (non-water diversion period from 2008 to 2013 and water diversion period from 2014 to 2020) as external validations and six sampling sites for the years 2021-2022 (2021 non-water diversion period and 2022 water diversion period) as internal validation. The CatBoost (AUC = 0.948) model fared best performance was obtained by comparing 10 machine learning models for comprehensive HABs prediction analyses in the external cohorts of Yilong Lake, and the 24 features were reduced to obtain the 8 (Including TP, TN and CODCr, etc.) most important environmental features. In addition, the SHapley Additive explanation (SHAP) method was used to interpret this CatBoost model through a global interpretation that describes the whole features of the model and a local interpretation that details how a certain forecast of HABs is made for a single sample via inputting the individual data. The CatBoost interpretable model also performed well in internal validation and the model has been converted into a convenient application for use by the Bureau of Yilong Lake Administration personnel and researchers. Finally, the results of the PLS-PM explains that water diversion indirectly mitigates HABs mainly through diluting nutrient concentrations. Overall, the final model of this study has a good performance and application benefits in predicting HABs during the non-water diversion period and water diversion period of Yilong Lake, which provides a guideline for water diversion. Furthermore, this study also provides a reference for other similar eutrophic lake water diversion strategies.

Identifying Critical Land Use Thresholds for Biodiversity Conservation in China's Lake Ecosystems

Aquatic biodiversity loss, particularly in rapidly developing nations, continues to raise concerns, prompting urgent debates on reconciling economic growth with environmental preservation through land use planning. While spatial variations in aquatic communities along land use gradients are well-documented, precise ecological thresholds for land use impacts on freshwater lakes remain elusive, hindering sustainable development efforts. This study investigated six representative freshwater lakes in China between 2019 and 2020, all significantly impacted by anthropogenic activities. We utilized macroinvertebrate communities as bioindicators and employed four categories of aquatic ecological metrics─taxonomic diversity, functional diversity, pollution tolerance, and water quality─to assess their responses to local land use patterns. Macroinvertebrate community composition varied significantly among the studied lakes, with pollution-tolerant taxa predominating in highly urbanized and eutrophic systems. Notably, benthic communities exhibited greater sensitivity to urban land use (ecological thresholds: 2-10%) compared to agricultural land use (thresholds: 15-40%). The most pronounced responses were observed within 1-5 km of the lakeshore, with circular buffers yielding more significant effects than fan-shaped buffers, excluding water areas. A novel land use intensity indicator─the ratio of nonecological to ecological land (NEL/EL = area of nonecological land/area of ecological land)─proved effective in predicting ecological shifts. Smaller or heavily urbanized lakes showed marked changes at NEL/EL ratios between 0 and 0.6, while larger or river-connected lakes exhibited shifts at ratios exceeding 1.5. These findings underscore the profound ecological footprint of human activities on lake ecosystems with urban land cover emerging as the most deleterious factor.

Seasonality of cyanobacteria and eukaryotes in Lake Geneva and the impacts of cyanotoxins on growth of the model ciliate Tetrahymena pyriformis

Toxic cyanobacteria are likely to be favored by global warming and other human impacts, posing significant threats to aquatic ecosystems. While cyanobacterial blooms in eutrophic lakes are widely investigated, the dynamics of cyanobacteria and the effects of their toxins and bioactive metabolites on the plankton communities in mesotrophic and oligotrophic lakes are less well understood. Here we investigated seasonal dynamics of cyanobacteria, eukaryotic algae and cyanotoxins in oligo-mesotrophic Lake Geneva-the largest and deepest lake in western Europe. High-throughput sequencing of the 16S rRNA genes in 143 samples along a water column revealed that Lake Geneva hosts diverse, co-dominant cyanobacterial genera, including Planktothrix, Cyanobium, Pseudanabaena, and Aphanizomenon. The abundance of the mcyA gene marker for microcystin production was highly correlated with total cyanobacteria abundance, obtained from qPCR of the 16S rRNA genes. Targeted LC-HRMS/MS analysis demonstrated peak concentrations of cyanotoxins in September and December 2021 at the deep chlorophyll-a maximum layer, reaching up to 1474 ng/l for anabaenopeptins and 144 ng/l for microcystins. The toxin peaks did not correlate with the abundance or variations in the cyanobacteria or eukaryote community, but they were correlated in time with seasonal lows in the abundances of ciliates (18S rRNA analysis). Laboratory exposure tests demonstrated that growth of the model ciliate Tetrahymena pyriformis was inhibited by Microcystin-RR and Anabaenopeptin A at environmentally relevant concentrations in the ng/l-range, in natural lake water, synthetic freshwater, and growth media spiked with the cyanotoxins. Our findings suggest that even low concentrations (in the ng/l-range) of microcystins and anabaenopeptins, reduce growth of ciliates such as T. pyriformis and can be expected to have wider impacts on the eukaryote communities.

Insights into cyanobacterial blooms through the lens of omics

Cyanobacteria are oxygen-producing photosynthetic bacteria that convert carbon dioxide into biomass upon exposure to sunlight. However, favorable conditions cause harmful cyanobacterial blooms (HCBs), which are the dense accumulation of biomass at the water surface or subsurface, posing threats to freshwater ecosystems and human health. Understanding the mechanisms underlying cyanobacterial bloom formation is crucial for effective management. In this regard, recent advancements in omics technologies have provided valuable insights into HCBs, which have raised expectations to develop more effective control methods in the near future. This literature review aims to present the genomic architecture, adaptive mechanisms, microbial interactions, and ecological impacts of HCBs through the lens of omics. Genomic analysis indicates that the genome plasticity of cyanobacteria has enabled their resilience and effective adaptation to environmental changes. Transcriptomic investigations have revealed that cyanobacteria use various strategies for adapting to environmental stress. Additionally, metagenomic and metatranscriptomic analyses have emphasized the significant role of the microbial community in regulating HCBs. Finally, we offer perspectives on potential opportunities for further research in this field.

Unveiling the trifecta of cyanobacterial quorum sensing: LuxI, LuxR and LuxS as the intricate machinery for harmful algal bloom formation in freshwater ecosystems

Harmful algal blooms (HABs) are causing significant disruptions in freshwater ecosystems, primarily due to the proliferation of cyanobacteria. These blooms have a widespread impact on various lakes globally, leading to profound environmental and health consequences. Cyanobacteria, with their ability to produce diverse toxins, pose a particular concern as they negatively affect the well-being of humans and animals, exacerbating the situation. Notably, cyanobacteria utilize quorum sensing (QS) as a complex communication mechanism that facilitates coordinated growth and toxin production. QS plays a critical role in regulating the dynamics of HABs. However, recent advances in control and mitigation strategies have shown promising results in effectively managing and reducing the occurrence of HABs. This comprehensive review explores the intricate aspects of cyanobacteria development in freshwater ecosystems, explicitly focusing on deciphering the signaling molecules associated with QS and their corresponding genes. Furthermore, a concise overview of diverse measures implemented to efficiently control and mitigate the spread of these bacteria will be provided, shedding light on the ongoing global efforts to address this urgent environmental issue. By deepening our understanding of the mechanisms driving cyanobacteria growth and developing targeted control strategies, we hope to safeguard freshwater ecosystems and protect the health of humans and animals from the detrimental impacts of HABs.

Strategies for regulating the intensity of different cyanobacterial blooms: Insights from the dynamics and stability of bacterioplankton communities

The occurrence of cyanobacterial blooms is increasing in frequency and magnitude due to climate change and human activities, which poses a direct threat to drinking water security. The impacts of abiotic and biotic factors on the development of blooms have been well studied; however, control strategies for different bloom intensities have rarely been explored from the perspective of the dynamics and stability of bacterioplankton communities. Here, a network analysis was used to investigate the interactions and stability of microbial communities during different periods of R. raciborskii bloom in an inland freshwater lake. The abundance and diversity of rare taxa were significantly higher than that of abundant taxa throughout the bloom cycle. At the pre-bloom (PB) stage, microbial interactions among the different bacterial groups were weak but strongly negatively correlated, indicating low robustness and weak disturbance resistance within the community. However, community stability was better, and microbial interactions became more complicated at the high-bloom (HB) and low-bloom (LB) stages. Interestingly, rare taxa were significantly responsible for community stability and connectivity despite their low relative abundance. The Mantel test revealed that Secchi depth (SD), orthophosphate (PO43--P), and dissolved oxygen (DO) were significantly positively correlated with abundant taxa, rare taxa and PB. DO was significantly positively correlated with HB, intermediate taxa, and rare taxa, while water temperature (WT), N/P and total nitrogen (TN) were significantly positively correlated with LB, abundant taxa, intermediate taxa, and rare taxa. These findings suggest that reducing the PO43--P concentration at the PB stage may be an effective approach to preventing the development of R. raciborskii blooms, while regulating rare taxa at the HB and LB stages may be a key factor in controlling R. raciborskii blooms.

pH-Related Changes in Soil Bacterial Communities in the Sanjiang Plain, Northeast China

Soil bacteria are crucial components of terrestrial ecosystems, playing an important role in soil biogeochemical cycles. Although bacterial community diversity and composition are regulated by many abiotic and biotic factors, how soil physiochemical properties impact the soil bacteria community diversity and composition in wetland ecosystems remains largely unknown. In this study, we used high-throughput sequencing technology to investigate the diversity and composition of a soil bacterial community, as well as used the structural equation modeling (SEM) method to investigate the relationships of the soil's physicochemical properties (i.e., soil pH, soil organic carbon (SOC), total nitrogen (TN), ammonium nitrogen (NH4+N), electrical conductivity (EC) and nitrate nitrogen (NO3-N)), and soil bacterial community structures in three typical wetland sites in the Sanjiang Plain wetland. Our results showed that the soil physicochemical properties significantly changed the α and β-diversity of the soil bacteria communities, e.g., soil TN, NH4+N, NO3-N, and SOC were the main soil factors affecting the soil bacterial α-diversity. The soil TN and pH were the key soil factors affecting the soil bacterial community. Our results suggest that changes in soil pH indirectly affect soil bacterial communities by altering the soil nitrogenous nutrient content.

Dynamic response of bacterial communities to Microcystis blooms: A three-year study

Although nutrient availability is widely recognized as the driving force behind Microcystis blooms, identifying the microorganisms that play a pivotal role in their formation is a challenging task. Our understanding of the contribution of bacterial communities to the development of Microcystis blooms remains incomplete, despite the fact that the relationship between Microcystis and bacterial communities has been extensively investigated. Most studies have focused on their interaction for a single year rather than for multiple years. To determine key bacteria crucial for the formation of Microcystis blooms, we collected samples from three sites in the Daechung Reservoir (Chuso, Hoenam, and Janggye) over three years (2017, 2019, and 2020). Our results indicated that Microcystis bloom-associated bacterial communities were more conserved across stations than across years. Bacterial communities could be separated into modules corresponding to the different phases of Microcystis blooms. Dolichospermum and Aphanizomenon belonged to the same module, whereas the module of Microcystis was distinct. The microbial recurrent association network (MRAN) showed that amplicon sequence variants (ASVs) directly linked to Microcystis belonged to Pseudanabaena, Microscillaceae, Sutterellaceae, Flavobacterium, Candidatus Aquiluna, Bryobacter, and DSSD61. These ASVs were also identified as key indicators of the bloom stage, indicating that they were fundamental biological elements in the development of Microcystis blooms. Overall, our study highlights that, although bacterial communities change annually, they continue to share core ASVs that may be crucial for the formation and maintenance of Microcystis blooms.

Spatial and Temporal Characteristics of Phytoplankton Communities in Drinking Water Source Reservoirs in Shenzhen, China

Phytoplankton diversity and community characteristics are closely associated with aquatic environmental factors. Understanding these dynamics can provide insights into the ecological health of water bodies. We investigate the spatial and temporal characteristics of phytoplankton communities in 27 drinking water source reservoirs in Shenzhen, China. As a method, we collected samples during the dry season in 2021 and the wet season in 2022, analyzed the alpha and beta diversities of phytoplankton communities, and correlated these with the environmental factors. The results reveal that Cyanobacteria dominate the phytoplankton communities in the Shenzhen reservoirs. Phytoplankton diversity is greater during the dry season. The algal composition varies spatially, and the phytoplankton diversity tends to decrease with increasing eutrophication. A co-occurrence network analysis indicates denser and stronger correlations among phytoplankton nodes during the wet season than dry season. Reservoirs with moderate eutrophication levels exhibit denser nodes and stronger correlations compared to those with low or high eutrophication levels. The chemical oxygen demand, water temperature, pH, and total nitrogen are identified as key influencers of the phytoplankton community structure. Our results contribute to the enhanced understanding of the spatial and temporal dynamics of phytoplankton communities in reservoirs in South China and provides insights into the management and conservation of these drinking water reservoirs.

Microbial community dynamics and assembly mechanisms across different stages of cyanobacterial bloom in a large freshwater lake

Cyanobacterial bloom caused by eutrophication in lakes has become one of the significant environmental problems worldwide. However, a notable research gap persists in understanding the environmental adaptation and community assembly of microbial dynamics in response to different blooming stages. Therefore, metagenomic sequencing was employed in this study to investigate alterations in the microbial community composition in water and sediment during different stages of cyanobacterial blooms in Lake Taihu. The results indicated significant spatiotemporal variations in physicochemical parameters across the early, medium, and late stages of a complete cyanobacteria bloom cycle. Diversity analysis further revealed that the temporal differences in the microbial community were substantially greater than spatial variations. Notably, during the medium-blooming stages in water, Microcystis emerged as the predominant detected cyanobacteria genus. Interestingly, the content of superoxide dismutase (SOD), malondialdehyde (MDA), and catalase (CAT) in sediment exceeded those in water by over 10 times, indicating that sediment-dwelling Cyanobacteria might constitute a crucial source of water blooms. Moreover, dissolved oxygen, pH, and water temperature were identified as the most influential environmental variables shaping the microbial community in the water. Stochasticity emerged as a prominent factor governing microbial community assembly across different bloom periods. Meanwhile, co-occurrence patterns suggested fewer interactions and instability between species in medium-blooming stages. Notably, the potential keystone phyla occupied crucial ecological niches. This research carries significant theoretical implications for managing cyanobacterial blooms in freshwater ecosystems.

Shift of phytoplankton assemblages in a temperate lake located on the eastern route of the South-to-North Water Diversion Project

There remains no consensus on the effects of changes in the environment factors under the action of water diversions on phytoplankton communities. Herein the changing rules applying to phytoplankton communities subject to water diversion were unveiled based on long-term (2011-2021) time-series observations on Luoma Lake, located on the eastern route of the South-to-North Water Diversion Project. We found that nitrogen decreased and then increased, while phosphorus increased after operation of the water transfer project. Algal density and diversity were not affected by water diversion, while the duration of high algal density was shorter after water diversion. Phytoplankton composition had dramatic differences before and after water transfer. The phytoplankton communities exhibited greater fragility when they first experienced a human-mediated disturbance, and then they gradually adapted to more interferences and acquired stronger stability. We furthermore found the niche of Cyanobacteria narrowed while that of Euglenozoa widened under the pressure of water diversion. In addition to WT and DO, the main environmental factor before water diversion was NH₄-N, whereas the effect of NO₃-N and TN on phytoplankton communities increased after water diversion. These findings fill the knowledge gap as to the consequence of water diversion on water environments and phytoplankton communities.

Abundant bacteria and fungi attached to airborne particulates in vegetable plastic greenhouses

The proliferation of modern vegetable plastic greenhouses (VPGS) supplies more and more vegetables for food all over the world. The airborne bacteria and fungi induce more exposure opportunities for workers toiling in confined plastic greenhouses. Culture-independent approaches by qPCR and high-throughput sequencing technology were used to study the airborne particulates microbiota in typic VPGS in Shandong, a large base of vegetables in China. The result revealed the mean airborne bacteria concentrations reached 1.67 × 10³ cells/m³ (PM_2.5) and 2.38 × 10³ cells/m³ (PM₁₀), and the mean airborne fungal concentrations achieved 1.49 × 10² cells/m³ (PM_2.5) and 3.19 × 10² cells/m³ (PM₁₀) in VPGS. The predominant bacteria in VPGS included Ralstonia, Alcanivorax, Pseudomonas, Bacillus, and Acinetobacter. Botrytis, Alternaria, Fusarium, Sporobolomyces, and Cladosporium were frequently detected fungal genera in VPGS. A higher Chao1 of bacteria in PM₁₀ was significantly different from PM_2.5 in VPGS. The potential pathogens in VPGS include Raltonia picketti, Acinetobacter lwoffii, Bacillus anthracis, Botrytis cinerea, and Cladosporium sphaerospermum. The network analysis indicated that airborne microbiota was associated with soil microbiota which was affected by anthropologic activities. The predicted gene functions revealed that bacterial function mainly involved metabolism, neurodegenerative diseases, and fungal trophic mode dominated by Pathotroph-Saprotroph in VPGS. These findings unveiled airborne microbiomes in VPGS so that a strategy for improving air quality can be applied to safeguard health and vegetation.

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

The environmental factors contributing to the Microcystis aeruginosa bloom (hereafter referred to as Microcystis bloom) are still debatable as they vary with season and geographic settings. We examined the environmental factors that triggered Microcystis bloom outbreak in India's largest brackish water coastal lagoon, Chilika. The warmer water temperature (25.31-32.48 °C), higher dissolved inorganic nitrogen (DIN) loading (10.15-13.53 μmol L^-1), strong P-limitation (N:P ratio 138.47-246.86), higher water transparency (46.62-73.38 cm), and low-salinity (5.45-9.15) exerted a strong positive influence on blooming process. During the bloom outbreak, M. aeruginosa proliferated, replaced diatoms, and constituted 70-88% of the total phytoplankton population. The abundances of M. aeruginosa increased from 0.89 × 10⁴ cells L^-1 in September to 1.85 × 10⁴ cells L^-1 in November and reduced drastically during bloom collapse (6.22 × 10³ cells L^-1) by the late November of year 2017. The decrease in M. aeruginosa during bloom collapse was associated with a decline in DIN loading (2.97 μmol L^-1) and N:P ratio (73.95). Sentinel-3 OLCI-based satellite monitoring corroborated the field observations showing Cyanophyta Index (CI) > 0.01 in September, indicative of intense bloom and CI < 0.0001 during late November, suggesting bloom collapse. The presence of M. aeruginosa altered the phytoplankton community composition. Furthermore, co-occurrence network indicated that bloom resulted in a less stable community with low diversity, inter-connectedness, and prominence of a negative association between phytoplankton taxa. Variance partitioning analysis revealed that TSM (16.63%), salinity (6.99%), DIN (5.21%), and transparency (5.15%) were the most influential environmental factors controlling the phytoplankton composition. This study provides new insight into the phytoplankton co-occurrences and combination of environmental factors triggering the rapid onset of Microcystis bloom and influencing the phytoplankton composition dynamics of a large coastal lagoon. These findings would be valuable for future bloom forecast modeling and aid in the management of the lagoon.

Seasonal Variation Characteristics and the Factors Affecting Plankton Community Structure in the Yitong River, China

To explore how environmental factors affected the plankton structure in the Yitong River, we surveyed the water environmental factors and plankton population in different seasons. The results showed high total nitrogen concentrations in Yitong River throughout the year, while the total phosphorus, water temperature (WT), and chemical oxygen demand in summer were significantly higher than those in other seasons (p < 0.05), and the dissolved oxygen (DO) concentrations and TN/TP ratio were significantly lower (p < 0.01) than those in other seasons. There was no significant seasonal change in other environmental factors. Cyanophyta, Chlorophyta, and Bacillariophyta were the main phytoplankton phylum, while Protozoa and Rotifera were the main zooplankton phylum. The abundance and biomass of zooplankton and phytoplankton in the summer were higher than those in other seasons. Non-Metric Multidimensional scaling methods demonstrated obvious seasonal variation of phytoplankton in summer compared to spring and winter, while the seasonal variation of the zooplankton community was not obvious. The results of the redundancy analysis showed that WT, DO and nitrate nitrogen were the main environmental factors affecting phytoplankton abundance. In contrast to environmental factors, phytoplankton was the main factor driving the seasonal variation of the zooplankton community structure. Cyanophyta were positively correlated with the changes in the plankton community.