Seasonal variation significantly affected bacterioplankton and eukaryoplankton community composition in Xijiang River, China

Water periods impact the structure and metabolic potential of the nitrogen-cycling microbial communities in rivers of arid and semi-arid regions

This study examined the influence of water periods on river nitrogen cycling by analysing nitrogen functional genes and bacterial communities in the Qingshui River, an upstream tributary of the Yellow River in China. Nitrate nitrogen predominated as inorganic nitrogen during the low-flow seasons, whereas salinity was highest during the high-flow seasons. Overall, the functional gene abundance increased with decreasing water volume, and nitrogen concentrations were determined by various specific gene groups. The relative abundance of bacteria carrying these genes varied significantly across water periods. The abundance of Pseudomona, Hydrogenophaga (carrying narGHI and nirB genes), and Flavobacterium (carrying nirK, norBC, and nosZ genes) significantly increased during the low-flow seasons. Nitrogen transformation bacteria exhibited both symbiotic and mutualistic relationships. Microbial network nodes and sizes decreased with decreasing water volume, whereas modularity increased. Additionally, the water period affected the functional microbial community structure by influencing specific environmental factors. Among them, SO42- primarily determined the denitrification, dissimilatory nitrate reduction to ammonium, and assimilatory nitrate reduction to ammonium communities, whereas NO2--N and Mg2+ were the main driving factors for the nitrogen-fixing and nitrifying communities, respectively. These findings have substantial implications for better understanding the reduction in river nitrogen loads in arid and semi-arid regions during different water periods.

Exploring the environmental influences and community assembly processes of bacterioplankton in a subtropical coastal system: Insights from the Beibu Gulf in China

Due to rapid urbanization, the Beibu Gulf, a semi-closed gulf in the northwestern South China Sea, faces escalating ecological and environmental threats. Understanding the assembly mechanisms and driving factors of bacterioplankton in the Beibu Gulf is crucial for preserving its ecological functions and services. In the present study, we investigated the spatiotemporal dynamics of bacterioplankton communities and their assembly mechanisms in the Beibu Gulf based on the high-throughput sequencing of the bacterial 16 S rRNA gene. Results showed significantly higher bacterioplankton diversity during the wet season compared to the dry season. Additionally, distinct seasonal variations in bacterioplankton composition were observed, characterized by an increase in Cyanobacteria and Thermoplasmatota and a decrease in Proteobacteria and Bacteroidota during the wet season. Null model analysis revealed that stochastic processes governed bacterioplankton community assembly in the Beibu Gulf, with drift and homogenizing dispersal dominating during the dry and wet seasons, respectively. Enhanced deterministic assembly of bacterioplankton was also observed during the wet season. Redundancy and random forest model analyses identified the physical properties (e.g., temperature) and nutrient content (e.g., nitrate) of water as primary environmental drivers influencing bacterioplankton dynamics. Moreover, variation partitioning and distance-decay of similarity revealed that environmental filtering played a significant role in shaping bacterioplankton variations in this rapidly developed coastal ecosystem. These findings advance our understanding of bacterioplankton assembly in coastal ecosystems and establish a theoretical basis for effective ecological health management amidst ongoing global changes.

Insight into diversity change, variability and co-occurrence patterns of phytoplankton assemblage in headwater streams: a study of the Xijiang River basin, South China

Phytoplankton has been used as a paradigm for studies of coexistence of species since the publication of the "paradox of the plankton." Although there are a wealth of studies about phytoplankton assemblages of lakes, reservoirs and rivers, our knowledge about phytoplankton biodiversity and its underlying mechanisms in mountain headwater stream ecosystems is limited, especially across regional scales with broad environmental gradients. In this study, we collected 144 phytoplankton samples from the Xijiang headwater streams of the Pearl River across low altitude (< 1,000 m) located in Guangxi province, intermediate altitude (1,000 m < altitude <2,000 m) in Guizhou province and high altitude (> 2,000 m) in Yunnan province of China. Our study revealed high phytoplankton diversity in these streams. Freshwater phytoplankton, including cyanobacteria, Bacillariophyta, Chlorophyta, Rhodophyta, Chrysophyta, Euglenophyta, Glaucophyta, Phaeophyta and Cryptophyta, were all detected. However, phytoplankton alpha diversity exhibited a monotonic decreasing relationship with increasing altitude. High altitudes amplified the "isolated island" effect of headwater streams on phytoplankton assemblages, which were characterized by lower homogeneous selection and higher dispersal limitation. Variability and network vulnerability of phytoplankton assemblages increased with increasing altitudes. Our findings demonstrated diversity, variability and co-occurrence patterns of phytoplankton assemblages linked to environmental factors co-varying with altitude across regional scales.

Method for screening water physicochemical parameters to calculate water quality index based on these parameters' correlation with water microbiota

Water quality index (WQI) plays a crucial role in guiding water resource management. However, WQI calculation methods are not uniform, especially the selection of water parameters and the weighting given to each water parameter (P_i). To optimize WQI calculation, 132 water samples from seven rivers and from Chaohu Lake (33 sampling sites in Chaohu Lake Basin) in four seasons were collected, and the water parameters and microbiota composition were analyzed using high-throughput sequencing of 16 S rDNA. The correlation coefficient R² between water parameters and microbiota composition using redundancy analysis with the Monte Carlo method were calculated, and the water parameters that significantly correlated with the microbiota composition were selected to calculate WQI_min. The results showed that TP, COD, DO, and Chl a correlated significantly with water microbiota composition. WQI_b calculated by substituting R² for P_i was more consistent with the similarity between the microbiota compositions. WQI_minb calculated using TP, COD, and DO was consistent with WQI_b. The results of WQI_b and WQI_minb were more consistent than those of WQI and WQI_min. These results imply that using R² instead of P_i could help obtain a more stable WQI_b that could better reflect the biological characteristics of the Chaohu Lake Basin.

Dynamics of Bacterioplankton Communities during Wet and Dry Seasons in the Danjiangkou Reservoir in Hubei, China

Water quality is directly linked to drinking water safety for millions of people receiving the water. The Danjiangkou Reservoir is the main water source for the Middle Route of the South-to-North Water Diversion Project (MR-SNWDP), located in the vicinity of Henan and Hubei provinces in China. Aquatic microorganisms are key indicators of biologically assessing and monitoring the water quality of the reservoir as they are sensitive to environmental and water quality changes. This study aimed to investigate the spatiotemporal variations in bacterioplankton communities during wet (April) and dry (October) seasons at eight monitoring points in Hanku reservoir and five monitoring points in Danku reservoir. Each time point had three replicates, labeled as wet season Hanku (WH), wet season Danku (WD), dry season Hanku (DH), and dry season Danku (DD) of Danjiangkou Reservoir in 2021. High-throughput sequencing (Illumina PE250) of the 16S rRNA gene was performed, and alpha (ACE and Shannon) and beta (PCoA and NDMS) diversity indices were analyzed. The results showed that the dry season (DH and DD) had more diverse bacterioplankton communities compared to the wet season (WH and WD). Proteobacteria, Actinobacteria, and Firmicutes were the most abundant phyla, and Acinetobacter, Exiguobacterium, and Planomicrobium were abundant in the wet season, while polynucleobacter was abundant in the dry season. The functional prediction of metabolic pathways revealed six major functions including carbohydrate metabolism, membrane transport, amino acid metabolism, signal transduction, and energy metabolism. Redundancy analysis showed that environmental parameters greatly affected bacterioplankton diversity during the dry season compared to the wet season. The findings suggest that seasonality has a significant impact on bacterioplankton communities, and the dry season has more diverse communities influenced by environmental parameters. Further, the relatively high abundance of certain bacteria such as Acinetobacter deteriorated the water quality during the wet season compared to the dry season. Our findings have significant implications for water resource management in China, and other countries facing similar challenges. However, further investigations are required to elucidate the role of environmental parameters in influencing bacterioplankton diversity in order to devise potential strategies for improving water quality management in the reservoir.