Understanding microbial communities in terms of taxon and function is essential to decipher the biogeochemical cycling in aquatic ecosystems. Lakes and their input streams are highly linked. However, the differences between microbial assemblages in streams and lakes are still unclear. In this study, we conducted an intensive field sampling of microbial communities from lake water and stream biofilms in the Qinghai Lake watershed, the largest lake in China. We determined bacterial communities using high-throughput 16S rRNA gene sequencing and predicted functional profiles using PICRUSt to determine the taxonomic and functional differences between microbial communities in stream biofilms and lake water. The results showed that stream biofilms and lake water harbored distinct microbial communities. The microbial communities were different taxonomically and functionally between stream and lake. Moreover, streams biofilms had a microbial network with higher connectivity and modularity than lake water. Functional beta diversity was strongly correlated with taxonomic beta diversity in both the stream and lake microbial communities. Lake microbial assemblages displayed greater predicted metabolic potentials of many metabolism pathways while the microbial assemblages in stream biofilms were more abundant in xenobiotic biodegradation and metabolism and lipid metabolism. Furthermore, lake microbial assemblages had stronger predicted metabolic potentials in amino acid metabolism, carbon fixation, and photosynthesis while stream microbial assemblages were higher in carbohydrate metabolism, oxidative phosphorylation, and nitrogen metabolism. This study adds to our knowledge of stream-lake linkages from the functional and taxonomic composition of microbial assemblages.

Urban storm runoff is a major source of pollutants in receiving water bodies. To assess the impact of urban stormwater runoff on an urban river, the runoff process of total suspended solids (TSS), chemical oxygen demand (COD), ammonium (NH₄), and total phosphorus (TP) were investigated on road surfaces classified as arterial road (AR), residential area (RA), and industrial area (IA) in the Pingshan River (PSR) watershed in Shenzhen, China. Event mean concentration (EMC) was calculated to analyze the water quality of road runoff, and the dimensionless M(V) cumulative curves were used to estimate the course of decreasing concentration of runoff pollutants during each rainfall event. Multicriteria decision making methods (PROMETHEE-GAIA) were used to identify the linkage between runoff pollutants, land use types, and rainfall intensity. The EMCs of COD and TP in runoff exceeded the class IV level of the water quality standard for surface water (China). RA was a major potential source for NH₄, COD, and TP in the river. Controlling the first flush is critical to decrease the effect of road runoff on receiving water bodies, as most runoff pollutants in AR, RA, and IA had a first flush effect during heavy rainfall. The specific management measure for runoff pollution varied with land use type. Reducing road TSS concentrations was effective for controlling runoff pollution in AR and RA because NH₄, TP, and COD attached to particulate matter. In IA, the collection and reuse of stormwater in the initial rainfall period were effective for reducing the effect of soluble pollutants in runoff on receiving water bodies. This study provides new information for managing urban road stormwater runoff in different land use types.

Networks of lakes and streams are linked by downslope flows of material and energy within catchments. Understanding how bacterial assemblages are associated with nutrients and stoichiometric gradients in lakes and streams is essential for understanding biogeochemical cycling in freshwater ecosystems. In this study, we conducted field sampling of bacterial communities from lake water and stream biofilms in Erhai Lake watershed. We determined bacterial communities using high-throughput 16S rRNA gene sequencing and explored the relationship between bacterial composition and environmental factors using networking analysis, canonical correspondence analysis (CCA), and variation partitioning analysis (VPA). Physicochemical parameters, nutrients, and nutrient ratios gradients between the lake and the streams were strongly associated with the differences in community composition and the dominant taxa. Cyanobacteria dominated in Erhai Lake, while Proteobacteria dominated in streams. The stream bacterial network was more stable with multiple stressors, including physicochemical-factors and nutrient-factors, while the lake bacterial network was more fragile and susceptible to human activities with dominant nutrients (phosphorus). Negative correlations between bacterial communities and soluble reactive phosphorus (SRP) as well as positive correlations between bacterial communities and dissolved organic carbon (DOC) in the network indicated these factors had strong effect on bacterial succession. Erhai Lake is in a eutrophic state, and high relative abundances of Synechococcus (40.62%) and Microcystis (16.2%) were noted during the course of our study. CCA indicated that nutrients (phosphorus) were key parameters driving Cyanobacteria-dominated community structure. By classifying the environmental factors into five categories, VPA analyses identified that P-factor (total phosphorus (TP) and SRP) as well as the synergistic effect of C-factor (DOC), N-factor (NO₃⁻), and P-factor (TP and SRP) played a central role in structuring the bacterial communities in Erhai Lake. Heterogeneous physicochemical conditions explained the variations in bacterial assemblages in streams. This study provides a picture of stream–lake linkages from the perspective of bacterial community structure as well as key factors driving bacterial assemblages within lakes and streams at the whole watershed scale. We further argue that better management of phosphorus on the watershed scale is needed for ameliorating eutrophication of Erhai Lake.