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Bacterial communities inhabiting alpine lakes are essential to our understanding of ecosystem processes in a changing climate, but little has been reported about the vertical patterns of sediment bacterial communities in alpine lakes. To address this knowledge gap, we collected the 100 cm long sediment core from the center of Lake Sayram, the largest alpine lake in Xinjiang Uygur autonomous area, China, and used 16S rRNA gene-targeted amplicon sequencing to examine the bacterial populations. The results showed that bacterial diversity, as estimated by the Shannon index, was highest at the surface (6.9849 at 0–4 cm) and gradually decreased with depth up to 3.9983 at 68–72 cm, and then increased to 5.0927 at 96–100 cm. A total of 56 different phyla and 1204 distinct genera were observed in the sediment core of Lake Sayram. The bacterial community structure in the sediment samples from the various layers was dissimilar. The most abundant phyla in alpine Lake Sayram were Proteobacteria, Firmicutes, and Planctomycetes, accounting for 73%, 6%, and 4% of the total reads, respectively; the most abundant genera were Acinetobacter, Hydrogenophaga, and Pseudomonas, accounting for 18%, 12%, and 8% of the total reads, respectively. Furthermore, the relative abundance of Acinetobacter increased with sediment depth, while the relative abundance of Hydrogenophaga and Pseudomonas decreased with sediment depth. Our findings indicated that the nitrate-reducing bacteria (Acinetobacter, Hydrogenophaga, and Pseudomonas) may be prevalent in the sediment core of Lake Sayram. Canonical correspondence analysis showed that carbonate and total organic carbon (TOC) may be the main environmental factors affecting the vertical patterns of bacterial community composition (BCC) in the sediment of Lake Sayram. This work significantly contributes to our understanding of the BCC of sediments from alpine lakes in arid and semiarid regions.

In eutrophic lakes, even if external loading is controlled, internal nutrient loading delays the recovery of lake eutrophication. When the input of external pollutants is reduced, the dissolved oxygen environment at the sediment interface improves in a season without algal blooms. As an important part of lake ecosystems, macroinvertebrates are sensitive to hypoxia caused by eutrophication; however, how this change affects macroinvertebrates is still unknown. In this study, we analysed the monitoring data of northern Lake Taihu from 2007 to 2019. After 2007, the external loading of Lake Taihu was relatively stable, but eutrophication began to intensify after 2013, and the nutrients in the sediments also began to decline, which was related to the efficient use of nutrients by algal blooms. The community structure and population density of macroinvertebrates showed different responses in different stages. In particular, the density of oligochaetes and the Shannon–Wiener index showed significant differences in their response to different stages, and their sensitivity to eutrophication was significantly reduced. Under eutrophication conditions dominated by internal loading, frequent hypoxia occurs at the sediment interface only when an algal bloom erupts. When there is no bloom, the probability of sediment hypoxia is significantly reduced under the disturbance of wind. Our results indicate that the current method for evaluating lake eutrophication based on oligochaetes and the Shannon–Wiener diversity index may lose its sensitivity.

Algal blooms are environmental challenges confronting lakes worldwide and are significantly influenced by chlorophyll a yields per unit phosphorus (Chla/TP), or nitrogen (Chla/TN). Here, the influence of inter-annual hydrometeorological variations on Chla/TP and Chla/TN were evaluated in eutrophic shallow Lake Taihu, China. Our results demonstrated significant increases (p < 0.001) in both Chla/TN and Chla/TP from 2005 to 2017, and increased Chla yields during the winter months were mainly correlated with higher water temperature and longer sunshine hours, which may cause severer blooms in winter and spring. In remaining months from 2005 to 2017, typical associations between atmospheric stilling (or water level elevation) and higher Chla yields were observed. The results also indicate that atmospheric stilling and water level elevation significantly (p < 0.001) decreased background turbidity and promoted buoyant cyanobacterial biomass, alleviating phytoplankton light limitation. Given the subtropical location, eutrophic status, and high background turbidity of Lake Taihu, light may be the critical limiting factor for summer phytoplankton growth; thus, improved light availability would promote Chla yields until self-shading caused further light limitations. If the mechanism is general, promoting the effect of atmospheric stilling on annual peak Chla in shallow lakes may be greatly underestimated, and our finding will affect future bloom mitigation efforts in such systems.

Due to the recent decades of climate change and intensive human activities, endorheic lakes are threatened by both salinization and eutrophication. However, knowledge of the aquatic bacterial community’s response to simultaneous increasing salinity and trophic status is still poor. To address this knowledge gap, we collected 40 surface water samples from five lakes and six rivers on the semi-arid Inner Mongolia Plateau, and investigated their bacterial communities using 16S rRNA gene-targeted amplicon sequencing. We found that bacterial species diversity significantly decreased from the mesotrophic freshwater river habitat to the eutrophic high-brackish lake habitat; salinity was more important than trophic status in explaining this decreased diversity. Salinity was the most important environmental factor in shaping community composition, while increased nitrogen loading was more important in structuring predicted functional composition. Within the lake habitats, the impact of environmental filtering on bacterial community assembly increased with the increasing salinity. The results suggested that the elevated salinity and nutrients have combined effects on the aquatic bacterial community, resulting in dramatic declines in species diversity, and promoted the importance of deterministic processes in community assembly. Our findings provide new insights into bacterial communities’ responses to the intensified climate-driven and anthropogenic environmental changes in aquatic ecosystems.

Aquatic vegetation serves many important ecological and socioeconomic functions in lake ecosystems. The presence of floating algae poses difficulties for accurately estimating the distribution of aquatic vegetation in eutrophic lakes. We present an approach to map the distribution of aquatic vegetation in Lake Taihu (a large, shallow eutrophic lake in China) and reduce the influence of floating algae on aquatic vegetation mapping. Our approach involved a frequency analysis over a 2003–2013 time series of the floating algal index (FAI) based on moderate-resolution imaging spectroradiometer (MODIS) data. Three phenological periods were defined based on the vegetation presence frequency (VPF) and the growth of algae and aquatic vegetation: December and January composed the period of wintering aquatic vegetation; February and March composed the period of prolonged coexistence of algal blooms and wintering aquatic vegetation; and June to October was the peak period of the coexistence of algal blooms and aquatic vegetation. By comparing and analyzing the satellite-derived aquatic vegetation distribution and 244 in situ measurements made in 2013, we established a FAI threshold of −0.025 and VPF thresholds of 0.55, 0.45 and 0.85 for the three phenological periods. We validated the accuracy of our approach by comparing the results between the satellite-derived maps and the in situ results obtained from 2008–2012. The overall classification accuracy was 87%, 81%, 77%, 88% and 73% in the five years from 2008–2012, respectively. We then applied the approach to the MODIS images from 2003–2013 and obtained the total area of the aquatic vegetation, which varied from 265.94 km2 in 2007 to 503.38 km2 in 2008, with an average area of 359.62 ± 69.20 km2 over the 11 years. Our findings suggest that (1) the proposed approach can be used to map the distribution of aquatic vegetation in eutrophic algae-rich waters and (2) dramatic changes occurred in the distribution of aquatic vegetation in Lake Taihu during the 11-year study.

This study presents results from field surveys performed over various seasons in a large, eutrophic, shallow lake (Lake Taihu, China) using an in situ chromophoric dissolved organic matter (CDOM) fluorescence sensor as a surrogate for other water quality parameters. These measurements identified highly significant empirical relationships between CDOM concentration measured using the in situ fluorescence sensor and CDOM absorption, fluorescence, dissolved organic carbon (DOC), chemical oxygen demand (COD) and total phosphorus (TP) concentrations. CDOM concentration expressed in quinine sulfate equivalent units, was highly correlated with the CDOM absorption coefficient (r2 = 0.80, p < 0.001), fluorescence intensities (Ex./Em. 370/460 nm) (r2 = 0.91, p < 0.001), the fluorescence index (r2 = 0.88, p < 0.001) and the humification index (r2 = 0.78, p < 0.001), suggesting that CDOM concentration measured using the in situ fluorescence sensor could act as a substitute for the CDOM absorption coefficient and fluorescence measured in the laboratory. Similarly, CDOM concentration was highly correlated with DOC concentration (r2 = 0.68, p < 0.001), indicating that in situ CDOM fluorescence sensor measurements could be a proxy for DOC concentration. In addition, significant positive correlations were found between laboratory CDOM absorption coefficients and COD (r2 = 0.83, p < 0.001), TP (r2 = 0.82, p < 0.001) concentrations, suggesting a potential further application for the real-time monitoring of water quality using an in situ CDOM fluorescence sensor.

The Secchi disk depth (ZSD, m) has been used globally for many decades to represent water clarity and an index of water quality and eutrophication. In recent studies, a new theory and model were developed for ZSD, which enabled its semi-analytical remote sensing from the measurement of water color. Although excellent performance was reported for measurements in both oceanic and coastal waters, its reliability for highly turbid inland waters is still unknown. In this study, we extend this model and its evaluation to such environments. In particular, because the accuracy of the inherent optical properties (IOPs) derived from remote sensing reflectance (Rrs, sr−1) plays a key role in determining the reliability of estimated ZSD, we first evaluated a few quasi-analytical algorithms (QAA) specifically tuned for turbid inland waters and determined the one (QAATI) that performed the best in such environments. For the absorption coefficient at 443 nm (a(443), m−1) ranging from ~0.2 to 12.5 m−1, it is found that the QAATI-derived absorption coefficients agree well with field measurements (r2 > 0.85, and mean absolute percentage difference (MAPD) smaller than ~39%). Furthermore, with QAATI-derived IOPs, the MAPD was less than 25% between the estimated and field-measured ZSD (r2 > 0.67, ZSD in a range of 0.1−1.7 m). Furthermore, using matchup data between Rrs from the Medium Resolution Imaging Spectrometer (MERIS) and in-situ ZSD, a similar performance in the estimation of ZSD from remote sensing was obtained (r2 = 0.73, MAPD = 37%, ZSD in a range of 0.1−0.9 m). Based on such performances, we are confident to apply the ZSD remote sensing scheme to MERIS measurements to characterize the spatial and temporal variations of ZSD in Lake Taihu during the period of 2003−2011.

The Tiaoxi River is the main source of water for Lake Taihu and can result in plumes in the lake after heavy precipitation events. These plumes have played a crucial role in the water quality changes within the lake. High temporal resolution GOCI (Geostationary Ocean Color Imager) data were used to study the spatial distribution of the total suspended matter concentration in Lake Taihu after heavy precipitation events in the Tiaoxi River Basin via an empirical model. The plumes were analyzed after two heavy precipitation events in 2011 and 2013 using 16 GOCI images, which indicated that the Tiaoxi River had a great influence on the spatial distributions of total suspended matter and algal blooms. It was concluded that the main factors affecting the plumes in the Tiaoxi River were precipitation intensity, runoff, and total suspended matter concentration. Human activity, such as sand excavation also played a crucial role in sediment discharge. The results of this study demonstrate that the visualization of GOCI data makes it possible to use remote sensing technology to continuously monitor an inland water environment on an hourly scale, which is of great significance for studying the diffusion and evolution of river plumes.