Composition, interaction networks, and nitrogen metabolism patterns of bacterioplankton communities in a grassland type Lake: a case of Hulun Lake, China

The composition of bacterial communities in freshwater ecosystems is influenced by numerous factors including environmental conditions and biological interactions. In grassland inland closed lakes, factors affecting lake ecosystems are either exogenous or endogenous, contributing to the formation of distinct habitats in the surface and bottom waters of the bacterial communities. However, the extent to which environmental factors selectively shape the bacterial communities in aquatic systems remains unclear. Therefore, we sampled the surface, middle, and bottom waters at 13 sampling points in each layer. High-throughput sequencing techniques were employed to examine the spatial heterogeneity of the bacterial community structure during summer in Hulun Lake, the largest grassland-type lake in Inner Mongolia, China, to determine the microbial community dynamics and symbiosis patterns under different habitat conditions. Our results revealed a decrease in the diversity and heterogeneity of the bacterioplankton community, influenced by changes in the environment from exogenous inputs to endogenous releases. Furthermore, this alteration in community structure was concomitant with enhanced co-occurrences among microorganisms in the bottom water layers. This finding suggests that endogenous release promotes heightened symbiotic interactions, thereby facilitating the development of more complex modular structures. Symbiotic networks in different layers were differentiated by key species, with the ecological clustering modules of these species demonstrating dissimilar environmental preferences. The microbial communities were highly habitat-specific, mimicking responses to total nitrogen (TN) in the surface layer, pH in the middle layer, and chemical oxygen demand (COD) in the bottom layer. Bacterioplankton functions were assessed using Tax4Fun, indicating exogenous inputs and endogenous release increased the relative abundance of genes with nitrogen-fixing and nitrification potential nitrogen metabolism functions in surface and bottom waters, respectively. With Planctomycetota and Proteobacteria phyla as potential key groups for regulating nitrogen metabolic processes, Proteobacteria may facilitate the depletion of nitrate in surface and bottom waters, while the close contact of surface waters with the atmosphere accelerated Planctomycetota-dominated nitrogen fixation into the lake. Our findings contribute to the understanding of vertical microbial diversity and its network patterns in grassland type lakes, underscoring the potential role of environmental factors (exogenous inputs and endogenous releases) in bacterioplankton community formation

Remote Sensing of Surface Water Dynamics in the Context of Global Change - A Review

Inland surface water is often the most accessible freshwater source. As opposed to groundwater, surface water is replenished in a comparatively quick cycle, which makes this vital resource—if not overexploited—sustainable. From a global perspective, freshwater is plentiful. Still, depending on the region, surface water availability is severely limited. Additionally, climate change and human interventions act as large-scale drivers and cause dramatic changes in established surface water dynamics. Actions have to be taken to secure sustainable water availability and usage. This requires informed decision making based on reliable environmental data. Monitoring inland surface water dynamics is therefore more important than ever. Remote sensing is able to delineate surface water in a number of ways by using optical as well as active and passive microwave sensors. In this review, we look at the proceedings within this discipline by reviewing 233 scientific works. We provide an extensive overview of used sensors, the spatial and temporal resolution of studies, their thematic foci, and their spatial distribution. We observe that a wide array of available sensors and datasets, along with increasing computing capacities, have shaped the field over the last years. Multiple global analysis-ready products are available for investigating surface water area dynamics, but so far none offer high spatial and temporal resolution