Response of OC, TN, and TP deposition mediated by aquatic photosynthetic community structures in shallow karst surface waters under different land uses

Multi-machine learning methods to predict spatial variation characteristics of total nitrogen at watershed scale: Evidences from the largest watershed (Yangtze River Watershed), Asian

Nitrogen pollution has emerged as a significant threat to the health of global river systems, garnering considerable attention. However, numerous challenges persist in understanding the characteristics and predicting the spatial changes of total nitrogen (TN) at the catchment scale. We leveraged data from 530 monitoring sections to calculate a land-use composite index and perform statistical analyses to explore the primary factors influencing nitrogen enrichment in the Yangtze River Watershed. We developed three machine learning models to forecast future TN concentrations at monitoring points. Our results showed that agricultural activities and rainfall were the primary drivers of monthly variations in TN concentrations. The upstream region of the watershed exhibited larger variations in TN concentrations (0.097 to 11.099 mg/L), significantly higher than the middle and downstream areas (0.348 to 6.844 mg/L). Microbial-mediated organic matter decomposition in sediment and changes in land-use were identified as key contributors to regional differences in nitrogen enrichment. Potential nitrogen sources include sediment release, urban sewage, and agricultural fertilization. Random Forest model achieved a prediction accuracy of 77.6 %, surpassing the BP and LSTM models. We identified 37 high-risk areas of nitrogen enrichment, concentrated in the Chengdu-Chongqing, Yunnan-Central urban cluster, and the Chaohu Lake sub-watershed. Increased urban land-use and industrial inputs primarily influenced nitrogen enrichment in the upstream area, while agricultural inputs were the main drivers in the middle and downstream regions. Our multi-machine learning models identified the relationship between TN and influencing factors, providing a reliable method for assessing nitrogen enrichment risk in the watershed.

Effects of carbon limitation and carbon fertilization on karst lake-reservoir productivity

Nitrogen and phosphorus are universally recognized as limiting elements in the eutrophication processes affecting the majority of the world's lakes, reservoirs, and coastal ecosystems. However, despite extensive research spanning several decades, critical questions in eutrophication science remain unanswered. For example, there is still much to understand about the interactions between carbon limitation and ecosystem stability, and the availability of carbon components adds significant complexity to aquatic resource management. Mounting evidence suggests that aqueous CO2 could be a limiting factor, influencing the structure and succession of aquatic plant communities, especially in karstic lake and reservoir ecosystems. Moreover, the fertilization effect of aqueous CO2 has the potential to enhance carbon sequestration and phosphorus removal. Therefore, it is important to address these uncertainties to achieve multiple positive outcomes, including improved water quality and increased carbon sinks in karst lakes and reservoirs.

Control of carbon dioxide exchange fluxes by rainfall and biological carbon pump in karst river-lake systems

As an important component of inland water, the primary factors affecting the carbon cycle in karst river-lake systems require further investigation. In particular, the impacts of climatic factors and the biological carbon pump (BCP) on carbon dioxide (CO2) exchange fluxes in karst rivers and lakes deserve considerable attention. Using quarterly sampling, field monitoring, and meteorological data collection, the spatiotemporal characteristics of CO2 exchange fluxes in Erhai Lake (a typical karst lake in Yunnan, SW China) and its inflow rivers were investigated and the primary influencing factors were analyzed. The average river CO2 exchange flux reached 346.80 mg m-2 h-1, compared to -6.93 mg m-2 h-1 for the lake. The carbon cycle in rivers was strongly influenced by land use within the basin; cultivated and construction land were the main contributors to organic carbon (OC) in the river (r = 0.66, p < 0.01) and the mineralization of OC was a major factor in CO2 oversaturation in most rivers (r = 0.76, p < 0.01). In addition, the BCP effect of aquatic plants and the high pH in karst river-lake systems enhance the ability of water body to absorb CO2, resulting in undersaturated CO2 levels in the lake. Notably, under rainfall regulation, riverine OC and dissolved inorganic carbon (DIC) flux inputs controlled the level of CO2 exchange fluxes in the lake (rOC = 0.78, p < 0.05; rDIC = 0.97, p < 0.01). We speculate that under future climate and human activity scenarios, the DIC and OC input from rivers may alleviate the CO2 limitation of BCP effects in karst eutrophication lakes, possibly enabling aquatic plants to convert more CO2 into OC for burial. The results of this research can help advance our understanding of CO2 emissions and absorption mechanisms in karst river-lake systems.

Toward an intensive understanding of sewer sediment prokaryotic community assembly and function

Prokaryotic communities play important roles in sewer sediment ecosystems, but the community composition, functional potential, and assembly mechanisms of sewer sediment prokaryotic communities are still poorly understood. Here, we studied the sediment prokaryotic communities in different urban functional areas (multifunctional, commercial, and residential areas) through 16S rRNA gene amplicon sequencing. Our results suggested that the compositions of prokaryotic communities varied significantly among functional areas. Desulfomicrobium, Desulfovibrio, and Desulfobacter involved in the sulfur cycle and some hydrolytic fermentation bacteria were enriched in multifunctional area, while Methanospirillum and Methanoregulaceae, which were related to methane metabolism were significantly discriminant taxa in the commercial area. Physicochemical properties were closely related to overall community changes (p < 0.001), especially the nutrient levels of sediments (i.e., total nitrogen and total phosphorus) and sediment pH. Network analysis revealed that the prokaryotic community network of the residential area sediment was more complex than the other functional areas, suggesting higher stability of the prokaryotic community in the residential area. Stochastic processes dominated the construction of the prokaryotic community. These results expand our understanding of the characteristics of prokaryotic communities in sewer sediment, providing a new perspective for studying sewer sediment prokaryotic community structure.