Influence of long-term inundation and nutrient addition on denitrification in sandy wetland sediments from Poyang Lake, a large shallow subtropical lake in China

Impact of water level management on organic carbon availability and nitrogen transformations in wetland sediments

The impact of water level management via water retention on benthic carbon and nitrogen fluxes was studied in a wetland of the Seine estuary. Carbon and inorganic nitrogen fluxes at the sediment-water interface were determined during periods of intermittent and permanent immersion along a lateral gradient. In addition to fluxes, nitrate reduction rates, quantity and quality of both sedimentary and dissolved organic carbon, and organic matter lability via external enzymatic activities were analyzed. During both periods, the sediments subject to water level management facilitated nitrogen removal, with potential NO3- fluxes averaging -109 ± 31 nmol NO3- cm-2 h-1 under permanent immersion and -34 ± 13 nmol NO3- cm-2 h-1 under intermittent immersion. During permanent immersion, more water retention favors a higher input of dissolved organic matter including fresh and labile compounds, which most likely explained the significantly higher NO3- influxes. Intermittent immersion resulted in a lower quantity of retained dissolved organic matter, which likely explains the low N fluxes. The results of this study indicate the implementation of water retention strategies can markedly enhance NO3- removal by increasing the availability of organic matter. This underscores the importance of considering water-level management of wetlands to sustain the ecological functions of these valuable ecosystems, which are often the first barriers against environmental disturbance.

An indispensable role of overlying water in nitrogen removal in shallow lakes

The nitrogen (N) removal characteristics in water columns and sediments of shallow lakes, influenced by various factors, may exhibit spatial variations in lakes with algal-macrophyte dominance. The N removal rates in water columns and sediments of Lake Taihu were investigated. Our findings indicated that the total N removal rates in Lake Taihu followed the order of algae-dominance > macrophyte-dominance > pelagic lake (without the presence of algae and macrophytes). Correlation analysis revealed that the key environmental factors affecting denitrification and anammox in sediments of algae/macrophyte-type lakes were nitrate nitrogen (NO3--N), nitrite nitrogen (NO2--N), ammonia nitrogen (NH4+-N), and chlorophyll a (Chl-a). The linear regression demonstrated that a significant correlation between the denitrification and the anammox in sediments, with a correlation coefficient of 0.81 (p < 0.01). The contributions to N removal from the water columns and sediments in Lake Taihu were 53 % and 47 %, respectively. Denitrification predominantly drove N removal from sediments, whereas anammox dominated the N removal in water columns. Thus, N removal from the water columns is nonnegligible in shallow eutrophic lakes. This study enhances our understanding of N biogeochemical cycling dynamics in sediment-water and algae/macrophyte ecosystems across various shallow eutrophic lake regions.

How internal nutrient loading forms in shallow lakes: Insights from benthic organic matter mineralization

Internal nutrient loading in shallow lakes has long been known as a key driver of eutrophication, especially after external loading reductions. Earlier efforts have been made to quantity the size and potential release of internal nutrient pools in lakes. Yet, links among substrates, microbial processes, and the size and actual release of internal nutrient pools remain largely unclear. To assess the links, sediment organic matter in Lake Taihu, China, was characterized by combining optical measurements, and lake-wide sediment gross nitrogen (N) transformations were measured using the stable isotope (15N) dilution technique. Meanwhile, respirations and nutrient fluxes across the sediment-water interface (SWI) were measured by conducting intact core continuous-flow incubations. The cause-effect relationships among sediment physicochemical parameters (especially organic matter properties), gross N transformations, extractable nutrient concentrations, and nutrient fluxes across the SWI were revealed by partial least square path models. Results showed that environmental controls on the N transformation rates at different seasons varied, with sediment-derived dissolved organic matter abundance being more important than other variables in driving the rates during summer blooms. This study put a step toward revealing the significant positive effects of sediment organic matter mineralization on porewater nutrient concentrations and then on nutrient fluxes across the SWI at late season. The significant positive correlation between the gross N mineralization rates and ammonium fluxes across the SWI and the estimated considerable volume of net N mineralization in summer further suggested that algal blooms can get substantial inorganic N from sediment N mineralization during the lake N limitation period. Overall, this paper presents new insights into the substrates- and microbial process-driven internal nutrient loading of shallow lakes, which is the fundamental driving force of internal nutrient loading formation.

Changes in the water environment and its major driving factors in Poyang Lake from 2016 to 2019, China

The hydrological exchange process between Poyang Lake (PYL), the largest freshwater lake in China, and the Yangtze River leads to drastic changes in water area (WA) and water level (WL), as well as apparent fluctuations in lake nutrients, algal organisms, and trophic level index. This study investigated the current status of the PYL water environment and the influence of hydrological changes on the nutrient status of the floodplain of the lake. Based on monthly measured data from six hydrological stations from 2016 to 2019, it was hypothesized that WA and WL were the key regulators of the spatial and temporal distribution patterns of lake water quality and algal growth, including water temperature, water clarity (Secchi depth [SD]), and nutrient levels. The results revealed that (1) the spatial and temporal distribution characteristics of major nutrients in PYL were influenced by dynamic changes in hydrological characteristics (SD, total nitrogen [TN], and total phosphorus [TP]); (2) the eutrophication level in PYL has been in a steady state in recent years, while the central area has been more prone to the risk of eutrophication (e.g., the peak eutrophication index during Period 1 [January to April] in the water near the Duchang station reached 70); and (3) there were significant correlations among environmental variables, nutrients, and algal organisms, with different spatial and temporal distribution characteristics (p < 0.05), while the changes in WA and WL considerably influenced the water environment in the PYL.

Water quality forecasting based on data decomposition, fuzzy clustering and deep learning neural network

Water quality forecasting can provide useful information for public health protection and support water resources management. In order to forecast water quality more accurately, this paper proposes a novel hybrid model by combining data decomposition, fuzzy C-means clustering and bidirectional gated recurrent unit. Firstly, the original water quality data is decomposed into several subseries by empirical wavelet transform, and then, the decomposed subseries are recombined by fuzzy C-means clustering. Next, for each clustered series, bidirectional gated recurrent unit is applied to develop prediction model. Finally, the forecast result is obtained by the summation of the predictions for the subseries. The proposed forecast model is evaluated by the water quality data of Poyang Lake, China. Results show that the proposed forecast model provides highly accurate forecast result for all of the six water quality data: the average of MAPE of the forecast results for the six water quality datasets is 4.59% for 7 day ahead prediction. Furthermore, our model shows better forecast performance than the other models. Particularly, compared with the single BiGRU model, MAPE decreased by 32.86% in average. Results demonstrate that the proposed forecast model can be used effectively for water quality forecasting.

Seasonal Water Level Fluctuation and Concomitant Change of Nutrients Shift Microeukaryotic Communities in a Shallow Lake

Seasonal water level fluctuations (WLFs) impose dramatic influences on lake ecosystems. The influences of WLFs have been well studied for many lake biotas but the microeukaryotic community remains one of the least-explored features. This study employed high-throughput 18S rRNA gene sequencing to investigate the spatiotemporal patterns of microeukaryotic communities in the dry and wet seasons with concomitant change of nutrients in Poyang Lake, which experiences huge seasonal WLFs. The results showed that the dry season and wet season had distinct microeukaryotic community compositions and structures. In the dry season, Ciliophora (13.86–40.98%) and Cryptomonas (3.69–18.64%) were the dominant taxa, and the relative abundance of these taxa were significant higher in the dry season than wet season. Ochrophyta (6.88–45.67%) and Chlorophyta (6.31–22.10%) was the dominant taxa of microeukaryotic communities in the wet season. The seasonal variation of microeukaryotic communities was strongly correlated to seasonal nutrient variations. Microeukaryotic communities responded significantly to dissolved organic carbon, total nitrogen, nitrate, and soluble reactive phosphorus in the dry season, and correlated to nitrate and total phosphorus in the wet season. The microeukaryotic community showed different modular structures in two seasons, and nutrient variations were the key factors influencing seasonal variations of the modular structures. Moreover, microeukaryotic community networks based on different seasons indicated that the microeukaryotic community co-occurrence patterns were not constant but varied largely associating with the nitrogen and phosphorus variations under the effects of WLFs. Our results are important for understanding how microeukaryotic communities respond to nutrient variation under seasonal water level fluctuation.

Microbial community structure and functional properties in permanently and seasonally flooded areas in Poyang Lake

Water level fluctuations are an inherent feature regulating the ecological structures and functions of lakes. It is vital to understand the effects of water level fluctuations on bacterial communities and metabolic characteristics in freshwater lakes in a changing world. However, information on the microbial community structure and functional properties in permanently and seasonally flooded areas are lacking. Poyang Lake is a typical seasonal lake linked to the Yangtze River and is significantly affected by water level fluctuations. Bottom water was collected from 12 sampling sites: seven inundated for the whole year (inundated areas) and five drained during the dry season (emerged areas). High-throughput 16S rRNA gene sequencing was used to identify the bacterial communities. The results showed that the taxonomic structure and potential functions of the bacterial communities were significantly different between the inundated and emerged areas. Cyanobacteria was dominant in both areas, but the relative abundance of Cyanobacteria was much higher in the emerged areas than in the inundated areas. Bacterial communities were taxonomically sensitive in the inundated areas and functionally sensitive in the emerged areas. Nitrogen, phosphorus, and dissolved organic carbon concentrations and their ratios, as well as dissolved oxygen, played important roles in promoting the bacterial taxonomic and functional compositional patterns in both areas. According to the metabolic predictions based on 16S rRNA gene sequences, the relative abundance of functional genes related to assimilatory nitrate reduction in the emerged areas was higher than in the inundated areas, and the relative abundance of functional genes related to dissimilatory nitrate reduction in the inundated areas was higher. These differences might have been caused by the nitrogen differences between the permanently and seasonally flooded areas caused by intra-annual water level fluctuations. The relative abundance of functional genes associated with denitrification was not significantly different in the inundated and emerged areas. This study improved our knowledge of bacterial community structure and nitrogen metabolic processes in permanently and seasonally flooded areas caused by water level fluctuations in a seasonal lake.

Hydropower reservoirs on the upper Mekong River modify nutrient bioavailability downstream

Hydropower development is the key strategy in many developing countries for energy supply, climate-change mitigation and economic development. However, it is commonly assumed that river dams retain nutrients and therefore reduce downstream primary productivity and fishery catches, compromising food security and causing trans-boundary disputes. Contrary to expectation, here we found that a cascade of reservoirs along the upper Mekong River increased downstream bioavailability of nitrogen and phosphorus. The dams caused phytoplankton density to increase with hydraulic residence time and stratification of the stagnant reservoirs caused hypoxia at depth. This allowed the release of bioavailable phosphorus from the sediment and an increase in dissolved inorganic nitrogen as well as a shift in nitrogen species from nitrate to ammonium, which were transported downstream by the discharge of water from the base of the dam. Our findings provide a new perspective on the environmental impacts of river dams on nutrient cycling and ecosystem functioning, with potential implications for sustainable development of hydropower worldwide.

Real-time monitoring of sediment bulking through a multi-anode sediment microbial fuel cell as reliable biosensor

Sediment bulking was closely related to the occurrence of black water agglomerate in anoxic aquatic sediments. Real-time monitoring of sediment bulking can be labor intensive and technically difficult, especially in dynamic environments where a record of variation in height over time is desired. In this study, a vertically distributed multi-anodes sediment microbial fuel cell (SMFC) as biosensor was developed for monitoring the changes in sediment height. According to the principle of sediment microbial fuel cell (SMFC), the voltage of SMFC would increase when the anode embedded into the sediment. The results showed that when the anode buried in the sediment, the biosensing system delivered voltage can increase to 40 mV, where the power density of SMFC exceeded 10 mW m^-2 with overshoot of power density appeared. However, for the anodes above the water-sediment interface, the voltages and power densities kept at around 0. The redundancy analysis further indicated that the labile carbon pool-I of sediment was a key factor for sediment bulking, which led to drastic changes in sediment characteristics. The results from this study can provide a simple strategy for identifying sediment bulking in shallow lakes.

Nitrogen along the Hydrological Gradient of Marsh Sediments in a Subtropical Estuary: Pools, Processes, and Fluxes

Knowledge on the distribution of nitrogen (N) pools, processes, and fluxes along hydrological gradients provides a comprehensive perspective to understand the underlying causal mechanisms in intertidal flats, and thus improve predictions and climate adaptation strategies. We used a space-for-time substitution method to quantify N pools, processes, and fluxes along a hydrological gradient. Further, we linked N pools and processes and investigated not only surface but also subsurface sediments. Our results showed a gradual decrease in total N (TN) and mineralization rates (PN_min), but an increase in potential rates of nitrification (PNR) and denitrification (PDNR) under an elevated hydrological gradient, except for TN and PN_min in the subsurface sediment, which accumulated on the interaction zone between the high and middle tidal flats. Most sedimentary ammonium N (NH₄⁺) and nitrate N (NO₃⁻) concentrations were similar; however, NH₄⁺ accumulated on the subsurface of the middle tidal flat. NO₃⁻ fluxes (from −0.54 to −0.35 mmol m⁻² h⁻¹) were uptake fluxes in the intertidal flats, but NH₄⁺ fluxes (−2.48–3.54 mmol m⁻² h⁻¹) changed from uptake to efflux in the seaward direction. Structural equation modeling of the effects of inundation frequency, underground biomass, total carbon (TC), electrical conductivity (EC), and clay proportion on the N processes revealed that these accounted for 67%, 82%, and 17% of the variance of PDNR, PN_min, and PNR, respectively. Inundation frequency, underground biomass, TC, EC, and PN_min effects on N pools accounted for 53%, 69%, and 98% of the variance of NH₄⁺, NO₃⁻, and TN, respectively. This suggests that future sea level rise may decrease N storage due to increase in coupled nitrification–denitrification and decrease in N mineralization, and the NH₄⁺ flux may change from sink to source in intertidal ecosystems.

Seasonal variation of potential denitrification rate and enhanced denitrification performance via water-lifting aeration technology in a stratified reservoir-A case study of Zhoucun reservoir

Zhoucun reservoir is one of the major water resources in Zao Zhuang city, northern China. The seasonal distribution of surface sediment denitrification rate and enhanced performance of denitrification via water-lifting aeration technology were explored using the acetylene-inhibition technique. Surface sediment denitrification rates ranged from 2.57 ± 1.32 to 923.90 ± 86.81 nmol N₂/(g dw·h), with the highest rates in November (ANOVA, p < 0.05) and significantly low rates in June, July, and August (ANOVA, p < 0.05), mainly because of the seasonal differences in nitrate concentration, water temperature, and sediment total nitrogen (STN). Meanwhile, the N₂/(N₂+N₂O) ratio (83.44-91.70% for the highest sediment denitrification period) indicated that N₂ accounted for a majority of denitrification. Correlation analysis between various environmental factors and denitrification was conducted, and nitrate concentration, STN, low molecular weight organic carbon, the number of aerobic denitrifying bacteria, and the environmental parameters of oxidation-reduction potential (ORP), pH, electrical conductivity (EC), and chlorophyll a (Chl-a) presented significant relationships during the entire study period. On the basis of the multiple regression model, nitrate and low molecular weight organic carbon concentration were the most influential factors on denitrification variability. Moreover, the denitrification rates of the surface sediment clearly increased, from 5.28 to 13.22 nmol N₂/(g dw·h) to 1117.02-3129.47 nmol N₂/(g dw·h), which were higher than those in the non-operating year. This suggests that the denitrification in the sediment system could be enhanced in situ by water-lifting and aeration technology in the reservoir ecosystem.

Sediment denitrification in Yangtze lakes is mainly influenced by environmental conditions but not biological communities

Globally, shallow lakes have suffered from excessive nitrogen (N) loading due to increased human activities in catchments, resulting in water quality degradation and aquatic biodiversity loss. Sediment denitrification, which reduces nitrate (NO₃^-) to N gaseous products, is the most important mechanism for permanent N removal in freshwater lakes. However, the relative contribution of abiotic and biotic factors to the sediment denitrification is highly variable. Here, we determined the unamended denitrification rate and nitrous oxide (N₂O) production rate of 74 sediment samples from 22 eutrophic lakes in the Yangtze River basin. We also quantified the diversity and abundance of denitrifying communities using nirK and nirS genes. The results of variance partitioning analyses showed that water physicochemical properties (e.g., dissolved oxygen) and nutrients (e.g., NO₃^- concentration) but not denitrifier communities and submerged vegetation were the major factor groups predicting denitrification and N₂O production rates. Path analyses further revealed that water physicochemical properties and nutrients could affect denitrification and N₂O production rates both directly and indirectly, and the direct effects were considerably higher than the indirect effects mediated through changes in sediment characteristics, denitrifier communities and submerged vegetation. These findings suggest that the dominant N removal process in Yangtze lakes is largely regulated by abiotic factors rather than diversity and abundance of denitrifiers and submerged macrophytes. Additionally, the findings in this study are helpful in developing a targeted strategy to assess and enhance the N removal capability of eutrophic lakes in China.

Assessment of nitrogen losses through nitrous oxide from abattoir wastewater-irrigated soils

The land disposal of waste and wastewater is a major source of N₂O emission. This is due to the presence of high concentrations of nitrogen (N) and carbon in the waste. Abattoir wastewater contains 186 mg/L of N and 30.4 mg/L of P. The equivalent of 3 kg of abattoir wastewater-irrigated soil was sieved and taken in a 4-L plastic container. Abattoir wastewater was used for irrigating the plants at the rates of 50 and 100 % field capacity (FC). Four crop species were used with no crop serving as a control. Nitrous oxide emission was monitored using a closed chamber technique. The chamber was placed inside the plastic container, and N₂O emission was measured for 7 days after the planting. A syringe and pre-evacuated vial were used for collecting the gas samples; a fresh and clean syringe was used each time to avoid cross-contamination. The collected gas samples were injected into a gas chromatography device immediately after each sampling to analyse the concentration of N₂O from different treatments. The overall N₂O emission was compared for all the crops under two different abattoir wastewater treatment rates (50 and 100 % FC). Under 100 % FC (wastewater irrigation), among the four species grown in the abattoir wastewater-irrigated soil, Medicago sativa (23 mg/pot), Sinapis alba (21 mg/pot), Zea mays (20 mg/pot) and Helianthus annuus (20 mg/pot) showed higher N₂O emission compared to the 50 % treatments-M. sativa (17 mg/pot), S. alba (17 mg/pot), Z. mays (18 mg/pot) and H. annuus (18 mg/pot). Similarly, pots with plants have shown 15 % less emission than the pots without plants. Similar trends of N₂O emission flux were observed between the irrigation period (4-week period) for 50 % FC and 100 % FC. Under the 100 % FC loading rate treatments, the highest N₂O emission was in the following order: week 1 > week 4 > week 3 > week 2. On the other hand, under the 50 % FC loading rate treatments, the highest N₂O emission was recorded in the first few weeks and in the following order: week 1 > week 2 > week 3 > week > 4. Since N₂O is a greenhouse gas with high global warming potential, its emission from wastewater irrigation is likely to impact global climate change. Therefore, it is important to examine the effects of abattoir wastewater irrigation on soil for N₂O emission potential.