Nitrogen removal enhanced by benthic bioturbation coupled with biofilm formation: A new strategy to alleviate freshwater eutrophication

Effects of benthic bioturbation on anammox in nitrogen removal at the sediment-water interface in eutrophic surface waters

Anaerobic ammonium oxidation (anammox) significantly contributes to nitrogen loss in freshwater ecosystems. The sediment-water interface (SWI), known as a "hot spot" for anammox, also harbors numerous macroinvertebrates. However, the impact of their bioturbation on anammox has generally been overlooked. This study compared the effects of three representative macroinvertebrates (i.e., Propsilocerus akamusi, Branchiura sowerbyi and Radix swinhoei) with different bioturbation modes on anammox and the N-removal processes at the SWI by using a microcosmic system. The results demonstrated that all three benthic macroinvertebrates promoted anammox in addition to denitrification processes. The highest N-removal was achieved in the presence of P. akamusi considered as a gallery-diffuser, where the relative abundance of Planctomycetes (to which the anammox bacteria belong) increased by 70%. P. akamusi increased the abundance of anammox hzsB gene by 2.58-fold and promoted potential anammox rate by 12.79 nmol N g-1 h-1, which in turn facilitated total N-removal mass increased by 2.42-fold. In the presence of B. sowerbyi and R. swinhoei, the potential anammox rates increased by 4.81 and 5.57 nmol N g-1 h-1, respectively. These results underscore the substantial impact of macroinvertebrates on anammox and N-removal processes, highlighting their crucial role in N pollution control, and sustaining the overall health and stability of eutrophic water bodies.

Biofilter-constructed wetland-trophic pond system: A new strategy for effective sewage treatment and agricultural irrigation in rural area

Artificial ecosystems with high biological complexity are generally considered to be efficient in metabolizing substances and resistant to temperature shock. In this study, a novel near-natural system (BCT system), which consisted of simple biofilter, constructed wetland and trophic biology pond, was conducted to treat rural sewage in situ for irrigation into farmland. Water quality related to carbon and nutrients and microbial community were analyzed along the system to reveal the effect of each unit. The annual average removals of BCT system for TN, NH₄⁺-N, TP and COD could reach 46.53%, 52.18%, 41.48%, and 53.21%, respectively. There was no significant decrease for removal efficiencies from high temperature period (HTP, ≥15 °C) to low temperature period (LTP, <15 °C). In LTP, the trophic pond (TRP) removed 34.85% of TN, 33.93% of NH₄⁺-N, 13.71% of TP and 18.77% of COD, while the removal efficiencies of constructed wetland fluctuated greatly. The TRP facilitated the BCT system to maintain the removal capability during low temperature period. The relative abundance of denitrification functional genes in TRP increased nearly tenfold from HTP to LTP. The effluent quality from the system can meet the agricultural irrigation standards, demonstrating the effect of BCT system on sewage treatment and agricultural irrigation in rural area.

Strategies for Restoring and Managing Ecological Corridors of Freshwater Ecosystem

Along with accelerating urbanization and associated anthropogenic disturbance, the structure and function of freshwater ecosystems worldwide are substantially damaged. To improve ecosystem health, and thus enhance the ecosystem security of the urban ecosystem, numbers of management approaches and engineering projects have been applied to mitigate the degradation of freshwaters. Nevertheless, there is still a lack of comprehensive and systematic research on the ecological corridor restoration of freshwater ecosystems; especially for Suzhou Grand Canal, one section of the world's longest and ancient Grand Canal which is inclined to severe ecosystem degradation. Through investigating the adjacent land use characteristics, habitat quality, vegetation cover, instream water quality, and habitat composition, we aimed to: (i) assess the water quality of the Suzhou Grand Canal; (ii) evaluate the ecological characteristics of the canal ecosystem; (iii) develop strategic countermeasures to restore the ecological corridors for the mitigation of ecological problems. The results demonstrated: a large built area, a smaller ecological zone, a low habitat quality and habitat connectivity, and a high degree of habitat fragmentation within the canal corridor, also a simplified instream habitat composition, and greater nutrient and COD concentrations in the surface water-especially in the upstream and midstream canal. All urbanization-induced multiple stressors, such as land use changes, altered hydrology, and the simplified riparian zone et al., contributed synergistically to the degradation of the canal ecosystem. To alleviate the ecosystem deterioration, three aspects of recommendations were proposed: water pollution control, watershed ecosystem restoration, and ecological network construction. Basically, building a comprehensive watershed ecological network-on the basis of associated ecosystem restoration, and the connection of multi-dimensional ecological corridors-would dramatically increase the maintenance of aquatic-terrestrial system biodiversity, and improve the regional ecological security pattern and watershed resilience toward stochastic future disturbances. This study contributes to the understanding of the ecological challenges and related causes of the canal ecosystem. The integrated strategy introduced in this study provides policymakers, water resource managers, and planners with comprehensive guidelines to restore and manage the ecological corridor of the canal ecosystem. This can be used as a reference in freshwater ecosystems elsewhere, to improve ecosystem stability for supporting the sustainable development of urban ecosystems.

A review on nirS-type and nirK-type denitrifiers via a scientometric approach coupled with case studies

The denitrification process plays an important role in improving water quality and is a source/sink of nitrous oxide to the atmosphere. The second important rate-limiting step of the denitrification process is catalyzed by two enzymes with different structures and unrelated evolutionary relationships, namely, the Cu-type nitrite reductase encoded by the nirK gene and the cytochrome cd1-type nitrite reductase encoded by the nirS gene. Although some relevant reviews have been published on denitrifiers, most of these reviews do not include statistical analysis, and do not compare the nirS and nirK communities in-depth. However, a systematic study of the nirS-type and nirK-type denitrifying communities and their response to environmental factors in different ecosystems is needed. In this review, a scientometric approach combined with case studies was used to study the nirS-type and nirK-type denitrifiers. The scientometric approach demonstrated that Pseudomonas, Paracoccus, and Thauera are the most frequently mentioned nirS-type denitrifiers, while Pseudomonas and Bradyrhizobium are the top two most frequently mentioned nirK-type denitrifiers. Among various environmental factors, the concentrations of nitrite, nitrate and carbon sources were widely reported factors that can influence the abundance and structure of nirS-type and nirK-type denitrifying communities. Case studies indicated that Bradyrhizobium was the major genus detected by high-throughput sequencing in both nirS and nirK-type denitrifiers in soil systems. nirS-type denitrifiers are more sensitive to the soil type, soil moisture, pH, and rhizosphere effect than nirK. To clarify the relationships between denitrifying communities and environmental factors, the DNA stable isotope probe combined with metagenomic sequencing is needed for new denitrifier detections.

Antibiotic resistome in a large urban-lake drinking water source in middle China: Dissemination mechanisms and risk assessment

The increasing pollution of urban drinking water sources by antibiotic resistance genes (ARGs) threatens human health worldwide. However, the distribution and influencing factors of ARGs, especially how to reveal the risks of ARGs in this environment remains unclear. Hence, Chaohu Lake was selected as an example to investigate the characteristics of ARGs and explore the interactions among physicochemical factors, microorganisms, and ARGs by metagenomic approach. In this work, 75 ARG subtypes with an average of 30.4 × /Gb (ranging from 15.2 ×/Gb to 57.9 ×/Gb) were identified, and multidrug and bacA were most frequent in Chaohu Lake. Non-random co-occurrence patterns and potential host bacteria of ARGs were revealed through co-occurrence networks. Microbial community and mobile genetic elements (MGEs) were the major direct factors in ARG profiles. The dissemination of ARGs was mainly driven by plasmids. Considering the interactions among MGEs, human bacterial pathogens, and ARGs, antibiotic resistome risk index (ARRI) was proposed to manifest the risks of ARGs. Overall, our work systemically investigated the composition and associated factors of ARGs and built ARRI to estimate the potential risks of ARGs in a typical urban drinking water source, providing an intuitive indicator for managing similar lakes.

Inland Reservoir Water Quality Inversion and Eutrophication Evaluation Using BP Neural Network and Remote Sensing Imagery: A Case Study of Dashahe Reservoir

In this study, an inland reservoir water quality parameters’ inversion model was developed using a back propagation (BP) neural network to conduct reservoir eutrophication evaluation, according to multi-temporal remote sensing images and field observations. The inversion model based on the BP neural network (the BP inversion model) was applied to a large inland reservoir in Jiangmen city, South China, according to the field observations of five water quality parameters, namely, Chlorophyl-a (Chl-a), Secchi Depth (SD), total phosphorus (TP), total nitrogen (TN), and Permanganate of Chemical Oxygen Demand (CODMn), and twelve periods of Landsat8 satellite remote sensing images. The reservoir eutrophication was evaluated. The accuracy of the BP inversion model for each water parameter was compared with that of the linear inversion model, and the BP inversion models of two parameters (i.e., Chl-a and CODMn) with larger fluctuation range were superior to the two multiple linear inversion models due to the ability of improving the generalization of the BP neural network. The Dashahe Reservoir was basically in the state of mesotrophication and light eutrophication. The area of light eutrophication accounted for larger proportions in spring and autumn, and the reservoir inflow was the main source of nutrient salts.