Influence of different land use types on hydrochemistry and heavy metals in surface water in the lakeshore zone of the Caohai wetland, China

Response of plants and soils to inundation duration and construction of the plant‒soil association mode in the hydro‒fluctuation belt of the reservoir wetland

Hydro-Fluctuation Belt (HFB), a periodically exposed bank area formed by changes in water level fluctuations, is critical for damaging the reservoir wetland landscape and ecological balance. Thus, it is important to explore the mechanism of hydrological conditions on the plant-soil system of the HFB for protection of the reservoir wetland and landscape restoration. Here, we investigated the response of plant community characteristics and soil environment of the HFB of Tonghui River National Wetland Park (China), is a typical reservoir wetland, to the duration of inundation, as well as the correlation between the distribution of dominant plants and soil pH, nutrient contents, and enzyme activity by linear regression and canonical correlation analyses. The results show that as the duration of inundation decreases, the vegetation within the HFB is successional from annual or biennial herbs to perennial herbs and shrubs, with dominant plant species prominent and uneven distribution of species. Soil nutrient contents and enzyme activities of HFB decreased with increasing inundation duration. Dominant species of HFB plant community are related to soil environment, with water content, pH, urease, and available potassium being principle soil environmental factors affecting their distribution. When HFB was inundated for 0-30 days, soil pH was strongly acidic, with available potassium content above 150 mg kg-1 and higher urease activity, distributed with Arundo donax L., Polygonum perfoliatum L., Alternanthera philoxeroides (Mart.) Griseb., and Daucus carota L. communities. When inundated for 30-80 days, soil pH was acidic, with lower available potassium content (50-150 mg kg-1) and urease activity, distributed with Beckmannia syzigachne (Steud.) Fern.+ Polygonum lapathifolium L., Polygonum lapathifolium L., Medicago lupulina L. + Dysphania ambrosioides L. and Leptochloa panicea (Retz.) Ohwi communities. Using the constructed HFB plant-soil correlation model, changes in the wetland soil environment can be quickly judged by the succession of plant dominant species, which provides a simpler method for the monitoring of the soil environment in the reservoir wetland, and is of great significance for the scientific management and reasonable protection of the reservoir-type wetland ecosystem.

Time series prediction of the chemical components of PM2.5 based on a deep learning model

Modeling-based prediction methods enable rapid, reagent-free air pollution detection based on inexpensive multi-source data than traditional chemical reaction-based detection methods in order to quickly understand the air pollution situation. In this study, a convolutional neural network (CNN) and long and short-term memory (LSTM) neural networks are integrated to create a CNN-LSTM time series prediction model to predict the concentration of PM2.5 and its chemical components (i.e., heavy metals, carbon component, and water-soluble ions) using meteorological data and air pollutants (PM2.5, SO2, NO2, CO, and O3). In the integrated CNN-LSTM model, the CNN uses convolutional and pooling layers to extract features from the data, whereas the powerful nonlinear mapping and learning capabilities of LSTM enable the time series prediction of air pollution. The experimental results showed that the CNN-LSTM exhibited good generalization ability in the prediction of As, Cd, Cr, Cu, Ni, and Zn, with a mean R2 above 0.9. Mean R2 predicted for PM2.5, Pb, Ti, EC, OC, SO42-, and NO3- ranged from 0.85 to 0.9. Shapley value showed that PM2.5, NO2, SO2, and CO had a greater influence on the predicted heavy metal results of the model. Regarding water-soluble ions, the predicted results were dominantly influenced by PM2.5, CO, and humidity. The prediction of the carbon fraction was affected mainly by the PM2.5 concentration. Additionally, several input variables for various components were eliminated without affecting the prediction accuracy of the model, with R2 between 0.70 and 0.84, thereby maximizing modeling efficiency and lowering operational costs. The fully trained model prediction results showed that most predicted components of PM2.5 were lower during January to March 2020 than those in 2018 and 2019. This study provides insight into improving the accuracy of modeling-based detection methods and promotes the development of integrated air pollution monitoring toward a more sustainable direction.

Dry-wet cycling area enhances soil ecosystem multifunctionality in the aquatic-terrestrial ecotones of the Caohai Lake in China

The microbial need for nutrient resources can be assessed by soil extracellular enzymes and their stoichiometry. Changes in lake water levels affect land use and nutrient management in the aquatic-terrestrial ecotones of the lakeshore. However, the drivers of changes in microbial nutrient limitation under different inundation gradients in the lake's aquatic-terrestrial ecotones remain unclear. Here, based on vector analysis, we assessed microbial nutrient limitation by studying soil enzyme activities in four different inundation zones (heavy, moderate, mild, and non-inundation) in the aquatic-terrestrial ecotones of Caohai Lake. The findings indicate that inundation conditions significantly influenced the soil properties and enzyme activities. The mean nitrogen and phosphorus acquisition enzymes were higher in both moderate inundation (Mod-inu) and mild inundation (Mil-inu) zone soils, indicating rapid N and P turnover rates in these two zones. However, microorganisms had higher carbon requirements and higher enzyme C:N and vector lengths in heavily inundated compared to lightly inundated. Compared to the non-inundation zone, the microbial phosphorus limitation was found to be most severe in heavy inundation (Hea-inu) and Mod-inu zones. Decreased phosphorus limitation following the inundation weakens could be contributed to improving soil ecosystem multifunctionality. The alterations in the soil extracellular enzymes and stoichiometric characteristics in various inundation zones were primarily influenced by factors such as soil moisture content, available phosphorus, and nitrate nitrogen. Overall, the Mod-inu and Mil-inu zones can better maintain the multifunctionality of the aquatic and terrestrial ecosystems; special attention should be given to the microbial phosphorus limitation in the Hea-inu zone in order to effectively manage nutrients and restore soil ecosystems in the aquatic-terrestrial ecotones.

Geochemical control, water quality indexing, source distribution, and potential health risk of fluoride and arsenic in groundwater: Occurrence, sources apportionment, and positive matrix factorization model

Fluoride (F-), and arsenic (As) in the groundwater cause health problems in developing countries, including Pakistan. We evaluated the occurrence, distribution, sources apportionment, and health hazards of F-, and As in the groundwater of Mardan, Pakistan. Therefore, groundwater samples (n = 130) were collected and then analyzed for F-, and As by ion-chromatography (IC) and Inductively-coupled plasma mass-spectrometry (ICP-MS). The F-, and As concentrations in groundwater were 0.7-14.4 mg/L and 0.5-11.2 µg/L. Relatively elevated F-, and As coexists with higher pH, Na+, HCO3-, SO4-2, and depleted Ca+2 due to fluoride, sulfide-bearing minerals, and anthropogenic inputs. Both F-, and/or As are transported in subsurface water through adsorption and desorption processes. Groundwater samples 45%, and 14.2% exceeded the WHO guidelines of 1.5 mg/L and 10 µg/L. Water quality indexing (WQI-model) declared that 35.7% samples are unfit for household purposes. Saturation and undersaturation of minerals showed precipitation and mineral dissolution. Groundwater contamination by PCA-MLR and PMF-model interpreted five factors. The fitting results and R2 values of PMF (0.52-0.99)>PCA-MLR (0.50-0.95) showed high accuracy of PMF-model. Human health risk assessment (HHRA-model) revealed high non-carcinogenic and carcinogenic risk for children than adults. The percentile recovery of F- and As was recorded 98%, and 95% with reproducibility ± 5% error.

Assessment and sources of heavy metals in the suspended particulate matter, sediments and water of a karst lake in Guizhou Province, China

An integrated assessment of heavy metal (HM) contamination in dissolved matter, suspended particular matter (SPM) and sediments in lakes is essential. This study assessed the risks of HMs in the water, SPM and sediment of Caohai, China, and analyzed the changes in sediment HM contamination in conjunction with historical data. The HM transport was dominated by the SPM load, and the concentrations of Zn (179.07-1821.24 mg kg^-1), Pb (53.63-181.46 mg kg^-1), and Cd (3.68-21.31 mg kg^-1) in SPM and sediment were 5.34-149.11 times higher than the upper continental crust (UCC) values. SPM and sediments were lightly to extremely polluted and had moderate to very high toxicity risks with Cd, Pb and Zn, and these three HMs originated from industrial and agricultural sources. The concentrations of Zn, Pb, and Cd in Caohai sediments increased by 36.7-187.9 % in 2022 compared to pre-2020. This research provides valuable reference data for the remediation of polluted karst lakes.

Heavy metal mapping, source identification, and ecological risk assessment in the International Hamoun wetland, Sistan region, Iran

This study is aimed at assessing the ecological risk of heavy metals (HMs) in the International Hamoun wetland, southeastern Iran. Twenty sediment samples were collected from the wetland surface for geochemical analysis of 23 HMs. The inverse distance weighting (IDW) technique was used to map the HMs. The single and multi-element pollution indicators and PER index (PERI) were respectively used to determine the contamination intensity and PER level. The principal components analysis (PCA) was performed to identify the HM source. The mean concentration of cesium (Cs: 5.2 µg/g), selenium (Se: 0.9 µg/g), and tellurium (Te: 0.2 µg/g) was higher than their mean values in the Earth's crust. The enrichment factor (EF) showed the Hamoun was high to extremely enriched by Te, As, and Se. The geo-accumulation index (GeoI) revealed the highest level of contamination caused by As, barium (Ba), cobalt (Co), chromium (Cr), cuprum (Cu), ferrum (Fe), manganese (Mn), nickel (Ni), lead (Pb), rubidium(Rb), titanium (Ti), vanadium(V), yttrium (Y), and zinc (Zn) in most study sites. The sediment contamination factor in more than 55% of the sediment samples was between 8 and 16, indicating very high contamination intensity in the studied wetland. The PER values were between 80 and 160 in more than 60% of the sediment samples, suggesting a considerable risk in the wetland. The PCA showed both anthropogenic and crustal activities were effective in increasing the concentration of HMs in the wetland. The largest ecological risk was due to arsenic (As) and cadmium (Cd). It is recommended to pay more attention to these HMs, which could cause more environmental pollution in the International Hamoun wetland, southeastern Iran.

Image-driven hydrological parameter coupled identification of flood plain wetland conservation and restoration sites

A good many works focus on wetland vulnerability; some works also explore restoration sites at a very limited spatial extent. But the satellite image-driven hydrological data-based approach adopted in this work is absolutely new. Moreover, existing work only focused on identifying restoration sites in the present context, but for devising long-term sustainable planning, predicted hydrological parameters based on possible restoration sites may be an effective tool. Considering this, the present work focused on exploring hydrological data (water presence frequency (WPF), hydro-period (HP) and water depth (WD)) from time-series satellite images. This exploration may resolve the hydrological data scarcity of wetland over the wider geographical areas. Using these parameters, we developed wetland restoration and conservation sites for different historical years (2008, 2018) and predicted years (2028) using ensemble machine learning (EML) models. From the analysis, it was found that water depth, hydro-period and WPF became poorer over the period, and the trend may seem to continue in predicted years. Among the applied EML models, Random Subspace (RS) predicted wetland restoration and conservation sites precisely over others. The predicted area under high-priority restoration sites is 34% in 2018, which was 14% in 2008. In 2028, 12% more areas may fall in this priority level. Wetland away from main streams (mainly ortho-fluvial wetland) and fringe wetland parts should be given more priority for restoration. These present and predicted information will effectively help to frame sustainable wetland restoration planning.

Abundance and characteristics of sediment-bound magnetic minerals and trace elements in karst ditch wetland: A case study from Guizhou Province, China

This study investigated sediment-bound magnetic properties and selected trace elements level in the karst ditch wetland, Caohai National Nature Reserve, Guizhou Province, China. Sediment-bound magnetic signals were quantified using low-frequency mass magnetic susceptibility (χLF), anhysteretic remanent magnetization susceptibility (χARM), saturation isothermal remanent magnetization (SIRM), and percentage frequency-dependent susceptibility (χfd%). Concentrations of Cd, Cr, Sb and Zn were determined using inductively coupled plasma mass spectrometry. Sediment χLF, χARM, SIRM, and χfd% were higher than those of bedrocks and mainly altered by the pedogenic processes. The estimated χfd% ranged from 6.15 % to 14.62 % and reflected the magnetic grain sizes were largely concentrated in the range of superparamagnetic particles. The elevated concentrations of sediment-bound Cd, Cr, Sb, and Zn supported the significant contribution of the anthropogenic sources in the karst ditch wetlands. The weak relationship between magnetic signals and selected trace elements (p < 0.05) suggested the occurrence of few sediment-bound iron-containing minerals associated with selected trace elements. These results indicated that a minor contribution of anthropogenic sources of selected trace elements to the elevated sediment magnetic signals in the karst ditch wetlands.

Natural and anthropogenic sources of potentially toxic elements to aquatic environment: a systematic literature review

Potentially toxic elements (PTEs) constitute a class of metals, semimetals, and non-metals that are of concern due to their persistence, toxicity, bioaccumulation, and biomagnification in high concentrations, posing risks to the ecosystem and to human health. A systematic literature review (SLR) was used in this study to identify natural and anthropogenic sources of PTEs for the aquatic environment. The databases consulted were ScienceDirect, Scopus, and Web of Science, in the period 2000-2020, using specific terms and filters. After analyzing the titles, abstracts, and full texts, 79 articles were selected for the SLR, in which 15 sources and 16 PTEs were identified. The main anthropogenic sources identified were mining, agriculture, industries, and domestic effluents, and the main natural sources identified were weathering of rocks and geogenic origin. Some places where environmental remediation studies can be carried out were highlighted such as Guangdong province, in China, presenting values of Cd, Cr, and Cu exceeding the national legislation from drinking water and soil quality, and Ardabil Province, in Iran, presenting values of As, Cr, Cu, Ni, Zn, and Pb exceeding the standard for freshwater sediments of USEPA, among others places. With the results exposed in this work, the government and the competent bodies of each locality will be able to develop strategies and public policies aimed at the main sources and places of contamination, in order to prevent and remedy the pollution of aquatic environments by potentially toxic elements.

Effect of Ecosystem Degradation on the Source of Particulate Organic Matter in a Karst Lake: A Case Study of the Caohai Lake, China

The cycle of biogenic elements in lakes is intimately linked with particulate organic matter (POM), which plays a critical role in ecosystem restoration and the control of eutrophication. However, little is known regarding the functionality of ecosystem degradation on the source of POM in the water of a karst lake. To fill this knowledge gap, herein we compared the temporal and spatial distribution characteristics of POM prior to and after ecosystem degradation in the karst lake Caohai Lake, located in the southwest of China, and analyzed the source of POM using a combination of carbon and nitrogen stable isotopes (δ13C–δ15N). Our results showed that the dissolved oxygen (DO) concentration and pH values decreased, and the concentrations of POM in water increased by 11% and 31% in the wet and dry seasons, respectively. The decrease in the δ13C value of POM was accompanied by the increase in the δ15N value of POM in the water of Caohai lake. Prior to the ecosystem’s degradation, sediment resuspension (28%) and submerged macrophytes (33%) were the dominant sources of POM in lake water. In contrast, sediment resuspension (51%) was the major source of POM after the ecosystem’s degradation. Environmental factors, including DO, turbidity, water depth, and water temperature, that are related to photosynthesis and sediment resuspension are the main factors controlling the spatiotemporal distribution of POM. The resuspension of sediment reduced the transparency of the water, limiting effective photosynthesis, impeding the survival of submerged macrophytes, and, consequently, deteriorating the ecosystem. We propose that the control of sediment resuspension is important for improving the water transparency that creates an appropriate habitat for the restoration of the submerged macrophyte community.

Assessment of some trace elements accumulation in Karst lake sediment and Procambarus clarkii, in Guizhou province, China

Lake wetland quality has decreased with the elevated concentrations of some trace elements. The consumption of crayfish in the trace elements concentrated lake wetland can be a hazard for the waterbirds and human health. Thus, the bioaccumulations of Cd, Ni, Pb and Zn in sediments and abdominal muscles of Procambarus clarkii in Caohai lake wetland, China were quantified. Sediment-bound Cd, Ni, Pb and Zn were remarkably elevated compared to the parent rock, while 64.71-94.12% of adverse effect index in sediment-bound Cd, Ni, Pb and Zn were > 1. Abdominal muscle-bound Cd, Pb and Zn in several samples were all above the maximum permissible limits. Pb, Zn and Ni in abdominal muscles were significantly linked with those in sediments (R² =0.60-0.89, p < 0.01) and lake sediment might be the important feed sources of P. clarkii. Target hazard quotients of Cd, Ni, Pb and Zn at the 95th percentile was all below the benchmark, normal consumption of the abdominal muscle of P. clarkii posed low or no probabilistic health risk to the Grus nigricollis and local inhabitants.

Metal pollution in the Pearl River Estuary and implications for estuary management: The influence of hydrological connectivity associated with estuarine mixing

Understanding the metal pollution can help governments and estuary management groups manage metal inputs. Here, we comprehensively analyzed the behaviors of seven metals Cd, Zn, Cu, As, Pb, Cr, and Hg in water and the responses of these metals to hydrological connectivity in the Pearl River Estuary. The analyses were based on the field measurements of August-2016 in the estuary and January-2016 in the upper river mouth. We also assessed the ecosystem health of these metals. Overall, this estuary had an overall moderate pollution level, with occasional severe perturbations. The mean concentration of individual metal was in the order of Zn > As > Cu > Cr > Pb > Cd > Hg. The eastern estuary was more heavily polluted by metals (notably, Zn, Cd, and Cu) than the western estuary; this condition was attributable to sewage and industrial effluent discharges from the eastern urban cities of Dongguan and Shenzhen. Longitudinally, high levels of Cd and Zn appeared in the upper estuary, while elevated levels of Cu, As, Pb, Cr, and Hg were found in the middle and lower estuaries. The riverine inputs and estuarine mixing significantly influenced the distribution and movement of trace metals in the estuary, and have contributed to phytoplankton productivity (chlorophyll-a > 10 μg/L). River inflow inhibited the vertical diffusion of metals, and tidal currents facilitated surface-to-bottom mixing. Cu and Cd posed ecological risks. We determined the source contributions and transport routes of the metals using principal component analysis combining with multiple linear regression. The results of this study suggest that the source apportionment of metals can help to manage the source input entering into the estuary. Further, identified hydrological connectivity of metals can inform water quality managers in the highly anthropogenically influenced estuary.

Evaluation of Soil and Irrigation Water Quality in Caohai Lakeside Zone

Due to the rapid population growth and over-application of fertilizers in the Caohai surrounding farmlands, controlling the non-point source pollution in the Caohai Lakeside Zone is significant for the local ecology balance and human health safety. A total of 54 soil and 24 irrigation water samples were collected in the Caohai Lakeside Zone to evaluate the current status of soil fertility and heavy metal pollution by measuring soil and water heavy metal content and soil physicochemical properties such as soil total nitrogen, total phosphorus, organic matter, and soil pH. These results showed that the total amounts of organic matter, nitrogen, phosphorus, potassium, and effective nutrient content in the Caohai Lakeside Zone were all at a rich level according to Chinese soil nutrient grade standard; the content of lead (Pb), chromium (Cr), cadmium (Cd), mercury (Hg), and arsenic (As) in the soil all exceeds the safety standard of Chinese classification of soil environmental quality assessment. In addition, the over-standard rates of Cd and Cr were 24.1% and 14.8%, respectively. On the whole, the comprehensive quality index (CQI) of the soil in the Caohai Lakeside Zone is 6.48, which is attributed to the heavy Cd pollution and the good soil fertility. The heavy metal content of the irrigation water met the requirements of irrigation water quality. It is feasible to use the irrigation water of Caohai Lake in the actual agricultural production process. Therefore, in terms of the comprehensive management and pollution control of Caohai, special attention should be paid to the control of Cd, Pb, As, and Hg pollution sources.

Spatial-temporal dynamics, ecological risk assessment, source identification and interactions with internal nutrients release of heavy metals in surface sediments from a large Chinese shallow lake

The surface sediment concentrations of heavy metals (Cu, Zn, Pb, Cd, Cr, Hg, and As), major metals (Fe and Mn), and the nutrient concentrations in the interstitial water of Lake Houguan, a large eutrophic shallow lake, were surveyed for three years. The results showed that Cu, Zn, and Fe were significantly higher in the east lake parts, and Cd in November was significantly higher than April. 19% of Hg and all of As were larger than the probable effect concentrations (PECs) according to the consensus-based sediment quality guidelines (SQGs), and the geo-accumulation index (I_geo) indicated As, Hg, and Cd were slightly polluted to severely polluted. The RI value (average 704.2) of the potential ecological risk index (PERI) suggested that heavy metals posed very high ecological risks with most of the contributions induced by Cd and Hg. The consequence of hierarchical clustering analysis (HCA) and principle component analysis (PCA) identified Cd, As, and Pb might originate from urbanization, industrial pollution, and agricultural activity; Hg might be from atmospheric deposition and anthropogenic sources above; Cu, Zn, Cr, Fe, and Mn might be from both natural and anthropogenic sources. The Spearman correlation analysis indicated Pb and As were significantly positively correlated with total nitrogen, while Cd significantly negatively correlated with sulfate; As was significantly correlated with ammonia, sulfate, and nitrate in the interstitial water. These results suggested eutrophication might affect sedimental heavy metals by increasing organic matter or influencing the redox potentials in the sediment.

Rapid diagnosis of heavy metal pollution in lake sediments based on environmental magnetism and machine learning

Environmental magnetism in combination with machine learning can be used to monitor heavy metal pollution in sediments. Magnetic parameters and heavy metal concentrations of sediments from Chaohu Lake (China) were analyzed. The magnetic measurements, high- and low-temperature curves, and hysteresis loops showed the primary magnetic minerals were ferrimagnetic minerals in sediments. For most metals, their concentrations were highest during the wet season and lowest during the medium-water period. Cd, Hg, and Zn were moderately enriched and Cd and Hg posed a considerable ecological risk. A redundancy analysis indicated a relationship between physicochemical indexes and magnetic parameters and heavy metal concentrations. An artificial neural network (ANN) and support vector machine (SVM) were used to construct six models to predict the heavy metal concentrations and ecological risk index. The inclusion of both the physicochemical indexes and magnetic parameters as input factors in the models were significantly ameliorated the simulation accuracy for the majority of heavy metals. The training and test R, for Be, Fe, Pb, Zn, As, Cu, and Cr were > 0.8. The SVM showed better performance and hence it has potential for the efficient and economical long-term tracking and monitoring of heavy metal pollution in lake sediments.

Microplastics removal efficiency of drinking water treatment plant with pulse clarifier

Microplastics are recognized as ubiquitous pollutants in aquatic environments; however, very little study is done on their occurrence and fate at drinking water treatment plants (DWTPs). Though, the toxic effect of microplastics on human health is not yet well established; there is global concern about their possible ill effect on the human. Hence, the present study evaluates the occurrence of microplastics at different treatment stages of a typical DWTP with pulse clarification and its removal efficiency. In the test DWTP, raw water, sourced from river Ganga, was found to contain microplastics 17.88 items/L. Cumulative microplastic removal at key treatment stages viz. pulse clarification and sand filtration was found to be 63% and 85%, respectively. The study also revealed higher microplastic abundance on the sand filter bed due to the screening effect. The most frequently occurring microplastics were fibers and films/fragments with polyethylene terephthalate and polyethylene as a major chemical type. The t-distributed stochastic neighbor embedding machine learning algorithm revealed a strong association between microplastic abundance with turbidity, phosphate and nitrate. The test DWTP with a pulse clarification system was having comparable microplastics removal efficiency with previously reported advanced DWTPs.

Phosphorus sorption - Desorption behaviors in the sediments cultured with Hydrilla verticillata and Scripus triqueter as revealed by phosphorus fraction and dissolved organic matter

The migration of sediment phosphorus (P) could be affected by the existence of aquatic plants. To explore the effects of aquatic plants on the P sorption-desorption behaviors in the sediments, sediment in Caohai wetland was collected and cultured with the submerged plant (Hydrilla verticillata) and emerged plant (Scripus triqueter). Then the sorption and desorption experiments were performed, and physicochemical properties, P fractions, and dissolved organic matter (DOM) characteristics were evaluated. Results showed that the treated sediments exhibited similar P sorption kinetic process fitted well with the two-compartment first-order model. Nevertheless, H. verticillata cultured sediment could be well described by the modified Langmuir isotherm model, while S. triqueter cultured sediment fitted the modified Freundlich equations well. The obvious changing P fractions in cultured sediments were BD-P and NaOH-SRP during sorption. H. verticillata and S. triqueter displayed different sorption-desorption behaviors by altering BD-P, humification index, fluorescence intensity, and PARAFAC component contents in sediments. Compared to raw sediment, H. verticillata presented higher P sorption and lower P release from sediments by decreasing BD-P and increasing DOM (fulvic acid-like and humic-like components) content, while S. triqueter showed adverse P sorption and release effects by reducing DOM components. The growth of submerged plants was suggested to make a positive influence on the high efficiency of P retention capacity and low release risk.

The response of microbial community structure and sediment properties to anthropogenic activities in Caohai wetland sediments

This study aimed to investigate the response of sediment microbial communities (including bacteria and archaeal groups) in Caohai Lake to anthropogenic activities. The sediment samples were collected from the regions with high anthropogenic interference and low anthropogenic interference. Their physicochemical properties and enzyme activities were analyzed, and the bacterial and archaeal communities were investigated using high-throughput sequencing technology. The results showed that the physicochemical characters changed by anthropogenic activities were the important factors that influenced enzyme activities, alpha diversity, key functional taxa, and community structure. And the impact of anthropogenic activities on microbial communities might follow a non-linear pattern. Furthermore, few significant differences of alpha indices between the high and low disturbed areas, but clear differences of microbial community composition analysis and beta-diversity analysis were observed. The hypothesis was proved that the intensity of anthropogenic impacts in Caohai had not reached the potential thresholds. The best distinguish biomarkers between the two areas and the most related key nodes among the network did not always have a high microbial abundance. The anthropogenic activities might influence the microbial community by affecting a small number of the key taxon in the ecological network. These findings provided a valuable understanding of how sediment microorganisms respond to anthropogenic activities in Caohai Lake.