Occurrence of organophosphorus flame retardants in Xiangjiang River: Spatiotemporal variations, potential affecting factors, and source apportionment

The environmental occurrence of organophosphorus flame retardants (OPFRs) is receiving increasing attention. However, their distribution in the Xiangjiang River, an important tributary in the middle reaches of the Yangtze River, is still uncharacterized, and the potential factors influencing their distribution have not been adequately surveyed. In this study, the occurrence of OPFRs in the Xiangjiang River was comprehensively investigated from upstream to downstream seasonally. Fourteen OPFRs were detected in the sampling area, with a total concentration (∑OPFRs) ranging from 3.16 to 462 ng/L, among which tris(1-chloro-2-propyl) phosphate was identified as the primary pollutant (ND - 379 ng/L). Specifically, ∑OPFRs were significantly lower in the wet season than in the dry season, which may be due to the dilution effect of river flow and enhanced volatilization caused by higher water temperatures. Additionally, Changsha (during the dry season) and Zhuzhou (during the wet season) exhibited higher pollution levels than other cities. According to the Redundancy analysis, water quality parameters accounted for 35.7% of the variation in the occurrence of OPFRs, in which temperature, ammonia nitrogen content, dissolved oxygen, and chemical oxygen demand were identified as the potential influencing factors, accounting for 28.1%, 27.2%, 24.1%, and 11.5% of the total variation, respectively. The results of the Positive Matrix Factorization analysis revealed that transport and industrial emissions were the major sources of OPFRs in Xiangjiang River. In addition, there were no high-ecological risk cases for any individual OPFRs, although tris(2-ethylhexyl) phosphate and tributoxyethyl phosphate presented a low-to-medium risk level. And the results of mixture risk quotients indicated that medium-risk sites were concentrated in the Chang-Zhu-Tan region. This study enriches the global data of OPFRs pollution and contributes to the scientific management and control of pollution.

Leveraging machine learning for prediction of antibiotic resistance genes post thermal hydrolysis-anaerobic digestion in dairy waste

Anaerobic digestion holds promise as a method for removing antibiotic resistance genes (ARGs) from dairy waste. However, accurately predicting the efficiency of ARG removal remains a challenge. This study introduces a novel appproach utilizing machine learning to forecast changes in ARG abundances following thermal hydrolysis-anaerobic digestion (TH-AD) treatment. Through network analysis and redundancy analyses, key determinants of affect ARG fluctuations were identified, facilitating the development of machine learning models capable of accurately predicting ARG changes during TH-AD processes. The decision tree model demonstrated impressive predictive power, achieving an impessive R2 value of 87% against validation data. Feature analysis revealed that the genes intI2 and intI1 had a critical impact on the absolute abundance of ARGs. The predictive model developed in this study offers valuable insights for improving operational and managerial practices in dairy waste treatment facilities, with the ultimate goal of mitigating the spread of antibiotic resistance.

Effects of climate and geochemical properties on the chemical forms of soil Cd, Pb and Cr along a more than 4000 km transect

Soil heavy metal speciation has received much attention for their different ecological and environmental effects. However, the effects of climate and soil geochemical properties on them in uncontaminated soils at macroscale were still unclear. Therefore, a transect more than 4000 km was chosen to study the effects of these factors on soil Cd, Pb and Cr forms. The results revealed that mean annual temperature and precipitation showed significant positive relations with the exchangeable and Fe-Mn oxide bound states of Cd, Pb and Cr, and residual Cr. And humidity and drought indexes were significantly positively correlated with their organic and carbonate bound forms, respectively. As for soil geochemical properties, pH displayed significant negative relationships with exchangeable, Fe-Mn oxide and organic bound Pb and Cr, and exchangeable Cd. Fe2O3 was significantly positively with the exchangeable and Fe-Mn oxide bound Cd, Pb and Cr, and residual Cr. And soil organic matter showed positive relations with organic bound Pb and Cr, and residual Cd and Cr, displayed negative relationships with carbonated bound Pb and Cr. Overall, climate and soil geochemical properties together affect the transformation and transport of heavy metals between different forms in uncontaminated soils.

The dynamic changes in phytoplankton and environmental factors within Dongping Lake (China) before and after the South-to-North Water Diversion Project

Dongping Lake is one of the most important regulation and storage lakes along the eastern route of the South-to-North Water Diversion Project in China, the water quality condition of which directly influences the safety of water diverting, because it serves as a Yangtze River water redistribution control point. However, the changes in algae, and in environmental factors affecting their community structures, before and after the water diversion project are rarely reported. In this study, the temporal variations of phytoplankton abundance were examined based on monthly samples collected at three stations from May 2010 to April 2022. The total abundance of algae greatly decreased after the water diversion project was implemented, with a relatively stable biodiversity and evenness before and after the water translocation. Multiple statistical methods were used together with the water quality indices (WQIs) and the nutrient status index (TSIM) to evaluate overall water condition and analyse relationships among environmental factors. The WQIs demonstrated a general "Good" water quality with a seasonal differentiation, and that water conditions during water transfer periods were better than during non-water transfer periods, which may be ascribed to the improved hydraulic conditions and purified water environment during water transfer periods. Redundancy analysis showed that water temperature, ammonia nitrogen, water transparency, and total phosphorus were the most important environmental factors, with relatively decreased contribution rates towards phytoplankton communities after the water translocation. Importantly, some dominant phytoplankton genera of Chlorophyta, Bacillariophyceae, and Cyanophyceae were similarly affected by water transparency, and nitrogen and phosphorus nutrients in summer after the water translocation. These research findings helped us gain a comprehensive understanding of the changing patterns of water quality and microalgae and their relationships before and after the water diversion project, providing a guidance for future lake management in regulating hydraulic conditions and improving water quality of Dongping Lake.

Major influencing factors identification and probabilistic health risk assessment of soil potentially toxic elements pollution in coal and metal mines across China: A systematic review

Deposition of potentially toxic elements (PTEs) in soils due to different types of mining activities has been an increasingly important concern worldwide. Quantitative differences of soil PTEs contamination and related health risk among typical mines remain unclear. Herein, data from 110 coal mines and 168 metal mines across China were analyzed based on 265 published literatures to evaluate pollution characteristics, spatial distribution, and probabilistic health risks of soil PTEs. The results showed that PTE levels in soil from both mine types significantly exceeded background values. The geoaccumulation index (Igeo) revealed metal-mine soil pollution levels exceeded those of coal mines, with average Igeo values for Cd, Hg, As, Pb, Cu, and Zn being 3.02-15.60 times higher. Spearman correlation and redundancy analysis identified natural and anthropogenic factors affecting soil PTE contamination in both mine types. Mining activities posed a significant carcinogenic risk, with metal-mine soils showing a total carcinogenic risk an order of magnitude higher than in coal-mine soils. This study provides policymakers a quantitative foundation for developing differentiated strategies for sustainable remediation and risk-based management of PTEs in typical mining soils.

Landscape genomics reveals regions associated with adaptive phenotypic and genetic variation in Ethiopian indigenous chickens

Climate change is a threat to sustainable livestock production and livelihoods in the tropics. It has adverse impacts on feed and water availability, disease prevalence, production, environmental temperature, and biodiversity. Unravelling the drivers of local adaptation and understanding the underlying genetic variation in random mating indigenous livestock populations informs the design of genetic improvement programmes that aim to increase productivity and resilience. In the present study, we combined environmental, genomic, and phenotypic information of Ethiopian indigenous chickens to investigate their environmental adaptability. Through a hybrid sampling strategy, we captured wide biological and ecological variabilities across the country. Our environmental dataset comprised mean values of 34 climatic, vegetation and soil variables collected over a thirty-year period for 260 geolocations. Our biological dataset included whole genome sequences and quantitative measurements (on eight traits) from 513 individuals, representing 26 chicken populations spread along 4 elevational gradients (6-7 populations per gradient). We performed signatures of selection analyses ([Formula: see text] and XP-EHH) to detect footprints of natural selection, and redundancy analyses (RDA) to determine genotype-environment and genotype-phenotype-associations. RDA identified 1909 outlier SNPs linked with six environmental predictors, which have the highest contributions as ecological drivers of adaptive phenotypic variation. The same method detected 2430 outlier SNPs that are associated with five traits. A large overlap has been observed between signatures of selection identified by[Formula: see text]and XP-EHH showing that both methods target similar selective sweep regions. Average genetic differences measured by [Formula: see text] are low between gradients, but XP-EHH signals are the strongest between agroecologies. Genes in the calcium signalling pathway, those associated with the hypoxia-inducible factor (HIF) transcription factors, and sports performance (GALNTL6) are under selection in high-altitude populations. Our study underscores the relevance of landscape genomics as a powerful interdisciplinary approach to dissect adaptive phenotypic and genetic variation in random mating indigenous livestock populations.

Comparison of the arsenic protective effects of four nanomaterials on pakchoi in an alkaline soil

Accurately applying engineered nanoparticles (NPs) in farmland stress management is important for sustainable agriculture and food safety. We investigated the protective effects of four engineered NPs (SiO2, CeO2, ZnO, and S) on pakchoi under arsenic (As) stress using pot experiments. The results showed that CeO2, SiO2, and S NPs resulted in biomass reduction, while ZnO NPs (100 and 500 mg kg-1) significantly increased shoot height. Although 500 mg kg-1 S NPs rapidly dissolved to release SO42-, reducing soil pH and pore water As content and further reducing shoot As content by 21.6 %, the growth phenotype was inferior to that obtained with 100 mg kg-1 ZnO NPs, probably due to acid damage. The addition of 100 mg kg-1 ZnO NPs not only significantly reduced the total As content in pakchoi by 23.9 % compared to the As-alone treatment but also enhanced plant antioxidative activity by increasing superoxide dismutase (SOD) and peroxidase (POD) activities and decreasing malondialdehyde (MDA) content. ZnO NPs in soil might inhibit As uptake by roots by increasing the dissolved organic carbon (DOC) by 19.12 %. According to the DLVO theory, ZnO NPs were the most effective in preventing As in pore water from entering plant roots due to their smaller hydrated particle size. Redundancy analysis (RDA) further confirmed that DOC and SO42- were the primary factors controlling plant As uptake under the ZnO NP and S NP treatments, respectively. These findings provide an important basis for the safer and more sustainable application of NP-conjugated agrochemicals.

Spatial distribution pattern and health risk of groundwater contamination by cadmium, manganese, lead and nitrate in groundwater of an arid area

Combining the results of base models to create a meta-model is one of the ensemble approaches known as stacking. In this study, stacking of five base learners, including eXtreme gradient boosting, random forest, feed-forward neural networks, generalized linear models with Lasso or Elastic Net regularization, and support vector machines, was used to study the spatial variation of Mn, Cd, Pb, and nitrate in Qom-Kahak Aquifers, Iran. The stacking strategy proved to be an effective substitute predictor for existing machine learning approaches due to its high accuracy and stability when compared to individual learners. Contrarily, there was not any best-performing base model for all of the involved parameters. For instance, in the case of cadmium, random forest produced the best results, with adjusted R2 and RMSE of 0.108 and 0.014, as opposed to 0.337 and 0.013 obtained by the stacking method. The Mn and Cd showed a tight link with phosphate by the redundancy analysis (RDA). This demonstrates the effect of phosphate fertilizers on agricultural operations. In order to analyze the causes of groundwater pollution, spatial methodologies can be used with multivariate analytic techniques, such as RDA, to help uncover hidden sources of contamination that would otherwise go undetected. Lead has a larger health risk than nitrate, according to the probabilistic health risk assessment, which found that 34.4% and 6.3% of the simulated values for children and adults, respectively, were higher than HQ = 1. Furthermore, cadmium exposure risk affected 84% of children and 47% of adults in the research area.

Effect of heterogeneous fenton-like pretreatment on semi-permeable membrane-covered co-composting: Humification and microbial community succession

This study focused on the impacts of heterogeneous Fenton-like pretreatment on the humification and bacterial community during co-composting of wheat straw with cattle dung covered with a semi-permeable membrane. In this study, FeOCl and low concentration of H2O2 were used for pretreatment and composting, which lasted for 39 days. The results showed that the pretreatment promoted the humification process, with degree of polymerization and percentage of humic acid increasing by 53.2 % and 7.3 %, respectively. Furthermore, the diversity and structure of bacterial communities were altered by pretreatment. During the thermophilic phase, pretreatment considerably promoted the metabolism of carbohydrate. According to redundancy analysis, C/N, moisture and organic matter were the key environmental factors that dominated the microbial community. In summary, heterogeneous Fenton-like pretreatment provided a novel idea for improving the humic acid content and maturity of the compost pile.

Parallels of quantum superposition in ecological models: from counterintuitive patterns to eco-evolutionary interpretations of cryptic species

BACKGROUND

Superposition, i.e. the ability of a particle (electron, photon) to occur in different states or positions simultaneously, is a hallmark in the subatomic world of quantum mechanics. Although counterintuitive at first sight, the quantum world has potential to inform macro-systems of people and nature. Using time series and spatial analysis of bird, phytoplankton and benthic invertebrate communities, this paper shows that superposition can occur analogously in redundancy analysis (RDA) frequently used by ecologists.

RESULTS

We show that within individual ecosystems single species can be associated simultaneously with different orthogonal axes in RDA models, which suggests that they operate in more than one niche spaces. We discuss this counterintuitive result in relation to the statistical and mathematical features of RDA and the recognized limitations with current traditional species concepts based on vegetative morphology.

CONCLUSION

We suggest that such "quantum weirdness" in the models is reconcilable with classical ecosystems logic when the focus of research shifts from morphological species to cryptic species that consist of genetically and ecologically differentiated subpopulations. We support our argument with theoretical discussions of eco-evolutionary interpretations that should become testable once suitable data are available.

Evaluation of impact of land use and landscape metrics on surface water quality in the northeastern part along Lake Tanganyika, Africa

As the second deepest lake in Africa, Lake Tanganyika plays an important role in supplying fish protein for the catchment's residents and is irreplaceable in global biodiversity. However, the lake's water environment is threatened by socioeconomic development and rapid population growth along the lake. This study analyzed the spatial scale effects and seasonal dependence of land use types and landscape metrics on water quality in 16 sub-basins along northeastern Lake Tanganyika at different levels of urbanization. The results revealed that land use types had a higher influence on water quality in urban areas than that in rural areas; the explanatory variance in the urban area was 0.78-0.96, while it was 0.21-0.70 in the rural area. The explanatory ability of land use types on water quality was better at the buffer scale than at the sub-watershed scale, and the 500 m buffer scale had the highest explanatory ability in the urban area and rural area both in the rainy season and dry season, and artificial surface and arable land were the main contributing factors. And this phenomenon was more obvious in dry season than in rainy season. We identified that CONTAG was the key landscape metric in urban area and was positively correlated with nutrient variables, indicating that water quality degraded in less fragmented landscapes. The sub-watershed scale had the highest explained ability, while in rural area, the 1500 m buffer scale had the highest explained ability and IJI had the highest explanatory variance, which had a negative effect on water quality. Research on the relationship between land use and water quality would help assess the water quality in the unmonitored watershed as monitoring is expensive and time-consuming in low-income area. This knowledge would provide guideline to watershed managers and policymakers to prioritize the future land use development within Lake Tanganyika basin.

Integrating ecosystem services closely related to human well-being into the restoration and management of deep lakes facing multiple stressors: Lessons from long-term practice in Qiandao Lake, China

Deep-lake (reservoir) ecosystems provide valuable ecosystem services (ES) and generate significant ecosystem service values (ESV); however, reservoir ecosystems have suffered great losses from environmental changes and human activities. Currently, studies on ES and its correlations with stressors remain insufficient and the integration of ES into ecological restoration and management poses numerous challenges. Here, we combined four types of stressors with six ES closely related to human well-being to discuss their interactions in Qiandao Lake (a representative deep lake in China). Our results indicate that all ESV showed a consistent growth trend throughout the study period, reaching 5203.8 million CNY in 2018, and the cultural service value surpassed the provisioning service value for the first time in 2004. Almost all the ESV were limited during the cyanobacterial bloom in Qiandao Lake. Redundancy analysis and partial least squares structural equation modeling jointly revealed that socioeconomic development was the most important direct driver of the increase in ESV (0.770) and that hydro-meteorological conditions (0.316) and pollutant loads (0.274) positively affected ESV by mediating lake trophic status. The trophic status of the lake is the result of the interaction of multiple stressors, which has a negative impact on ESV. Therefore, to continuously protect the provisioning and cultural service values of deep-lake ecosystems from damage, the government must rationally formulate SED goals and reduce pollutant loads during lake development, operation, and utilization. This work provides valuable insights into the interactions between ES, which are closely related to human well-being, and stressors in deep-lake ecosystems.

Waste seaweed compost and rhizosphere bacteria Pseudomonas koreensis promote tomato seedlings growth by benefiting properties, enzyme activities and rhizosphere bacterial community in coastal saline soil of Yellow River Delta, China

This study investigated the effects of waste seaweed compost and rhizosphere bacteria Pseudomonas koreensis HCH2-3 on the tomato seedlings growth in coastal saline soils and chemical properties, enzyme activities, microbial communities of rhizosphere soil. Microcosmic experiment showed that the seaweed compost and rhizosphere bacteria (SC + HCH2-3) significantly alleviated the negative effects of salinity on the growth of tomato seedlings. SC + HCH2-3 amendment significantly increased the plant height and root fresh biomass of tomato seedling by 105.59% and 55.60% in the coastal saline soils, respectively. The soil properties and enzyme activities were also dramatically increased, indicating that the nutrient status of coastal saline soil was improved by SC + HCH2-3 amendment. In addition, Proteobacteria, Actinobacteriota and Firmicutes were the dominant phyla in the rhizosphere soil after adding seaweed compost and rhizosphere bacteria P. koreensis HCH2-3. The relative abundances of Massilia, Azospira, Pseudomonas and Bacillus increased in treatment SC + HCH2-3. Especially, the beneficial bacteria genera, such as Pseudomonas, Bacillus and Azospira, were significantly correlated with the increases of contents of total nitrogen, nitrate nitrogen and ammonium nitrogen in tomato rhizosphere soil samples. Consequently, adding waste seaweed compost and rhizosphere bacteria P. koreensis HCH2-3 into coastal saline soil was suggested as an effective method to relieve salt stress of tomato plants.

Multi-spatial-scale land/use land cover influences on seasonally dominant water quality along Middle Ganga Basin

Studying spatiotemporal water quality characteristics and their correlation with land use/land cover (LULC) patterns is essential for discerning the origins of various pollution sources and for informing strategic land use planning, which, in turn, requires a comprehensive analysis of spatiotemporal water quality data to comprehend how surface water quality evolves across different time and space dimensions. In this study, we compared catchment, riparian, and reach scale models to assess the effect of LULC on WQ. Using various multivariate techniques, a 14-year dataset of 20 WQ variables from 20 monitoring stations (67,200 observations) is studied along the Middle Ganga Basin (MGB). Based on the similarity and dissimilarity of WQPs, the K-means clustering algorithm classified the 20 monitoring stations into four clusters. Seasonally, the three PCs chosen explained 75.69% and 75% of the variance in the data. With PCs > 0.70, the variables EC, pH, Temp, TDS, NO2 + NO3, P-Tot, BOD, COD, and DO have been identified as dominant pollution sources. The applied RDA analysis revealed that LULC has a moderate to strong contribution to WQPs during the wet season but not during the dry season. Furthermore, dense vegetation is critical for keeping water clean, whereas agriculture, barren land, and built-up area degrade WQ. Besides that, the findings suggest that the relationship between WQPs and LULC differs at different scales. The stacked ensemble regression (SER) model is applied to understand the model's predictive power across different clusters and scales. Overall, the results indicate that the riparian scale is more predictive than the watershed and reach scales.

Genomic signals of local adaptation in Picea crassifolia

BACKGROUND

Global climate change poses a grave threat to biodiversity and underscores the importance of identifying the genes and corresponding environmental factors involved in the adaptation of tree species for the purposes of conservation and forestry. This holds particularly true for spruce species, given their pivotal role as key constituents of the montane, boreal, and sub-alpine forests in the Northern Hemisphere.

RESULTS

Here, we used transcriptomes, species occurrence records, and environmental data to investigate the spatial genetic distribution of and the climate-associated genetic variation in Picea crassifolia. Our comprehensive analysis employing ADMIXTURE, principal component analysis (PCA) and phylogenetic methodologies showed that the species has a complex population structure with obvious differentiation among populations in different regions. Concurrently, our investigations into isolation by distance (IBD), isolation by environment (IBE), and niche differentiation among populations collectively suggests that local adaptations are driven by environmental heterogeneity. By integrating population genomics and environmental data using redundancy analysis (RDA), we identified a set of climate-associated single-nucleotide polymorphisms (SNPs) and showed that environmental isolation had a more significant impact than geographic isolation in promoting genetic differentiation. We also found that the candidate genes associated with altitude, temperature seasonality (Bio4) and precipitation in the wettest month (Bio13) may be useful for forest tree breeding.

CONCLUSIONS

Our findings deepen our understanding of how species respond to climate change and highlight the importance of integrating genomic and environmental data in untangling local adaptations.

Eisenia fetida impact on cadmium availability and distribution in specific components of the earthworm drilosphere

Although the potential of vermiremediation for restoring metal-contaminated soils is promising, the effects of earthworms on the availability of soil metals are still debatable. Most previous studies considered the soil as a "whole black box." Mobilization or immobilization of metals are affected by earthworm activities within drilosphere hotspots under different soil conditions, which has not been specifically studied. Therefore, an improved 2D terrarium was designed to study the impact of earthworm activities on cadmium (Cd) fate in the drilosphere hotspots (burrow wall soils, burrow casts, and surface casts) of different artificially spiked Cd treatments (CK: 0 mg kg-1; LM: 1 mg kg-1; and HM: 5 mg kg-1) with different organic amendments (2% and 10%). The results revealed that Cd increased earthworm activities with the highest cast production in HM and the highest burrow length in LM. Earthworms exhibited a stronger tendency to reduce total Cd concentration by 4.48-13.58% in casts of LM soils, while 3.37-5.22% in burrow walls under HM treatments. Overall, earthworms could increase the availability of Cd in casts under all conditions (55.46-121.01%). The organic amendments decreased the total Cd concentration and increased the availability of Cd in the disturbed soil. A higher amount of organic amendment significantly decreased total Cd concentration of the drilosphere by 1.16-5.83% in LM and HM treatments, while increasing DTPA-Cd concentrations in all components by 23.13-55.20 %, 14.63-35.11%, and 3.30-11.41% in CK, LM, and HM treatments, respectively, except for earthworm non-disturbed soil and no-earthworm soil in HM treatments. Redundancy analysis (RDA) revealed that the moisture, pH, and total carbon contents in soil are the main factors affecting Cd bioavailability. In this study, we decoded the "black box" of soil by making it relatively simple to better understand the effects and mechanisms of earthworm activities on soil metal availability and consequently provided comprehensive insights for using earthworms in soil vermiremediation.

Evaluation of algal species distributions and prediction of cyanophyte cell counts using statistical techniques

Safe drinking water sources are crucial for human health. Consequently, water quality management, including continuous monitoring of water quality and algae at sources, is critical to ensure the availability of safe water for local residents. This study aimed to construct statistical prediction models considering probability distributions relevant to cyanophyte cell counts and compare their prediction performance. In this study, water quality parameters at Juam Lake and Tamjin Lake, representative water sources in the Yeongsan and Seomjin rivers, South Korea, were investigated. We used a water quality monitoring network, algae alert system, and hydraulic and hydrological data measured every 7 days from January 2017 to December 2022 from the Water Environment Information System of the National Institute of Environmental Research. Using data for 2017-2021 as a training set and data for 2022 as a test set, the performances of seven models were compared for predicting cyanophyte cell counts. Environmental factors associated with algae in water sources were observed based on the monitoring data, and a prediction model appropriate for the cyanophyte distribution was generated, which also included the risk of toxicity. The extreme gradient boosting with the random forest model had the best predictive performance for cyanophyte cell counts. The study results are expected to facilitate water quality management in various water systems, including water sources.

Statistical Inference in Redundancy Analysis: A Direct Covariance Structure Modeling Approach

Redundancy analysis (RA) is a multivariate method that maximizes the mean variance of a set of criterion variables explained by a small number of redundancy variates (i.e., linear combinations of a set of predictor variables). However, two challenges exist in RA. First, inferential information for the RA estimates might not be readily available. Second, the existing methods addressing the dimensionality problem in RA are limited for various reasons. To aid the applications of RA, we propose a direct covariance structure modeling approach to RA. The proposed approach (1) provides inferential information for the RA estimates, and (2) allows the researcher to use a simple yet practical criterion to address the dimensionality problem in RA. We illustrate our approach with an artificial example, validate some standard error estimates by simulations, and demonstrate our new criterion in a real example. Finally, we conclude with future research topics.

Key factors influencing pollution of heavy metals and phenolic compounds in mangrove sediments, South China

Concentrations of heavy metals (HMs) and phenolic compounds with factors which potentially affected their spatial distribution were investigated in mangrove sediments, South China. Compared to Qi'ao, Futian sediments exhibited higher levels of Pb and nonylphenol (NP), but lower levels of Co and Ni. Seasonal variation showed higher concentrations of Pb, Cr, Co, NP and bisphenol A (BPA), while lower concentration of methylparaben (MP) in wet than dry season. Contaminant levels in sediments collected at different tidal heights showed insignificant variations, except for Zn and NP. MP was found negatively correlated with nearly all HMs and BPA, whereas the latter exhibited positive correlations with each other. Sedimentary total carbon, total nitrogen, C/N and N/P ratios were screened as the most influential factors affecting the distribution of these contaminants. Additionally, both salinity and total phosphate exhibited positive, while both pH and sedimentary particle size registered negative correlation, with one or more contaminants.

The effects of water quality parameters, water level changes, and mixing on zooplankton community dynamics in a tropical high-mountain Lake Ardibo, Ethiopia

The diversity and abundance of the zooplankton community are affected by changes in physico-chemical parameters, trophic interactions, water level changes, and periodic mixing. In this study, the influence of environmental variables, water level changes, and periodic mixing on zooplankton distribution and abundance was seasonally studied for Lake Ardibo from October 2020 to September 2021 collected from 3 sites. Results on the physico-chemical variables indicated that all variables, except turbidity, varied significantly (p < 0.05) in all sampling seasons. A total of 33 zooplankton species were recorded, comprising 18 rotifers, 11 cladocerans, and 4 cyclopoid copepods. Zooplankton abundance significantly varied seasonally with peak abundance (4232.13 ind. L-1) recorded in the dry season and lowest numbers (402.42 ind. L-1) during the long rainy period. Redundancy analysis (RDA) results indicated that total phosphorus, ammonia, water temperature, silicon dioxide, and conductivity were the most significant driving forces for the seasonal successions in the abundance and distribution of zooplankton communities. Cyclopoid copepod abundance was significantly (p < 0.05) higher in the dry season, which could be correlated with the partial mixing (atelomixis) phenomenon that occurred during the dry period.

Response of nitrite accumulation to elevated C/NO- 3-N ratio during partial denitrification process: Insights of extracellular polymeric substance, microbial community and metabolic function

This study investigated the response of nitrite accumulation to elevated COD/NO₃^--N ratio (C/N) during partial denitrification (PD). Results indicated nitrite was gradually accumulated and remained stable (C/N = 1.5 ∼ 3.0), while that rapidly declined after reaching the peak (C/N = 4.0 ∼ 5.0). The polysaccharide (PS) and protein (PN) content of tightly-bound extracellular polymeric substances (TB-EPS) reached the maximum at C/N of 2.5 ∼ 3.0, which might be stimulated by high level of nitrite. Illumina MiSeq sequencing showed Thauera and OLB8 were dominated denitrifying genera at C/N of 1.5 ∼ 3.0, while Thauera was further enriched with fading OLB8 at C/N of 4.0 ∼ 5.0. Meanwhile, the highly-enriched Thauera might enhance the activity of nitrite reductase (nirK) promoting further nitrite reduction. Redundancy analysis (RDA) showed positive correlations between nitrite production and PN content of TB-EPS, denitrifying bacteria (Thauera and OLB8) and nitrate reductases (narG/H/I) in low C/N. Finally, their synergistic effects for driving nitrite accumulation were comprehensively elucidated.

Use of multivariate analysis to identify phytoplankton bioindicators of stream water quality in the monomodal equatorial agroecological zone of Cameroon

The aquatic ecosystem is compromised by many contaminants that may reduce ecosystem functions and severely affect human health. This study aimed at determining suitable phytoplankton bioindicators of water quality for biomonitoring of freshwater streams in the monomodal agroecological zone of Cameroon. Water physicochemical and hydrological parameters, together with phytoplankton abundance and diversity, were measured from June 2016 to May 2017 along the Benoe Stream. Principal component analysis and redundancy analysis were used to determine phytoplankton spatial and temporal distribution and identify indicator species. The Shannon-Wiener diversity and Pielou's evenness indices indicated a clean to mildly polluted stream with a diverse phytoplankton community consisting of 84 genera belonging to 51 families that was dominated by the Bacillariophyta (64%), followed by Chlorophyta (13%) and Cyanophyta (10%). The total dissolved solids, electrical conductivity, stream water velocity, and discharge were the most important stream characteristics affecting the abundance of the dominant phytoplankton genera. Seasonal variations in the stream characteristics as well as spatial community distribution along an urban-small-scale farming - large-scale farming gradient were unveiled and their influence on the phytoplankton relative abundances. Increased abundance of Synedra ulna was indicative of low TDS and EC, which was the contrary for Gyrosigma baltium dominance. High Pleurosira laevis abundance was associated with the urban zone while high Diatoma sp. and Oscillatoria sp. abundances were related to the large-scale farming zone of the stream. These phytoplankton species have good potential for use as bioindicators for stream water quality monitoring in the monomodal agroecological zone.

Chiral pesticides levels in peri-urban area near Yangtze River and their correlations with water quality and microbial communities

Pesticides are considered to be the second-largest non-point source pollution in water. Our research assayed the river network of typical agricultural areas in the middle and lower Yangtze River as the study area. Pesticides residues in aquatic environment were determined by QuEChERS, combined with high-performance liquid chromatography tandem mass spectrometry, or gas chromatograph-mass spectrometer. At chiral pesticides' levels, we detected pesticides contents in water, classified and counted the types of pesticides, and analyzed their environmental risk assessment. Furthermore, potential correlations between chiral pesticides concentrations and water quality indicators were assayed. Additionally, we explored their relations with microbial communities at species levels. Enantiomers of Diclofop-methyl, Ethiprole, Difenoconazole and Epoxiconazole were enantioselectively distributed. More interestingly, due to various chiral environment of the sampling site, the enantiomers of Tebuconazole Acetochlor, Glufosinate ammonium and Bifenthrin had completely different distributions at different sites. Based on that, the chiral pesticides Diclofop-methyl, Bifenthrin, Ethiprole, Tebuconazole and Difenoconazole are enantioselective to the risk of aquatic environment. Generally, enantiomeric selectivity had high positive correlations with total nitrogen and phosphorus. Then we found that chiral fate behavior of Tebuconazole and Paichongding in water might be affected by prokaryotes. In addition, the chiral behavior of Diclofop-methyl, Propiconazole, Difenoconazole, and Tebuconazole isomers in water might be negatively affected by eukaryotes. That research helped us to comprehensively understand the impact of non-point source pollution of chiral pesticides in aquatic environment and provided basic data support for developing biological and water quality indicators for monitoring pollution in aquatic environment.

Evaluating the relationship between groundwater quality and land use in an urbanized watershed

Understanding the impact of urbanization on groundwater quality is critical. Effective water management requires understanding the relationship between land use and water quality. The study's goals were to compare the effects of land use, identify the types of land that impact hydrochemistry, and define how different land use affects water quality. For this purpose, the comparative relationship between groundwater quality, land use classes and landscape metrics were established for the years 2016 and 2021. Water samples were collected from 42 wells, and different hydro-chemical variables were considered to calculate the water quality index (WQI). The WQI value in 2016 ranged from 26.49 to 151.03 and 29.65 to 155.62 in 2021. The results indicate that the water quality in most parts of the study area is moderate for drinking and domestic purpose use. The google earth engine platform was used and radiometrically corrected and orthorectified Sentinel-2 satellite images were processed to classify land use classes for selected years. Five buffer zones were established within a 2-km watershed along each well site, and the effects of land use types and landscape metrics on water quality in the buffer zones were analyzed. Results revealed that the effects of land use types on water quality were mainly reflected in buffer 1 (B1), buffer 4 (B4), buffer 5 (B5) in 2016 and B1, buffer 3 (B3), and B5 in 2021. The impacts of landscape-level metrics on water quality are mainly reflected in buffer 2 (B2) and B3 in 2021, while at the class-level, they are mainly reflected in B1 and B4 in 2021. The redundancy analysis revealed that different hydro-chemical variables behaved differently with the land use classes and landscape metrics in the various buffer zones.

New insights into pollution source analysis using receptor models in the upper Yangtze river basin: Effects of land use on source identification and apportionment

To effectively control pollution and improve water quality, it is essential to accurately analyze the potential pollution sources in rivers. The study proposes a hypothesis that land use can influence the identification and apportionment of pollution sources and tested it in two areas with different types of water pollution and land use. The redundancy analysis (RDA) results showed that the response mechanisms of water quality to land use differed among regions. In both regions, the results indicated that the water quality response relationship to land use provided important objective evidence for pollution source identification, and the RDA tool optimized the procedure of source analysis for receptor models. Positive matrix decomposition (PMF) and absolute principal component score-multiple linear regression (APCS-MLR) receptor models identified five and four pollution sources along with their corresponding characteristic parameters. PMF attributed agricultural nonpoint sources (23.8%) and domestic wastewater (32.7%) as the major sources in regions 1 and 2, respectively, while APCS-MLR identified mixed sources in both regions. In terms of model performance parameters, PMF demonstrated better-fit coefficients (R²) than APCS-MLR and had a lower error rate and proportion of unidentified sources. The results show that considering the effect of land use in the source analysis can overcome the subjectivity of the receptor model and improve the accuracy of pollution source identification and apportionment. The results of the study can help managers clarify the priorities of pollution prevention and control, and provide a new methodology for water environment management in similar watersheds.

Leaf litter chemistry and its effects on soil microorganisms in different ages of Zanthoxylum planispinum var. Dintanensis

BACKGROUND

Leaf litter is the products of metabolism during the growth and development of plantation, and it is also an important component of nutrient cycling in plantation ecosystems. However, leaf litter chemistry and its effects on soil microorganisms in different ages, as well as the interactions between chemical components in leaf litter have been rarely reported. Based on this, this paper took Zanthoxylum planispinum var. dintanensis (hereafter Z. planispinum) plantations of 5-7, 10-12, 20-22, and 28-32 years old as the objects. By using one-way ANOVA, Pearson correlation analysis and redundancy analysis, we investigated leaf litter chemistry and its effects on soil microorganisms in different ages, and to reveal internal correlation of various chemical components in leaf litter, which can provide a scientific basis for the regulation of soil microbial activity in plantations.

RESULTS

The variation of organic carbon with plantation age was more stable compared to total nitrogen and phosphorus of leaf litter. Nitrogen resorption was stronger than phosphorus resorption efficiency in Z. planispinum, and resorption efficiencies of leaf nitrogen and phosphorus for different ages were lower than the global average. Total nitrogen was highly significantly positively correlated with lignin, and total potassium was significantly positively correlated with tannin, suggesting the increase of inorganic substances in leaf litter would promote the accumulation of secondary metabolites. The leaf litter chemical traits explained up to 72% of soil microorganisms, where lignin was positively correlated with fungi and negatively correlated with bacteria, indicating that fungi are able to decompose lower quality litter and can break down complex and stable organic compounds more rapidly than bacteria. The nutrient elements carbon and nitrogen in the leaf litter and their interrelationship also have a great impact on soil microorganisms, because carbon is not only the element that provides energy, but also the element with the largest content in the microbiota.

CONCLUSIONS

The sustained increase in inorganic nutrients of leaf litter did not favor the decomposition of secondary metabolites, but rather inhibited the degradation of leaf litter. The significant positive effect of the leaf litter chemistry on soil microorganisms indicates the important role of leaf litter in promoting nutrient cycling in Z. planispinum plantations.

Fluorescein diacetate hydrolytic activity as a sensitive tool to quantify nitrogen/sulfur gene content in urban river sediments in China

The relative abundance of functional genes used to quantify the abundance of functional genes in communities is controversial. Quantitative PCR (qPCR) technology offers a powerful tool for quantifying functional gene abundance. However, humic substances can inhibit qPCR in sediment/soil samples. Therefore, finding a convenient and effective quantitative analysis method for sediment/soil samples is necessary. The functional genes and physicochemical properties in sediments with different-level pollutions were analyzed in this study. Correlations between physicochemical properties and the relative abundance of functional genes were used to test whether relative abundance in gene prediction quantifies the abundance of functional genes. The abundance of functional genes could be corrected by multiplying the fluorescein diacetate (FDA) hydrolytic rates by the relative abundance of functional genes since the FDA assay has been widely used as a rapid and sensitive method for quantifying microbial activity in sediments. Redundancy analysis showed significant interrelations between the functional genes and the physicochemical properties of sediments. The relative abundance of functional genes is unreliable for quantifying the abundance of functional genes because of the weak correlation (R < 0.5, P < 0.05) between different pollutants and the relative abundance of functional genes. However, a significant positive correlation between concentrations of different pollutants and the activities of associated enzymes was obtained (R > 0.933, P < 0.05), which revealed that the abundance of functional genes could be reliably quantified by the relative abundance and FDA hydrolytic rate. This study proposed an alternative method besides qPCR to quantify the absolute abundance of functional genes, which overcomes the problem of humic interference in the quantitative analysis of sediment/soil samples.

Spatial effects of the agricultural ecosystem services based on environmental kuznets curve in Mengyin county, China

Worldwide most agroecosystems effort to increase production and yields and leads to damages of a series of non-provisioning ecosystem services (ESs). To fill in the knowledge gaps pertaining to the understanding of complex relationship between agricultural harvests and other ESs, therefore this study aims to estimate the existence of Environmental Kuznets Curve (EKC) for agricultural ESs by incorporating the spatial factors. Based on the test of the spatial autocorrelation of agricultural ESs, the estimation results of spatial model are compared with general regression to explain the spatial effect of agricultural ESs. The results show that (1) contrary to expectation, the curve of the nonlinear relationship between agricultural ESs and annual household income is an inverted U-shape, and not an upright U-shape; (2) compared to non-spatial model, the turning point of the inverted U-shaped curve for agricultural ESs under the direct effect would happen earlier and happen later under the indirect effect; (3) years of formal education, vegetation coverage of field margin and cultivated land area have significantly impact on local agricultural ESs, and local perennial crops has significantly impact on agricultural ESs of neighboring villages. Results of this study have a promising application prospect to promote sustainable development of agriculture.

Fate of selenium in a Se-enriched region of North China: Translocation, bioaccumulation, source, and health benefits

There are limited studies on the translocation and bioaccumulation of selenium (Se) in weak alkaline cultivated Se-enriched soil, and the sources and speciation of Se in wheat grains remain unclear. In this study, we measured the Se levels in soils, roots, stems, and wheat grains from Se-enriched cultivated land in Ci County, China, which has a high incidence of esophageal cancer. The Se levels in the roots were higher than those in the soils, indicating that wheat plants bioaccumulated high concentrations of Se from the soil (enrichment coefficient [EC] range from the soil to the root: 0.94-3.29). Redundancy analysis indicated that the bioaccumulated factor, translocation coefficient, and EC were mainly controlled by phosphorus, pH, and Fe₂O₃ (contribution rates: 37.5%, 19.5%, and 15.9%, respectively). Linear regression analysis revealed that the sources of Se in grains were mainly from the water-soluble fraction (R² = 0.55, at p < 0.05), the weakly acidic fraction (R² = 0.84, at p < 0.05), the reducible fraction (R² = 0.84, at p < 0.05), and the oxidizable fraction (R² = 0.70, at p < 0.05), as well as from atmospheric deposition (R² = 0.37, at p < 0.01). There is a significant correlation between the Se from atmospheric deposition and the oxidizable fraction (R² = 0.62, at p < 0.01) and the residual fraction (R² = 0.33, at p < 0.01). The contribution of Se input flux from atmospheric deposition was 5.50 g/hm² for one year. Furthermore, the average content of organic Se in wheat grains was 58.93%. The Se concentrations found in wheat grains were considered beneficial for human health based on a comparison with the Chinese Society of Nutrition standard and worldwide levels. The results of this study will increase the overall knowledge on the theme, which could help prevent and control the harmful effects of undesirable concentrations of Se on human health.

Co-composting of cattle manure and wheat straw covered with a semipermeable membrane: organic matter humification and bacterial community succession

Semipermeable membrane-covered composting is one of the most commonly used composting technologies in northeast China, but its humification process is not yet well understood. This study employed a semipermeable membrane-covered composting system to detect the organic matter humification and bacterial community evolution patterns over the course of agricultural waste composting. Variations in physicochemical properties, humus composition, and bacterial communities were studied. The results suggested that membrane covering improved humic acid (HA) content and degree of polymerization (DP) by 9.28% and 21.57%, respectively. Bacterial analysis indicated that membrane covering reduced bacterial richness and increased bacterial diversity. Membrane covering mainly affected the bacterial community structure during thermophilic period of composting. RDA analysis revealed that membrane covering may affect the bacterial community by altering the physicochemical properties such as moisture content. Correlation analysis showed that membrane covering activated the dominant genera Saccharomonospora and Planktosalinus to participate in the formation of HS and HA in composting, thus promoting HS formation and its structural complexity. Membrane covering significantly reduced microbial metabolism during the cooling phase of composting.

Effects of natural non-volcanic CO2 leakage on soil microbial community composition and diversity

Geological carbon capture and storage (CCS) can reduce anthropogenic CO₂ emissions, but questions exist about impacts at the surface if CO₂ leaks from deep storage reservoirs. To examine potential impacts on soils, previous studies have investigated the geochemistry and microbiology of volcanic soils hosting high fluxes of CO₂ rich gas. This study builds on those previous investigations by considering impacts of CO₂ leakage at a non-volcanic site, where deep geogenic CO₂ leaks from a cracked well casing. At the site, we collected 26 soil cores adjacent to soil gas monitoring wells. Based on measured CO₂ fluxes, the soil samples fall into two groups 1) high CO₂ (flux = 304.6 ± 272.1 g m^-2 d^-1, conc. = 29.1 ± 34 %) and 2) low CO₂ (flux = 15.8 ± 6.1 g m^-2 d^-1, conc. = 0.8 ± 0.9 %). Soil pH was significantly lower (p < 0.05) in high flux group samples (4.6 ± 0.3) than the low flux ones (5.3 ± 0.7). Beta diversity calculations using 16S rRNA gene sequences and redundancy analysis (RDA) revealed clear clustering of microbial communities relative to CO₂ flux and significant correlations of community composition with pH and organic carbon content. In the high flux soils, abundant microbial groups included Acidobacteriota, Ktedonobacteria, and SC-I-84 in the phylum Proteobacteria, as well as Nitrososphaeria, a genus of ammonia oxidizing archaea. Compared to volcanic sites described previously, our non-volcanic site had slight differences in soil geochemical properties and gradual shifts in community compositions between CO₂ hotspots and background locations. Moreover, the elevated abundance of SC-I-84 has not been reported in studies of volcanic sites. This study improves our ability to predict potential environmental impacts of geological CCS by expanding the range of conditions over which existing CO₂ leakage has been observed.

Influences of landscape pattern on water quality at multiple scales in an agricultural basin of western China

Determining the associations between landscape pattern and river water quality and quantifying the abrupt change points of landscape metrics are vital to optimize landscape planning and improve basin water quality. This study took an agricultural basin in western China as a case study. River water quality of 61 sub-basin outlets were monitored during wet and dry seasons from 2020 to 2021. Landscape metrics were extracted at 100 m, 300 m, 500 m riparian buffer and sub-basin scales, respectively. Relationships between water quality and landscape pattern at multiple scales were explored by using redundancy analysis (RDA). Results showed that urban-related landscape metrics served as the primary contributor to degrade water quality during both seasons, followed by cropland-related metrics, which might be attributed to the increase of urban land and reduction of agricultural chemical fertilizer use. Landscape metrics could better explain the water quality variations during wet season than dry season. The explanatory abilities of landscape metrics to overall water quality appeared little difference among spatial scales during wet season, whereas landscape metrics within 100 m riparian buffer had much larger explanatory rate than other spatial scales during dry season. Results of abrupt change point analysis revealed that the abrupt change interval values (ACIVs) of percentage of urban land (PLAND_urban) and the largest patch index of urban land (LPI_urban) differed among COD, TN, and TP. The recommended threshold values of PLAND_urban and LPI_urban for COD, TN, and TP management were smaller than 11.0%, 2.5%, and 1.0%, respectively. When the PLAND_urban or LPI_urban exceeded 19.0%, the TN, TP, and COD pollution would all significantly accelerate. Therefore, a limit value of 19% of PLAND_urban and LPI_urban, respectively is put forward. From dry season to wet season, the ACIVs of PLAND_urban and LPI_urban for COD concentration increased, whereas they decreased for TN and TP concentrations. Our results can provide scientific insights into sustainable landscape planning and effective water quality protection in agricultural basins.

Effect of Phanerochaete chrysosporium inoculation on manganese passivation and microbial community succession during electrical manganese residue composting

Electrolytic manganese residue poses potentially threats to the environment and therefore needs eco-friendly treatment. Composting has been reported to effectively passivate heavy metals and alleviate their ecotoxicity. Observation of the Mn concentration during composting indicated that the mobility of Mn was significantly reduced, with the easily extraction fraction (acid extractable and easily reduction fraction) of Mn in the control pile (pile 1 without Phanerochaete chrysosporium inoculation) and treat pile (pile 2 with Phanerochaete chrysosporium inoculation) decreasing by 17% and 29%, respectively. The inoculation of Phanerochaete chrysosporium prompted the passivation of manganese, prolonged the thermophilic period, and enriched the microbial community structure, which was attributed to the rapid growth and reproduction of thermophilic bacteria. Moreover, Phanerochaete chrysosporium inoculation promoted the effect of pH on the stabilization of Mn, but the opposite contribution of organic matter. This study would provide a new perspective for remediating EMR contaminated soil via composting.

First report on per- and polyfluoroalkyl substances (PFASs) in coral communities from the Northern South China sea: Occurrence, seasonal variation, and interspecies differences

In this study, the contamination levels and seasonal variation of 22 PFASs were investigated in coastal reef-building corals (n = 68) from the northern South China Sea (SCS) during wet and dry seasons. Perfluorohexane sulfonate (PFHxS) was the predominant PFASs in all coral samples, representing 43% of the total PFAS. Long-chain PFASs, as well as PFAS alternatives, were frequently detected above the MQL (>88%) but showed relatively low concentrations compared to short-chain PFASs in most species and seasons. Seasonal variation of PFAS concentrations were observed in branching corals, indicating that the accumulation of PFASs may be associated with coral morphological structures. Interspecies differences in PFAS levels agree well with different bioaccumulation potentials among coral species. Redundancy analysis (RDA) showed that seasonal factor and coral genus could partly influence PFAS concentrations in coral tissues. In summary, our study firstly reported the occurrence of PFASs in coral communities from the SCS and highlights the necessity for future investigations on more toxicity data for coral communities.

Effects of multi-scale landscape pattern changes on seasonal water quality: a case study of the Tumen River Basin in China

Landscape patterns affect river water quality by influencing hydrological processes. However, with changes in spatial scale and season, landscape factors may have different effects on water pollution. Therefore, quantitative analysis of the scale effect of each landscape index was carried out to determine the mutation point of river water quality and its index relationship, which is of great significance to landscape planning and water quality protection. Based on the water quality monitoring data of 19 sampling points in the Tumen River Basin, we used redundant methods to quantify the spatial scale effects and seasonal dependencies of various landscape indicators on river water quality, then determined the mutation point of the water quality along the landscape-scale gradient. The results showed that different types of landscape indicators have different effects on river water quality, and the spatial-scale effect of landscape composition affects a river's water quality, while landscape configuration indicators had the highest sensitivity. The landscape characteristics of river straps better explained the overall water quality, a phenomenon that is more obvious in the wet season than the dry season. We identified a key landscape indicator of urban area proportion (Urban%) and a contagion index (CONTAG) as the river strap scale. An Urban% < 30% and a CONTAG > 70% suggest effective landscape planning parameters that effectively protect water quality. The results indicated that, to protect water quality, landscape regulation should follow scale-adaptability measures and consider landscape thresholds, which cause abrupt changes in water quality.

The profiles of chiral pesticides in peri-urban areas near Yangtze River: Enantioselective distribution characteristics and correlations with surface sediments

Chiral pesticides account for 30% of pesticides. Pesticides are inevitably leached into the groundwater by runoff. At the watershed level, the distribution characteristics of enantiomers in sediments collected from the river network of an agricultural area near the middle and lower reaches of the Yangtze River were tested, and their potential correlations with the physicochemical properties and microbial communities of the sediments were analyzed. The sediment pollution was serious at sites 8 and 9, with their pollution source possibly being agricultural or industrial sewage. Moreover, there were higher cumulative contents of pesticide residues at sites 4, 8, and 9. Specifically, Cycloxaprid was the most detected chiral pesticide in the study area, followed by Dinotefuran and Diclofop-methyl. Additionally, Ethiprole and Difenoconazole had strong enantioselectivity in the study area. Interestingly, the enantiomers of some chiral pesticides, such as Tebuconazole, had completely different distributions at different sites. Pearson correlation analysis showed that sediment catalase and microbial biomass carbon were important factors for enantioselectivity of chiral pesticides. The effect of sediment physicochemical properties on enantioselective distribution was achieved by influencing the microorganisms in the sediment. Furthermore, the enantioselective distribution of Tebuconazole was closely related to the genus Arenimonas. Overall, the enantioselective distribution of most of the chiral pesticides was positively correlated with the prokaryotic microbial community. This study provides empirical support for agricultural non-point source pollution caused by chiral pesticides, and also lays a research foundation for exploring the factors that affect the fate of chiral pesticides in the environment.

Driving effects and transfer prediction of heavy metal(loid)s in contaminated courtyard gardens using redundancy analysis and multilayer perceptron

The distribution and migration of heavy metal(loid)s in the soil-vegetable systems of courtyard gardens near mining areas have rarely been investigated, leading to potential food safety risks for residents. Moreover, the existing research is mainly focused on the total content of heavy metal(loid)s (tMetals) rather than the bioavailable contents (aMetals). In this study, 26 and 28 pairs of soil and vegetable samples were collected from the courtyard gardens near the Realgar mine in Baiyun Town and the lead-zinc (Pb-Zn) mine in Shuikoushan Town, respectively. The tMetal and aMetal of cadmium (Cd), mercury (Hg), arsenic (As), Pb, chromium (Cr), nickel (Ni), copper (Cu), Zn, manganese (Mn), iron (Fe), and calcium (Ca) in the samples were analyzed in this study. The results showed that courtyard gardens were polluted by various heavy metal(loid)s at varying degrees. The bioavailabilities of different metals varied significantly, among which Cd has the highest bioavailability (> 30%). In the transfer process of heavy metal(loid)s, the transfer rate (Tf) was ranked as soil-roots (1.50) > stems-leaves (1.07) > roots-stems (0.46) > stems-fruits (0.33). Redundancy analysis was used to evaluate the driving effects, and the results revealed that aCa, aZn, and aFe in soil could inhibit the absorption of aCd by plant roots. Soil organic matter was the inhibiting factor regarding the transfer of aAs and aCu, whereas it was also the promoting factor for transferring aPb, aNi, and aCr. Furthermore, the multilayer perceptron (MLP) could effectively predict the Tf of heavy metal(loid)s based on the aMetal. The R² values of the MLP were ranked as follows: 0.91 for As, 0.88 for Zn, 0.85 for Hg, 0.83 for Cu, 0.79 for Cr, 0.66 for Cd, 0.65 for Pb, and 0.52 for Ni. This study emphasizes the aMetal-based ecological characteristics and prediction ability. The study results are significant for guiding residents to strategize appropriate crop planting and ensure the safe production and consumption of vegetables.

Occurrences, transport drivers, and risk assessments of antibiotics in typical oasis surface and groundwater

Intensive use of antibiotics affects biogeochemical cycles and stimulates the evolution of antibiotic resistance, thus threatening global health and social development. The spatiotemporal distributions of antibiotics in single aqueous matrices have been widely documented; however, their occurrence in surface-groundwater systems has received less attention, especially in arid regions that usually have fragile ecosystems. Therefore, we investigated the occurrence of thirty-one antibiotics in the surface water and adjacent groundwater in the Xinjiang Uygur Autonomous Region, China. The results showed that the total concentrations of detected antibiotics varied from 17.37 to 84.09 ng L^-1 and from 16.38 to 277.41 ng L^-1 in surface and groundwater, respectively. The median concentration of antibiotics showed the pattern of norfloxacin (4.86 ng L^-1) > ciprofloxacin (3.93 ng L^-1) > pefloxacin (3.39 ng L^-1) in surface water; whereas in groundwater, this was in the order of pefloxacin (6.30 ng L^-1) > norfloxacin (4.33 ng L^-1) > ciprofloxacin (2.68 ng L^-1). Heatmap analysis indicated that vertical infiltration had limited effects on antibiotic exchange in surface-ground water systems because of the high potential evaporation and low water storage. Redundancy analysis suggested that the oxidation-reduction potential (p < 0.01) and dissolved oxygen (p < 0.05) jointly affected the distribution of antibiotics in surface water. Ecological risk assessment showed that antibiotics in 98.9% of surface water and 99.1% of groundwater did not pose significant risks to aquatic species. The findings of this study will help develop effective mitigation strategies for antibiotics in aquatic environments.

Macroecological drivers of vascular plant species composition in semi-natural grasslands: A regional study from Lower Silesia (Poland)

In agricultural landscapes of Europe, species-rich semi-natural grasslands provide numerous ecosystem services, such as forage production, ground and surface water regulation, and carbon sequestration. In the face of the declining area of grasslands, information about the macroecological drivers of grasslands diversity is an important element of studies on their ecology and management. Here, we tested the effect of factors representing environmental gradients, landscape structure, human pressure, habitat continuity in time, and spatial structure on species composition of vascular plants in semi-natural grasslands. The analysis was performed using a multivariate approach for 689 vegetation plots distributed across ~20,000 km² in the Lower Silesia region (Poland, Central Europe). We found that species composition was significantly influenced by factors representing all studied groups. The most influential factors were temperature, long-term habitat continuity, and topography. Moreover, we captured the correlation between habitat conditions and habitat continuity. Old grasslands (existing since the 1940s) usually occurred in wet habitats, and medium grasslands (existing since the 1980s) existed in highlands in most cases. We highlighted the potential of freely available environmental databases, as well as historical topographic maps, in the exploration of patterns of species composition at a large spatial extent. The result show also the usefulness of vegetation databases in recognition of grassland complexes contributing the regional biodiversity.

Understanding the relationship between globalization and biophysical resource consumption within safe operating limits for major Belt and Road Initiative countries

Over the past few years, a growing number of scholars have explored environmental deterioration and its connection to various indicators acting as proxies for growth and globalisation. Taking this into view, the current study examines the globalisation-environment nexus, using 66 major countries and administrative regions of the Belt and Road Initiative (BRI) as case studies for 2000-2015. For this analysis, six biophysical resource usages were used within the safe operating space of the planetary boundary concept as proxies for the environmental state, along with the four main and five sub-indices of the Konjunkturforschungsstelle (KOF) globalisation index. Pearson's correlation, hierarchical clustering, redundancy analysis, linear regression, autoregressive integrated moving average (ARIMA) forecasting, etc. were used to infer existing trends, the interactions between the environment and globalisation, a projected future, and coupling with safe operating space aspects. The findings reveal the long-run asymmetric relationship of variables. Surpassing safe operating limits to achieve globalisation is the most prominent outcome. Economic, trade, and financial globalisation are more crucially related to biophysical resource usage. Nitrogen use and material footprint act as strong drivers for various indices of globalisation. At least 40% of countries are above the global average resource usage and 50% have crossed all of the safe operating limits. At the present rate, nearly 51% of countries might cross all their safe operating spaces in 2030. In a race to achieve more globalisation (0.95), more than 30% of countries might cross 5 of the 6 planetary boundaries. Land system change, the biogeochemical cycle, and climate change are impending as the most important domains to be focused on regarding globalisation. Based on the findings, it can be recommended that governments and policymakers devote more attention to reframing and redesigning globalisation to be more environment friendly to achieve long-term sustainable development goals.

Improved insights into the adaptation and selection of Nitrosomonas spp. for partial nitritation under saline conditions based on specific oxygen uptake rates and next generation sequencing

Partial nitritation (PN) is a bioprocess that is essential for developing cost-effective biological nitrogen removal processes. Understanding the abundant bacterial communities responsible for nitrification under salt stress conditions is important to achieve a stable PN system for treating saline wastewater. Therefore, in this study, we identified the core nitrifying communities and investigated their correlations with the process parameters in a nitrifying bioreactor that was used for treating saline high-strength ammonia wastewater. A PN system worked efficiently under saline conditions with varying operational factors, such as temperature, dissolved oxygen (DO), and alkalinity. Interestingly, the specific oxygen uptake rate (SOUR) became similar under salt-free and saline media after the salt adaption. Next generation sequencing results suggested that the inactivation of Nitrobacter winogradskyi was a key factor for the PN reaction under salt stress conditions. We also found that Nitrosomonas europaea, a freshwater type ammonia-oxidizing bacteria (AOB), was predominantly found under both salt-free and saline conditions, whereas other halotolerant or halophilic AOB species, including Nitrosomonas nitrosa and Nitrosomonas mobilis, became selectively abundant under saline conditions. This implies that adaptation (training of N. europaea) and selection (presence of N. nitrosa and N. mobilis) were simultaneously attributed to selective ammonia conversion for the PN reaction. The redundancy analysis showed that the salinity and ammonia loading rates were statistically significant process parameters that determined the nitrifying bacterial community, suggesting that these parameters drive the adaptation and selection of the core AOB species during the PN reaction. Furthermore, the correlation analysis revealed that the abundance of N. nitrosa and N. mobilis was critically correlated with the specific oxygen uptake rates in saline media containing ammonia.

Mechanism that allows manno-oligosaccharide to promote cellulose degradation by the bacterial community and the composting of cow manure with straw

The new sugar source manno-oligosaccharide can regulate the structure of the microbial community. This study investigated the effects of adding manno-oligosaccharide at four different levels (0, 0.1%, 0.5%, and 1% w/w compost) to composting cow manure and straw on lignocellulose degradation and the bacterial community. Adding 0.5% manno-oligosaccharide had the greatest effects on accelerating the composting process, reducing its toxicity, and improving the stability of the product. After composting for 25 days, adding 0.5% manno-oligosaccharide decreased the hemicellulose, cellulose, and lignin contents to 2.25%, 11.25%, and 7.07%, respectively, compared with those under CK. Manno-oligosaccharide promoted the degradation of lignocellulose by increasing the abundances of Thermobifida, Streptomyces, and Luteimonas. In addition, manno-oligosaccharide inhibited pathogenic bacteria and increased the abundances of functional genes related to metabolism. Finally, adding 0.5% manno-oligosaccharide mainly affected the degradation of lignocellulose by enhancing the C/N ratio and the abundances of Streptomyces and the secretion system during composting according to redundancy analysis.

Characteristics of airborne bacterial communities and antibiotic resistance genes under different air quality levels

Pathogenic bacteria and antibiotic resistance genes (ARGs) in bioaerosols are major threats to human health. In this study, the microbial community structure and ARG distribution characteristics of airborne bacteria in total suspended particulates (TSP) and PM_2.5 were investigated under different air quality levels in Xinxiang, Central China. The results revealed that with the deterioration of air quality, the concentrations of airborne bacteria in both TSP and PM_2.5 decreased; however, the relative amounts of pathogenic bacteria increased. The predominant genera in pathogenic bacteria of Bacillus, Sphingomonas, Corynebacterium, Rhodococcus, and Staphylococcus were identified in both TSP and PM_2.5. Although the airborne bacteria concentrations and absolute abundances of ARGs in TSP were higher than those in PM_2.5 under identical air quality conditions, the bacterial community structure and relative amounts of pathogenic bacteria were similar. In addition, the relationship between environmental factors of ions, metal elements, and meteorological parameters and the community structures of airborne bacteria and pathogenic bacteria were also analyzed. The effects of soluble ions and metal elements on several dominant genera of total bacteria and pathogenic bacteria differed, probably due to the strong tolerance of pathogenic bacteria to harsh atmospheric environments Different subtypes of ARGs showed various distribution characteristics with variations in air quality. The deterioration of air quality can inhibit the dissemination of ARGs, as the minimum values of all ARGs and class 1 integrase intI1 were observed under Severely Polluted conditions. This study provides a comprehensive understanding of the effect of air pollution levels on the airborne bacteria community composition and ARG distribution.

Seasonal Variation and Contamination Risk Assessment of Heavy Metals in Surface Sediment of an Estuary Alluvial Island in Eastern China

The heavy metal pollution of estuary wetlands caused by industrial and agricultural production activities has aroused widespread concern. The Hakanson Pollution index, Geo-accumulation index (I_geo) and Redundancy analysis were used to explore the seasonal variation and contamination risk of heavy metals in surface sediments. Results showed that the heavy metal concentrations were ranked in descending order: Cd > Cu > Zn > Pb > Cr. The analysis result of HPI and I_geo showed that there was a low level of heavy metal contamination both in summer and winter. Redundancy analysis showed that the correlation between heavy metals and physicochemical properties of sediment was significantly different in winter and summer. Our findings provide scientific support for the prevention of heavy metal pollution in estuary wetlands.

Spatial distribution, homologue patterns and ecological risks of chlorinated paraffins in mangrove sediments along the South China Coast

The spatial distribution, homologue patterns, and ecological risks of chlorinated paraffins (CPs) were investigated in sediments from sixteen mangrove wetlands along the South China Coast (SCS). The total concentrations of CPs in mangrove sediments from Guangdong, Fujian, Guangxi, and Hainan were in the range of 933-4760, 619-2300, 375-1550, and 271-658 ng/g dry weight, respectively. The contamination levels and spatial distribution of short-chain and medium-chain CPs (SCCPs and MCCPs, respectively) in mangrove sediments were mainly affected by local population scale and CP industries. The dominant CP patterns in sediments were C₁₀-₁₁Cl_6-8 and C₁₄Cl_7-9 for SCCPs and MCCPs, respectively. Redundancy analysis, based on CP levels and several potential influencing factors showed that MCCPs/SCCPs ratio was the main factor affecting the accumulation of CPs in mangrove sediments. Additionally, MCCP concentrations were significantly correlated with total organic carbon (TOC), indicating that TOC might affect MCCP accumulation in mangrove sediments. Risk assessments indicated that CPs would pose medium ecological risks to sediment dwelling organisms in nearly one-third of the sampling sites. This is the first comprehensive report of the sedimentary SCCPs and MCCPs in mangrove wetlands along the SCS and highlights the need for more sediment toxicity data for CPs.

Key factors affecting seed germination in phytotoxicity tests during sheep manure composting with carbon additives

The germination index (GI) was widely applied to evaluate the phytotoxicity of compost. This study investigated the key phytotoxicity factors affecting seed germination in compost by using aqueous extracts in seed germination tests. The relationship between water-soluble substances in compost and seed germination, and their association with the microbial community were identified. In this study, sheep manure (SM) composted along or with three carbon additives (mushroom substrate, MS; cornstalks, CS; garden substrate, GS) for 49 days and, during this time, changes in multiple physical-chemical parameters, carbon and nitrogen matters, germination indexes (GI) and the compost microbiome were monitored. The results showed that all additives decreased water-soluble total nitrogen (TN), ammonium nitrogen (NH₄⁺-N) and low molecular weight organic acids, and significantly improved the seed germination indexes (seed germination rate, radical length and GI). The GI was correlated with water-soluble carbon degradation products (TOC, butyric acid, humic acid) and certain bacteria (Planifilum, Oceanobacillus, Ruminococcaceae_UCG_005 and Saccharomonospora). A structural equation model revealed that the main factors affecting seed germination were TOC (SM compost), acetic acid (SM+MS compost), humic acid (SM+CS compost), and pH (SM+GS compost). Low TOC and low molecular weight organic acids contents and higher humic acid content promoted GI. The research results could provide theoretical basis and measures for directional regulation of compost maturity.

Multi-level methods to quantify risk assessment, source apportionment and identifying key risk areas of soil toxic elements in Ashi River watershed, China

With the advancement of small watershed governance in agricultural production process, soil toxic element pollution issue in watersheds constitutes a recent research hot spot. The Ashi River watershed is an agriculture-dominated small watershed which is exposed to toxic element sources, posing high risk of toxic element pollution to the planting areas. In this study, collection of soil samples was carried out along the periphery of the river network, and the soil physicochemical parameters and toxic elements (As, Cd, Cr, Cu, Pb, and Zn) were analyzed. The results showed that: (1) The geo-accumulation index (I_geo) and potential ecological risk index were used to evaluate the pollution degree, and the contents of As, Cd, and Zn in some sampling sites exceeded risk screening values. Moreover, soils closer to mining sources were found to be more polluted; (2) Redundancy analysis confirmed the contribution rate relationship between environmental factors and toxic elements. C/N ratio, total carbon (C), and total potassium (K) exhibited significant relationships with toxic elements (P < 0.01 or P < 0.05), respectively. Moreover, geographic locations (longitude, latitude, and elevation) showed significant impacts on toxic element contents (except for Cu); (3) The apportionment of toxic element pollution sources by using principal component analysis showed that Pb, Zn, Cu, and Cd were mainly related to mining activities, while As was closely related to insecticide and herbicide, and Cr was mainly related to soil parent material and electroplating factory; (4) Through the integrated resistance base surface and toxic element sources combined with minimum cumulative resistance model, the toxic element risk areas were identified. The middle reaches corresponded to the extremely high risk zone, which undeniably requires the strengthening of the environmental management.

Hair and nails as noninvasive bioindicators of human exposure to chlorinated paraffins: Contamination patterns and potential influencing factors

Most of the studies on short- and medium-chain chlorinated paraffins (SCCPs and MCCPs) in human tissues have focused on human milk and blood. However, little is known about the occurrence of CPs in human hair and nails. In this study, SCCPs and MCCPs were analyzed in 62 pairs of human hair and nails from North China. Median concentrations (range) of SCCPs and MCCPs in human hair were 239 (19.2-877) and 325 (16.9-893) ng/g dw, respectively, all of which were significantly higher than 154 (57.7-355) and 233 (61.0-476) ng/g dw, respectively, in nail samples (p < 0.05). The homologue profiles of CPs in human hair were similar to those in nails, where SCCPs and MCCPs were dominated by C₁₀Cl_6-7 and C₁₄Cl_7-8, respectively. A significant positive relationship was observed between CP levels and age of people for hair, whereas negative linear correlations were observed for nails. The redundancy analysis indicated that age of people might be the main influencing factor on the accumulation of CPs in hair and nails. The present study performed comprehensive evaluation of CP exposure levels in human hair and nail and highlights the need for more data on relationship between internal and external exposure to CPs.

Spatial variations in soil organic carbon, nitrogen, phosphorus contents and controlling factors across the "Three Rivers" regions of southwest China

Based on the data of China Geochemical Baselines project, geostatistical analysis was used to investigate the spatial variations in soil organic carbon (SOC), total nitrogen (TN) and total phosphorus (TP) contents across the "Three Rivers" regions of southwest China, and the factors affecting them were analyzed by the redundancy analysis (RDA) and Person's correlation. Results showed that, the average content of SOC, TN and TP in the study area were 7.20 g/kg, 0.84 g/kg and 0.55 g/kg, respectively. The SOC and TN contents showed an obvious enrichment characteristic with great spatial variability, while TP content was stable on regional scale. The SOC, TN and TP contents decreased with elevation increase in the northern frigid highland, but showed an opposite character in the southern tropical & subtropical, which actually reflected the control of temperature on them. Combined with that there were higher SOC, TN and TP contents in subalpine meadow soil and red earth-yellow earth of the middle latitude zone, these suggested that the suitable temperature was conducive to the accumulation of soil nutrients. The weak positive correlation between population density and soil nutrients, together with high level of soil nutrients in the vicinity of large cities, demonstrated that human activities had significantly increased the soil nutrients contents in the study area. The RDA results showed that soil nutrients in the northern frigid highland were mainly controlled by the environmental factors dominated by temperature and soil structural factors dominated by parent materials with the total explanatory power as high as 75.87%, while in the southern tropical & subtropical mainly by the environmental factors dominated by chemical and biological weathering and the biological factors dominated by vegetation with the total explanatory power as high as 88.53%. The above factors superimposing a certain degree of human activities converged to cause that the SOC and TP contents in the south were higher than that in the north while the TN content was lower than that in the north.

Geo-climatic factors weaken the effectiveness of phytoplankton diversity as a water quality indicator in a large sediment-laden river

The study aims to determine whether phytoplankton diversity can be used as an indicator of water quality in large-scale sediment-laden rivers with heterogeneous environmental conditions. We hypothesized that environmental factors, such as sediment load, water surface slope, and precipitation, may impact the effectiveness of using phytoplankton diversity as a water quality indicator. To test this hypothesis, the Yellow River was selected for phytoplankton diversity and water quality assessments. We measured water quality parameters, calculated phytoplankton diversity indices, and collected data on geo-climatic variables at 130 sampling points in the Yellow River mainstream over two seasons (spring and autumn) in 2019. The results of the water quality assessment based on phytoplankton diversity indices were compared with those based on water quality index (WQI). Correlation analysis, multiple stepwise regression, distance-based redundancy analysis, and regression modeling were used to explore the biogeographical patterns and drivers of phytoplankton diversity. According to the WQI, the water quality gradually deteriorated from the source to the estuary of the river. Three biodiversity indices (Margalef, Pielou, and Shannon-Wiener) indicated that the water quality varied dynamically in the middle reaches of the river. The actual relationships between the biodiversity indices and WQI did not fit well with the standard curves of water quality classification based on the respective biodiversity indices and WQI. Variation partitioning analysis indicated that water quality parameters, such as sediment and nutrient load, were the dominant drivers of variation in phytoplankton diversity in most cases, with the contribution ranging from 11.0% to 25.7%. Geo-climatic factors, such as water surface slope and annual mean precipitation, also affected phytoplankton diversity, with the contribution reaching 27.8%. Therefore, in sediment-laden rivers with a large geographical span and complex environment, phytoplankton diversity cannot be used as a suitable water quality indicator, albeit it can reflect habitat changes to a certain extent.