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[Display omitted] • A data mining framework for analyzing antibiotics in bays worldwide was developed. • High levels of antibiotics in waters and sediments mainly occurred in Asian bays. • Environmental factors driving antibiotic distribution in bays were identified. • Compositional profiles of antibiotics varied between water and sediment matrices. • Priority antibiotics with potential ecological and health risks were listed. Antibiotics have been widely detected in bay ecosystems, yet little is known regarding their distribution, composition, sources, ecological and human health risks at the regional scale. We developed a systematic framework to mine data from existing publications and compiled an antibiotic concentration-based dataset containing 439 samples from 30 bays, and compared antibiotics across bays and matrices (water, sediment, and biota). Antibiotic concentrations varied considerably between bays, with hotspots occurring in East Asia. The main categories of antibiotics in waters included sulfonamide and macrolide, while tetracycline, quinolone, and macrolide antibiotics were prevalent in sediments. The main sources of antibiotics in bays included sewage treatment plant effluent, domestic sewage, agriculture runoff, and discharges from mariculture activities. Antibiotics with high ecological risks mainly included sulfamethoxazole, erythromycin, clarithromycin, and oxytetracycline. Erythromycin posed a considerable risk to human health, and the human health risks presented by other antibiotics were negligible. Regional variations of concentrations correspond to the uneven geographic consumption of antibiotics and their removal rate during wastewater treatment. Differences in antibiotics' composition between matrices are associated mainly with the physicochemical properties of antibiotics (e.g., molecular structure, solubility, and stability) and the content of total organic carbon, metal ions, chlorophyll a , and clay minerals in the sediments. To reduce the ecological and human health implications, priority should be given to the removal of erythromycin, sulfamethoxazole, oxytetracycline, and clarithromycin, with a special focus on their treatment in the Asian bay areas. [ABSTRACT FROM AUTHOR]

Global patterns in soil microbiomes are driven by non‐linear environmental thresholds. Fertilization is known to shape the soil microbiome of terrestrial ecosystems worldwide. Yet, whether fertilization influences global thresholds in soil microbiomes remains virtually unknown. Here, utilizing optimized machine learning models with Shapley additive explanations on a dataset of 10,907 soil samples from 24 countries, we discovered that the microbial community response to fertilization is highly dependent on environmental contexts. Furthermore, the interactions among nitrogen (N) addition, pH, and mean annual temperature contribute to non‐linear patterns in soil bacterial diversity. Specifically, we observed positive responses within a soil pH range of 5.2–6.6, with the influence of higher temperature (>15°C) on bacterial diversity being positive within this pH range but reversed in more acidic or alkaline soils. Additionally, we revealed the threshold effect of soil organic carbon and total nitrogen, demonstrating how temperature and N addition amount interacted with microbial communities within specific edaphic concentration ranges. Our findings underscore how complex environmental interactions control soil bacterial diversity under fertilization. [ABSTRACT FROM AUTHOR]

• A global dataset with 254,738 AMR-related manuscripts was complied. • An AI information retrieval system based on NLP was developed to extract knowledge. • Global foci and current knowledge gaps of AMR research were characterized. • More intersectoral AMR research is urgently needed to guide One Health AMR solutions. • Intrasectoral and intersectoral AMR research co-occurrence networks were constructed. The global health crisis posed by increasing antimicrobial resistance (AMR) implicitly requires solutions based a One Health approach, yet multisectoral, multidisciplinary research on AMR is rare and huge knowledge gaps exist to guide integrated action. This is partly because a comprehensive survey of past research activity has never performed due to the massive scale and diversity of published information. Here we compiled 254,738 articles on AMR using Artificial Intelligence (AI; i.e., Natural Language Processing, NLP) methods to create a database and information retrieval system for knowledge extraction on research perfomed over the last 20 years. Global maps were created that describe regional, methodological, and sectoral AMR research activities that confirm limited intersectoral research has been performed, which is key to guiding science-informed policy solutions to AMR, especially in low-income countries (LICs). Further, we show greater harmonisation in research methods across sectors and regions is urgently needed. For example, differences in analytical methods used among sectors in AMR research, such as employing culture-based versus genomic methods, results in poor communication between sectors and partially explains why One Health-based solutions are not ensuing. Therefore, our analysis suggest that performing culture-based and genomic AMR analysis in tandem in all sectors is crucial for data integration and holistic One Health solutions. Finally, increased investment in capacity development in LICs should be prioritised as they are places where the AMR burden is often greatest. Our open-access database and AI methodology can be used to further develop, disseminate, and create new tools and practices for AMR knowledge and information sharing. [ABSTRACT FROM AUTHOR]

• Data-driven framework shows distribution, factors, and pollution hotspots of ARGs. • Geospatial differences exist in the classes and abundance of ARGs in reservoirs. • Reservoir characteristics have a strong influence on ARG pollution. • ARGs in reservoir waters and sediments exhibited different pollution hotspots. • Data sharing is encouraged to improve data accessibility and depth of research. The propagation of antibiotic resistance genes (ARGs) in freshwater reservoirs threatens ecosystem security and human health, and has attracted increasing attention. A series of recent research articles on ARGs provides a unique opportunity for data-driven discoveries in this emerging field. Here, we mined data from a total of 290 samples from 60 reservoirs worldwide with a data-driven framework (DD) developed to discover geographical distribution, influencing factors and pollution hotspots of ARGs in freshwater reservoirs. Most data came from Asia and Europe where nine classes of ARGs were most frequently detected in reservoirs with multi-drug resistance and sulfonamide resistance genes prevailing. Factors driving distribution of reservoir ARGs differed between reservoir waters and sediments, and interactions among these factors had linear or nonlinear enhancement effects on the explanatory power of ARG distribution. During the cold season, small-sized reservoir waters rich in organic carbon, mobile genetic elements (MGEs) and antibiotics had a higher pollution potential of ARGs; during the spring drought, sediments in large reservoirs located in densely populated areas were more conducive to dissemination of ARGs due to their richness in antibiotics and MGEs. Thus, distribution pattern of ARG pollution hotspots in reservoir waters and sediments varies greatly depending on the differences of internal and external factors. From the "One Health" perspective, this widespread contamination of freshwater reservoirs by ARGs we discovered through the DD framework should be a push to promote integrated research across regions and disciplines. Especially the human - food-chain - ecosystem interface needs an improved understanding of ARG contamination mechanisms and targeted monitoring and evaluation systems should be developed to maintain all ecosystem services in freshwater reservoirs as well as to safeguard human health. [Display omitted] [ABSTRACT FROM AUTHOR]

Research on riverine microplastics has gradually increased, highlighting an area for further exploration: the lack of extensive, large-scale regional variations analysis due to methodological and spatiotemporal limitations. Herein, we constructed and applied a comprehensive framework for synthesizing and analyzing literature data on riverine microplastics to enable comparative research on the regional variations on a large scale. Research results showed that in 76 rivers primarily located in Asia, Europe, and North America, the microplastic abundance of surface water in Asian rivers was three times higher than that in Euro-America rivers, while sediment in Euro-American rivers was five times more microplastics than Asia rivers, indicating significant regional variations (p < 0.001). Additionally, based on the income levels of countries, rivers in lower-middle and upper-middle income countries had significantly (p < 0.001) higher abundance of microplastics in surface water compared to high-income countries, while the opposite was true for sediment. This phenomenon was preliminarily attributed to varying levels of urbanization across countries. Our proposed framework for synthesizing and analyzing microplastic literature data provides a holistic understanding of microplastic disparities in the environment, and can facilitate broader discussions on management and mitigation strategies. [Display omitted] • Constructed a framework for large-scale regional river microplastic analysis. • Integrated microplastic data from 76 rivers mainly in Asia, Europe, North America. • Detected regional variation in microplastics in bulk water and volume methods. • Contrasted microplastic pattern in water and sediment: Asia vs. Euro-America. • Observed higher in mid-income water, more prevalent in high-income sediment. [ABSTRACT FROM AUTHOR]

• Quantile regression more realistically quantify distance-decay equation of ARGs. • Study scales influence the understanding of biogeographical patterns of ARGs. • Data emergence has facilitated application of QR in the domain of DDR. Distance-decay (DD) equations can discern the biogeographical pattern of organisms and genes in a better way with advanced statistical methods. Here, we developed a data Compilation, Arrangement, and Statistics framework to advance quantile regression (QR) into the generation of DD equations for antibiotic resistance genes (ARGs) across various spatial scales using freshwater reservoirs as an illustration. We found that QR is superior at explaining dissemination potential of ARGs to the traditionally used least squares regression (LSR). This is because our model is based on the 'law of limiting factors', which reduces influence of unmeasured factors that reduce the efficacy of the LSR method. DD equations generated from the 99th QR model for ARGs were ' S all = 90.03e−0.01Dall ' in water and ' S all = 92.31e−0.011Dall ' in sediment. The 99th QR model was less impacted by uneven sample sizes, resulting in a better quantification of ARGs dissemination. Within an individual reservoir, the 99th QR model demonstrated that there is no dispersal limitation of ARGs at this smaller spatial scale. The QR method not only allows for construction of robust DD equations that better display dissemination of organisms and genes across ecosystems, but also provides new insights into the biogeography exhibited by key parameters, as well as the interactions between organisms and environment. [Display omitted] [ABSTRACT FROM AUTHOR]

• We construct a Contrasting Analysis of Scales approach for groundwater microplastics. • The morphology of microplastics is different between open and closed groundwater. • Groundwater in landfills and nature reserves is heavily contaminated. • Groundwater is at high ecological risk of microplastics, especially in Asia. • More serious microplastic contamination may exist downstream of groundwater. Given that microplastics (MPs) in groundwater have been concerned for risks to humans and ecosystems with increased publications, a Contrasting Analysis of Scales (CAS) approach is developed by this study to synthesize all existing data into a hierarchical understanding of MP accumulation in groundwater. Within the full data of 386 compiled samples, the median abundance of MPs in Open Groundwater (OG) and Closed Groundwater (CG) were 4.4 and 2.5 items/L respectively, with OG exhibiting a greater diversity of MP colors and larger particle sizes. The different pathways of MP entry (i.e., surface runoff and rock interstices) into OG and CG led to this difference. At the regional scale, median MP abundance in nature reserves and landfills were 17.5 and 13.4 items/L, respectively, all the sampling points showed high pollution load risk. MPs in agricultural areas exhibited a high coefficient of variation (716.7%), and a median abundance of 1.0 items/L. Anthropogenic activities at the regional scale are the drivers behind the differentiation in the morphological characteristics of MPs, where groundwater in residential areas with highly toxic polymers (e.g., polyvinylchloride) deserves prolonged attention. At the local scale, the transport of MPs is controlled by groundwater flow paths, with a higher abundance of MP particles downstream than upstream, and MPs with regular surfaces and lower resistance (e.g., pellets) are more likely to be transported over long distances. From the data-scaled insight this study provides on the accumulation of MPs, future research should be directed towards network-based observation for groundwater-rich regions covered with landfills, residences, and agricultural land. [Display omitted] [ABSTRACT FROM AUTHOR]

[Display omitted] • A data mining framework for analyzing microplastics in marine bays was developed. • Higher levels of sedimental microplastics mainly occurred in East Asian bays. • Influencing factors of microplastic distribution were identified. • An environmental risk assessment system of sedimental microplastics was proposed. • Microfibers should be given priority in mitigating environmental risk. Microplastic contamination in the sediment of marine bays has attracted widespread attention, whereas the distribution, sedimentation, morphology and risk of microplastics at regional scale remain poorly understood. By introducing a data mining framework into microplastic research, we compiled a microplastic dataset of 649 samples from 24 bays to enhance the understanding of geographical difference and drivers, transfer, composition profile and environmental risk of sedimental microplastics. Microplastic abundance varied from 0.72 to 1963.96 items/kg dry weight, with higher concentrations mainly occurring in East Asian bays. The spatial pattern in abundance was driven by the river plastic emissions, aquaculture production and hydrodynamic condition. A significantly positive correlation between microplastic abundance in water and sediment was found, and microplastic sedimentation was related to polymer density, hydrodynamic conditions and sediment properties. The dominant shape and polymer of sedimental microplastics were fiber and polypropylene, respectively, and the similarity of microplastic composition decreased with increasing geographical distance. The environmental risks of microplastics were partitioned into three classes (Rank II-Rank IV) with a two-dimensional assessment system considering the bioavailability and toxicity of microplastics, and Asian bays were identified as potential high-risk areas. To reduce the environmental risk of sedimental microplastics in bays, priority should be given to the removal of microfibers, and control measures depend on the risk classes and dominant polymers. Microplastic abundance and composition were significantly affected by methodological choices regarding sampling, pretreatment and identification, suggesting a unified methodology is essential to further enhance our knowledge on the distribution and risk of microplastics in marine bays. [ABSTRACT FROM AUTHOR]

The unreasonable use of antibiotics and the transmission of antibiotic resistance genes (ARGs) induced by antibiotics have led to a large number of ARGs entered the water environment, which seriously threatened human health and environmental safety. The estuarine aquatic environment connects with inland rivers and sea and is frequently influenced by human activities. This study aims to reveal the occurrences and abundances of ARGs and bacterial community composition by high-throughput quantitative PCR including 296 primers and high-throughput sequencing in the tide rising and ebbing of surface water in the Yongjiang Estuary, China. The results showed that there were a large number of ARGs and mobile genetic elements (MGEs) detected in the rising tide and ebb tide water bodies. The numbers of detected ARGs in each sample at rising and ebb tide ranged from 16 to 77 and 61 to 88, respectively, and the absolute abundance ranges were 1.69 × 104–1.69 × 109 copies/L and 3.18 × 103–2.57 × 109 copies/L, respectively. Obvious tidal distribution characteristics of ARGs were showed. Most of ARGs conferred resistance to multidrug, aminoglycosides and sulfanilamides. Proteobacteria, Actinobacteria and Bacteroidetes were the dominantly bacterial phylum in the Yongjiang Estuary. Network analysis results indicated that multi-genera were identified as possible ARGs hosts, and they carried more than two types of ARGs genes. Partial least squares path modeling further revealed that MGEs and bacterial community composition were the most important driving factors. The results of the study can provide the corresponding scientific basis for the diffusion and control of ARGs in estuaries. • Tides had influences on the abundance of ARGs. • The abundance of multidrug resistance genes was the highest. • ARGs might have more than one potential hosts. • MGEs and bacterial community composition were the key factors affecting the spread of ARGs. [ABSTRACT FROM AUTHOR]

Sulfate-reducing prokaryotes (SRP) represent a diverse group of heterotrophic and autotrophic microorganisms that are ubiquitous in anoxic habitats. In addition to their important role in both sulfur and carbon cycles, SRP are important biotic and abiotic regulators of a variety of sulfur-driven coupled biogeochemical cycling of elements, including: oxygen, nitrogen, chlorine, bromine, iodine and metal(loid)s. SRP gain energy form most of the coupling of element transformation. Once sulfate-reducing conditions are established, sulfide precipitation becomes the predominant abiotic mechanism of metal(loid)s transformation, followed by co-precipitation between metal(loid)s. Anthropogenic contamination, since the industrial revolution, has dramatically disturbed sulfur-driven biogeochemical cycling; making sulfur coupled elements transformation complicated and unpredictable. We hypothesise that sulfur might be detoxication agent for the organic and inorganic toxic compounds, through the metabolic activity of SRP. This review synthesizes the recent advances in the role of SRP in coupled biogeochemical cycling of diverse elements. [ABSTRACT FROM AUTHOR]

We used statistical approach by coupling redundancy analysis with linear regression analysis, which is useful to understand potential sources of antibiotics in the tide rising and ebbing of surface water in the Yongjiang Estuary, China. This study aimed to investigate the relationship between 29 antibiotics at five sites over four seasons and 13 environmental parameters during the tide rising and ebbing durations. The results found that dissolved organic carbon (DOC), salinity, temperature and chlorophyll a (Chla) were the main factors to impact antibiotics. The concentrations of macrolides were increasing with DOC, suggesting DOC may influence the adsorption capacity of antibiotics. The concentrations of tetracyclines had significant correlation with temperature and Chla during the tide rising period. This study demonstrated a method of exploring the relationship between the concentrations of antibiotics and environmental parameters, which is beneficial to future antibiotics research in estuaries. • Statistical approach applied in the field of antibiotics. • Redundancy analysis with linear regression analysis is used. • Explore responses of estuarial antibiotics to environmental drivers. [ABSTRACT FROM AUTHOR]