Sensitivity Distribution Research Articles

Development of Highway Construction Route Selection Based on Ecological Sensitivity Evaluation and Intervention Optimization Strategy Research

Ecological sensitivity is an essential indicator for measuring the degree of ecological fragility of a region, and traditional highway routing ignores the ecological benefits of regional nature, which causes irreversible impacts on the natural environment. Based on the AHP method, this paper carries out a comprehensive assessment of the ecological sensitivity of the K0+000~K56+438 section of the Guanzhuang Tourist Highway in the Zhangjiajie Wuling Mountain Area from 2000 to 2020, and it utilizes the spatial autocorrelation analysis method to reveal the pattern of its spatial and temporal changes in ecological sensitivity. The following results were obtained. (1) The ecological condition of the study area is gradually improving, and the areas with higher sensitivity are mainly distributed in the northeast and southwest of the study area. (2) The ecological sensitivity of the study area has strong spatial autocorrelation, but the autocorrelation has been reduced in recent years, and the distribution of the ecological sensitivity has been gradually discretized. (3) There are problems of high ecological risk and construction difficulty in the traditional highway route selection scheme of the A line. The optimized route selection scheme, the K line, can effectively avoid highly sensitive areas by adjusting the route and bridge settings. Finally, the article proposes engineering construction suitability and ecological restoration strategies for different road sections regarding vegetation cover, landscape risk, and geological hazards. This study establishes a set of comprehensive technical chains for tourism highway routing in ecologically fragile areas based on the spatial and temporal evolution of sensitivity, which provides new ideas for traditional highway routing and is of great significance for maintaining the balance and stability of ecosystems within the road area.

Spatiotemporal Variations and Driving Factors of Ecological Sensitivity in the West Qinling Mountains, China, Under the Optimal Scale

This study selected the five indicators of soil erosion, climate environment, geological hazards, biodiversity, and human disturbances and uses the entropy weight method to calculate the ecological sensitivity of the West Qinling Mountains from 2000 to 2020. The analysis produced a spatiotemporal distribution of ecological sensitivity over the 20-year period. An equal step size of 500 m was used to progressively increase the spatial scale from 500 m to 6 km. The optimal scale for the spatial differentiation of ecological sensitivity in the West Qinling Mountains was determined by analyzing the characteristics of changes at different scales, response mechanisms, and optimal parameters for geographical detector spatial scale identification. Based on this scale, the change in intensity and pattern and the influencing factors of ecological sensitivity were analyzed. The results show the following: (1) The 5.5 km spatial scale balances the requirements of accuracy, spatial heterogeneity, and data adequacy, making it the optimal scale for analyzing the spatiotemporal variation patterns of ecological sensitivity in the West Qinling Mountains. (2) From 2000 to 2020, the mean ecological sensitivity in the West Qinling Mountains exhibited a decreasing trend, indicating an improvement in the ecological environment. Spatially, the ecological sensitivity of the West Qinling Mountains showed a spatial distribution pattern of “low in the west and high in the east, low in the south and high in the north”. During the study period, the ecological sensitivity in the West Qinling region remained generally stable, with no high-frequency changes observed. (3) Population density is the primary driving factor of spatial differentiation of ecological sensitivity in the West Qinling Mountains, while GDP serves as a secondary factor. Overall, socioeconomic factors have the most significant impact on ecological sensitivity. (4) Over 75% of the ecological sensitivity trends exhibit patterns of perennial unchanged and fluctuating unchanged trends, with areas of fluctuating increase smaller than areas of fluctuating decrease. Regions of perennial high sensitivity are primarily concentrated in the northeastern part of the West Qinling Mountains, while areas with increased fluctuation in ecological sensitivity are mainly located in the western and southern parts of the West Qinling Mountains. Future efforts should focus on these regions.

Biodiversity-safeguarding threshold for urea-fertilizer application on paddy fields: Protozoa-based toxicity tests

Urea is a widely applied fertilizer to enhance crop yields. Ecological risks associated with the excessive application of urea fertilizer threaten the paddy fields' sustainable agriculture and biodiversity preservation. There are no practical thresholds based on proven data on microbial communities. Protozoa are nitrogen-sensitive organisms. For the first time, this study conducted acute and chronic urea toxicity tests on eight species of organisms. The results indicate that Blepharisma sp. is the most sensitive species to urea exposure and is a suitable indicator for determining the safe threshold of urea. This study estimated the predicted no-effect concentration using species sensitivity distribution curves. Subsequently, it established the threshold for urea application in rice fields based on the fields' area and the surface water's height. The short-term safety threshold for urea in the studied paddy field with black soil is 87.7mg/L, equivalent to 43.85kg of urea per hectare for a single nitrogen fertilizer application. The long-term safety threshold is 5.02mg/L, representing the concentration for re-applicating urea. The biodiversity-safeguarding application threshold provides the basis for developing a urea fertilizer reduction protocol to safeguard the paddy fields' biodiversity.

A New Approach to Differentiate the Causes of Excessive Cadmium in Rice: Soil Cadmium Extractability or Rice Variety

In order to effectively decrease cadmium (Cd) in rice grains in contaminated paddy soil and maintain the safe production of rice, identifying excessive Cd in rice caused by rice varieties or soil Cd is critical, but it is currently lacking. In the present study, the soil ethylenediaminetetraacetic acid (EDTA)-extractable Cd (EDTA-Cd) and the bioaccumulation factors of rice based on EDTA-Cd (BCFEDTA-Cd) were used to develop an approach to identify excessive Cd in rice caused by rice varieties or soil Cd. Based on an empirical soil–plant transfer model and species sensitivity distribution (SSD), BCFEDTA-Cd and EDTA-Cd were divided into five grades. The results showed that the five grades of the EDTA-Cd (minimum value less than 0.11 mg/kg and maximum value greater than 2.93 mg/kg) and BCFEDTA-Cd (minimum value less than 0.09 and maximum value greater than 1.40) were classified in the normal soil pH range. Further, the conversion equation between EDTA-Cd and diethylene triamine pentaacetic acid (DTPA)-Cd was obtained through linear regression analysis using 67 sets of soil data from the literature. In addition, the four selected rounding thresholds for the percentage of EDTA-Cd to total soil Cd (EDTA-Cd) (%) were 52.5, 67.5, 82.5, and 97.5%. A selected soil EDTA-Cd (%) (about 75%) can be used to identify the status of soil bioavailability, especially in soil with high background Cd. Finally, a set of 1084 pairs of rice and soil data for Cd-contaminated soils was used to investigate the respective contributions of rice varieties and soil Cd when Cd in rice exceeds the limit (0.2 mg/kg). Based on field experiment data, a systematic identification approach for the causes of rice Cd exceeding the limit, soil Cd or rice variety, was established and applied. In conclusion, under Cd exposure conditions, the importance of the causes of Cd in soil and rice varieties can be identified, and their contributions can be distinguished, thus helping to identify the causes of Cd contamination in rice.

Biomarker and adverse outcome pathway responses of Tubifex tubifex(sludge worm) exposed to environmentally-relevant levels of acenaphthene: insights from behavioral, physiological, and chemical structure-activity analyses.

Polycyclic aromatic hydrocarbons (PAHs), including acenaphthene, pose a significant threat to aquatic ecosystems by harming vital organisms such as benthic invertebrates. This study evaluated the impact of environmentally relevant concentrations of acenaphthene on Tubifex tubifex, focusing on sublethal acute toxicity and subchronic biomarker responses. Key biomarkers assessed included histopathological changes and the modulation of antioxidant enzymes: catalase (CAT), superoxide dismutase (SOD), glutathione S-transferase (GST), and malondialdehyde (MDA). Additionally, the study examined structure-activity relationships and species sensitivity distribution (SSD). Concentrations exceeding the solubility threshold of acenaphthene (3.9 mg/L) triggered distinct, concentration-dependent behavioral responses in Tubifex tubifex, such as clumping, mucus secretion, and body wrinkling. Prolonged exposure exacerbated these behavioral dysfunctions, while subchronic exposure resulted in significant histopathological alterations, including epithelial hyperplasia, inflammation, edema, fibrosis, and degenerative changes. The edematic appearance of the body wall suggested a potential immune response to exposure. Furthermore, increased activities of CAT, SOD, and GST indicated oxidative stress in the worms. The study found a 1.5-fold increase in CAT and GST activity, a fivefold increase in SOD, and a striking 100-fold increase in MDA levels compared to controls, signifying an overwhelmed antioxidant defense system and potential cellular disruption. The SSD curve revealed hazard concentrations (HC50 and HC90), indicating that Tubifex tubifex exhibited lower sensitivity to acenaphthene compared to other taxa. In silico analysis and read-across models confirmed the potential of acenaphthene to induce significant oxidative stress upon exposure. The correlation between biomarker responses and structure-activity relationship analysis highlighted the aromatic nature of acenaphthene as a key factor in generating reactive metabolites, inhibiting antioxidant enzymes, and promoting redox cycling, ultimately contributing to adverse outcomes. These findings, coupled with behavioral responses and SSD curve inferences, underscore the importance of the solubility threshold of acenaphthene as a critical benchmark for evaluating its ecological impact in aquatic environments.

Harnessing Ascidians as Model Organisms for Environmental Risk Assessment

Environmental Risk Assessment (ERA) often relies on a restricted set of species as bio-indicators, introducing uncertainty when modeling complex environmental variables. This may lead to oversimplified or erroneous risk assessments. Ascidians, marine filter-feeding sessile chordates, are valuable models for scientific research in various biological fields such as stem cell biology, embryogenesis, regeneration, innate immunity, and developmental biology. Their global distribution, sensitivity to pollutants, high abundance, mass sexual reproduction, and habitation in coastal areas impacted by anthropogenic pollution make them excellent indicators for monitoring marine pollution and global environmental changes, including biological invasions and species diversity diminution cases. Despite their potential as environmental bioindicators, ascidians remain underutilized in ERAs (≤0.13% of ERA studies), particularly in the field of chemical pollution impact assessment, primarily due to a lack of standardization. This underrepresentation poses a challenge for accurate modeling, especially in models relying on a broad range of species (e.g., Species Sensitivity Distributions). Given these constraints, expanding the use of ascidians in ERAs could improve the comprehension and precision of environmental changes and their assessments. This underscores the necessity for future research to establish standardized testing protocols and choose the most suitable ascidian species for inclusion in ERAs.

Risk assessment of Arsenic in surface water of China water systems based on a time-dependent species sensitivity distribution (SSD) method

Arsenic (As) is a naturally occurring metalloid element widespread in the environment. Assessing the ecological risk of As in surface water, especially the acute risk caused by emergent pollution incidents, is of great significance. However, acute toxicity data including median lethal concentration (LC50) and median effective concentration (EC50) of As derived by toxicology experiment may vary according to the exposure time, which is referred as time dependence effect. Time dependence not only affects toxicity data but also influences the characterization of acute risk in the ecosystem. However, previous research on the time dependence effect of As, especially the quantitative influence on the risk assessment is still limited. In this research, acute toxicity data of As(III) and As(V) was collected. Time dependence of toxicology data of inorganic As was studied. Time-dependent species sensitivity distributions of freshwater species were established. The hazardous concentration for 5% of species (HC5) values in different exposure time were further derived. Finally, the dynamic ecological risk of As in major Chinese water basins was evaluated. The results suggested that the toxicity data of inorganic As had a significant linear relationship (p < 0.01) with time. The HC5 values of As (III) and As (V) at an exposure time of four days were reduced by 15.5% and 77.5%, respectively, as compared to the HC5 value of one day. According to the ecological risk characterized by the probability density overlapping area method, the ecological risk of As(III) and As(V) increases with the exposure duration. The Yangtze River had the highest risk, with risk values ranging from 19.9% to 22.6%. According to the results, the time dependence of toxicity data should be fully considered in the formulation of water quality criteria or ecological risk assessment so as to provide better protection for the water ecosystem security.

Characterizing Ecological Sensitivity of Yangtze River Delta Urban Agglomeration in China

Ecological sensitivity, as one of the most important indicators to evaluate regional environmental issues, holds significant implications for ecological governance and management in the related area. This study utilized remote sensing imagery of Landsat Thematic Mapper (TM) from the Yangtze River Delta (YRD) in 2014 and 2018, combined with field surveys and socio-economic data. Considering the local ecological and environmental conditions in the region, nine factors related to seven aspects, soil erosion, topography, humidity, habitat, water environment, human interference, and climate, were selected to create an ecological sensitivity evaluation framework for the YRD urban agglomeration. The coefficient of variation method was applied to determine factor weights, while the zonal statistics and spatial overlay methods were used for a comprehensive analysis of ecological sensitivity in a geographic information system (GIS). The YRD urban agglomeration was categorized into five ecological sensitivity levels: extremely sensitive, highly sensitive, moderately sensitive, slightly sensitive, and insensitive. The analysis results revealed spatial variations in the distribution of ecological sensitivity across the YRD urban agglomeration, with the overall ecological sensitivity level being slightly sensitive. The proportions of the total area occupied by extremely sensitive, highly sensitive, moderately sensitive, slightly sensitive, and insensitive zones were 14.30%, 12.02%, 25.29%, 30.34%, and 18.05% in 2014, and 14.30%, 24.01%, 16.33%, 27.32%, and 18.05%, respectively, in 2018. Based on these results, relevant ecological vulnerabilities for the YRD urban agglomeration were discussed.

Effects of α-olefin sulfonate (AOS) on Tubifex tubifex: toxicodynamic-toxicokinetic inferences from the general unified threshold (GUTS) model, biomarker responses and molecular docking predictions.

We investigated the potential ecological risks and harm to aquatic organisms posed by anionic surfactants such as α-olefin sulfonate (AOS), which are commonly found in industrial and consumer products, including detergents. This study assessed acute (96-h) and subchronic (14-day) responses using antioxidant activity, protein levels, and histopathological changes in Tubifex tubifex exposed to different AOS concentrations (10% of the LC50, 20% of the LC50, and a control). Molecular docking was used to investigate the potential interactions between the key stress biomarker enzymes (superoxide dismutase, catalase, and cytochrome c oxidase) of Tubifex tubifex. Acute AOS exposure showed a concentration-dependent decrease in survival, and the general unified threshold (GUTS) model revealed that survivorship is linked to individual response patterns rather than random (stochastic) fluctuations. The GUTS model also revealed dose-dependent toxicity patterns in Tubifex tubifex exposed to α-olefin sulfonate (AOS), with adaptive mechanisms at lower concentrations but significant increases in mortality beyond a certain threshold, emphasizing the role of the AOS concentration in shaping its toxicological impact. Exposure to AOS disrupted antioxidant activity, inducing oxidative stress, with GST and GPx showing positive associations with surfactant concentration and increased lipid peroxidation (elevated MDA levels); moreover, AOS exposure decreased protein concentration, signifying disturbances in vital cellular processes. Histopathological examinations revealed various tissue-level alterations, including cellular vacuolation, cytoplasmic swelling, inflammation, necrosis, and apoptosis. Molecular docking analysis demonstrated interactions between AOS and enzymes (-catalase, superoxide dismutase, and cytochrome c oxidase) in Tubifex tubifex, including hydrophobic and hydrogen bond interactions, with the potential to disrupt enzyme structures and activities, leading to cellular process disruptions, oxidative stress, and tissue damage. According to the species sensitivity distribution (SSD), the difference in toxicity between Tilapia melanopleura (higher sensitivity) and Daphnia magna (low sensitivity) to AOS suggests distinct toxicokinetic and toxicodynamic mechanisms attributable to more complex physiology in Tilapia and efficient detoxification in Daphnia due to its smaller size.

Derivation of ecological safety thresholds and risk assessment of new SDHI fungicides in farmland system

Succinate dehydrogenase inhibitor (SDHI) fungicides have become some of the top-selling fungicides in recent years. As the utilization of these fungicides intensifies, the corresponding potential risks to the environment proportionately increase. However, there is still limited knowledge about their toxic effects on ecosystems. In this study, acute toxicity data from laboratory assessments of the springtail Folsomia candida, alongside collected data from terrestrial and aquatic non-target species, were utilized to construct a species sensitivity distribution (SSD) model for both terrestrial and aquatic non-target organisms. Subsequently, we derived ecological baseline values for diverse scenarios within ecosystems. The results indicated that benzovindiflupyr exhibited the highest 7-day median lethal concentration (7d-LC50) to Folsomia candida at 2.0 μg cm−2, while the toxicity levels of other SDHI fungicides varied, ranging from 99 to 304 μg cm−2. In agricultural environments, the Hazard Concentration for 5 % of species (HC5) values for fluxapyroxad, boscalid, sedaxane, and isopyrazam were determined to be 8.0, 1240, 12.97, and 25.37 g ha−1, respectively. In aquatic environments, the HC5 values for benzovindiflupyr, fluxapyroxad, boscalid, sedaxane, isopyrazam, and carboxin were 0.0013, 0.022, 1.76, 0.372, 0.013, and 0.161 mg L−1, respectively. In an evaluation of typical agricultural scenarios within China, SDHI fungicides were found to exert substantial ecological risks to terrestrial non-target fauna and aquatic ecosystems around agricultural fields. Specifically, isopyrazam and fluxapyroxad were identified as posing heightened ecological risks to Typhlodromus pyri and Aphidius rhopalosiphi. Moreover, the application of benzovindiflupyr, carboxin, isopyrazam, and fluxapyroxad in paddy field environments is associated with unacceptable risks to groundwater. The findings of this study contribute significantly to the environmental risk evaluation of SDHI fungicides within farmland system, thereby informing the development of policy frameworks for their scientifically grounded application.

Derivation of environmental quality standards for free cyanide incorporating censored data into species sensitivity distributions

Free cyanide is considered to be the most toxic form of cyanides to aquatic life. Due to its broad range of uses and subsequent potential widespread emissions to surface water, the environmental effects of free cyanide have been extensively researched. Regulatory bodies have proposed water quality standards for free cyanide, but these are regularly debated and implementation has been inconsistent due to monitoring challenges. The aim of the present study was therefore to derive new environmental quality standards (EQS) for free cyanide according to the Water Framework Directive (WFD). Ecotoxicity data from previous derivations and an additional literature search were gathered and individually (re) evaluated on reliability. The pooled acute ecotoxicity dataset consisted of reliable results for 35 species, distributed over 8 taxonomic groups. The pooled chronic ecotoxicity dataset consisted of results for 13 species, distributed over 7 taxonomic groups. WFD criteria for deriving a species sensitivity distribution (SSD) were met, if censored data points were included. Using the R-package ETX 3.0, an SSD including censored data was constructed and acute and chronic HC5 values of 17 and 0.66 μg/L, respectively, were derived. Comparisons were made with alternative SSDs constructed by transforming or discarding the censored data. Applying a default assessment factor (AF) of 10 to the HC5 from the acute SSD resulted in a MAC-EQS of 1.7 μg CN/L for freshwater and marine water. Careful consideration was given to addressing the uncertainty around the chronic HC5 value for the selection of an AF of 3, resulting in an AA-EQS of 0.22 μg CN−/L for freshwater and 0.044 μg CN−/L for marine water by applying an additional AF of 5. It is concluded that the current environmental quality standards for free cyanide are the first to be derived according to the WFD guidance, using only reliable data and including censored values.

Comparison of three artificial intelligence methods for predicting 90% quantile interval of future insulin sensitivity of intensive care patients

Insulin dosing of hyperglycemic patients in the intensive care unit (ICU) is a complex and nonlinear clinical control problem. Recent model-based glycemic control protocols predict a patient-specific and time-specific future insulin sensitivity distribution, which defines the future patient state in response to insulin and nutrition inputs. The prediction methods provide a 90% confidence interval for a future insulin sensitivity distribution for a given time horizon, making the prediction problem more specific compared to common prediction problems where the aim is to predict the expected value of the given stochastic parameter. This study proposes three alternative artificial intelligence-based insulin sensitivity prediction methods to improve the prediction accuracy and make prediction parameters better fit the clinical requirements. The proposed prediction methods use different neural network models: a classification deep neural network model, a Mixture Density Network model, and a Quantile Regression-based model. A large patient data set was used to create the neural network models, including 2357 patients and 92646 blood glucose measurements from three clinical sites (Christchurch, New Zealand, Gyula, Hungary, and Liege, Belgium). Prediction accuracy was assessed by statistical metrics expressing clinical requirements, as well as via validated in-silico virtual patient simulations comparing the clinical performance of a proven glycaemic control protocol using the alternative prediction methods to assess impact on glycemic control performance and thus the need for these alternative models.

Critical Evaluation and Meta-Analysis of Ecotoxicological Data on Per- and Polyfluoroalkyl Substances (PFAS) in Freshwater Species.

Despite the increasing concern regarding the ecological risks posed by per- and polyfluoroalkyl substances (PFAS), a lack of comprehensive understanding of their actual ecotoxicity remains. Through a meticulous examination of 91 peer-reviewed studies investigating effects at a population level and constructing probabilistic species sensitivity distributions (PSSDs), we present a state-of-the-science hazard assessment of PFAS in freshwater species. Using data subsets containing suboptimal data led to an overestimation of the predicted no-effect concentrations (PNECs) of PFAS. We report PNECs of perfluoroalkyl carboxylic acids (PFCAs) and perfluoroalkyl sulfonates (PFSAs) in freshwater to be 4.8-2000 μg/L and 0.4-8.9 μg/L, respectively, derived from high-quality data. Statistical analyses revealed that both functional groups and carbon chain length significantly influenced (p < 0.05) the variations in toxicity observed among different PFAS. This study underscores the importance of obtaining high-quality PFAS ecotoxicity data to comprehend associated hazards. The PNECs of PFAS derived in this study are higher compared to those of micro/nanoplastics and persistent organic pollutants. Our research offers valuable insights into prioritizing the regulation of more toxic PFAS.

Robust estimator of the ruin probability in infinite time for heavy-tailed distributions

The probability of ruin of an insurance company is one of the main risk measures considered in risk theory, and the problems of its calculation and approximation have attracted much attention. Statistical estimations have been developed on the ruin probability in infinite time for insurance loses from heavy-tailed distributions. However, these estimation suffer heavily from under-coverage or have a robustness problem. We therefore need another method for estimating the probability of ruin in infinite time for heavy-tailed losses. In this paper, we introduce a robust estimator of the infinite-time probability of ruin for such distributions. Our methodology is based on extreme value theory, which offers adequate statistical results for such distributions. Our approach is based on a sensitive distribution known as the t-Hill estimator (t-score or score moment estimation) for the index of any tail distribution and introduced in Fabiáan and Stehlík. We establish their asymptotic normality, and through a simulation study, illustrate their behaviour in terms of absolute bias and mean squared error. The simulation results show that our estimators perform well and that they are fairly robust to outliers.

Predicting soil ecological criteria of 17 metal(loid)s in China based on quantitative ion character-activity relationship - Species sensitivity distribution (QICAR-SSD) coupled model

Soil pollution caused by metal(loid)s is increasingly serious and poses unexpected risks to terrestrial organisms. Establishing soil quality standards is essential for assessing ecological risks of metal(loid)s and protecting soil ecosystems. However, the limited availability of metal(loid) ecotoxicological data has hampered the development of soil quality standards due to financial and practical constraints on toxicity testing. This study collected 77 normalization equations and 58 cross-species extrapolation equations to calculate the normalized EC10 (the added concentration causing a 10 % inhibition effect) of metal(loid)s under a representative scenario. A set of quantitative ion character-activity relationship (QICAR) models were then constructed using normalized EC10 and nine critical ionic characters (AR, AR/AW, BP, MP, Z/r2, Z/r, Xm, σp, and |Log(KOH)|). Subsequently, these QICAR models were employed to predict ecotoxicological EC10 of 17 metal(loid)s to 12 soil species and coupled with species sensitivity distribution (SSD) to determine Predicted No Effect Concentration (PNEC). The results demonstrated the coupled QICAR-SSD model could effectively derive terrestrial PNEC for data-poor metal(loid)s, with errors between the predicted PNEC and reported soil standards (excluding soil background levels) from different countries mostly <0.3 orders of magnitude. Finally, soil ecological criteria (SEC) for 17 metal(loid)s were calculated using an added risk approach based on PNEC and national soil background concentration. Overall, the coupled model proposed here can provide a valuable supplement to the development of soil quality standards for numerous metal(loid)s in soil components.

Predicting the ecological risk thresholds of soil metals in Europe using the quantitative ion character-activity relationships (QICAR) model

Metal pollutants have become increasingly diverse. Therefore, managing the ecological risks associated with these elements in soil is urgently required. However, determining the soil ecological risk thresholds of elements through routine toxicological tests is time-consuming and laborious, establishing prediction models is vital to risk management. Accordingly, this study aimed to predict the element toxicity to soil organisms by collecting the toxicological data of eight elements to soil organisms at 18 European and 17 Chinese sites through literature and toxicology databases, using the quantitative ion character-activity relationship (s-QICAR) model. Firstly, the toxicity values (logEC10) of eight elements to five biological species and three microbial processes were obtained through clustering and soil normalization methods in three typical soil scenarios. Correlation analysis revealed that for different species and microbial processes, there are three to six physicochemical properties of elements related to their toxicity, among which, the covalent radius of the element was the best significantly correlated with logEC10 of all organisms (R2 = 0.77–0.95). Based on this, the s-QICAR model was established and used to predict the logEC10 of Sc, Ti, V, Cr, Co, Ni, Cu, and Zn to eight organisms. Furthermore, along with the species sensitivity distribution curve, the HC5 values (i.e., 95% species protection level) for the above eight elements were calculated. Following correction, the predicted no-effect concentrations of these elements ranging from 9 to 189 mg/kg, and the ecological risk threshold map has been produced. In summary, we present a new method to quantify the ecological risk of metal-induced pollution in European soils without routine toxic measurements, and provide important insights into soil pollution risk assessment and management.

Ecological risk threshold for chromium in Chinese soils and its prediction models

The derivation of chromium (Cr) ecological risk thresholds in soils remains limited, despite their importance as measurement standards and indicators for enacting soil protection policies. In this study, toxicity of Cr in soil to different species was tested based on Log-Logistic dose-effect relationship. On this basis, combined with Cr toxicity measurement data in literature, the ecological risk threshold HC5 for protecting 95% species safety in soils with different properties was obtained by fitting species sensitivity distribution curve (SSD). This research collected various Cr toxicological data from Chinese cropland soils, based on 31 different endpoints covering soil fauna, functional indicators of microorganisms, terrestrial plants, etc., sourced from both our laboratory and existing literature. We applied the SSD method to estimate the hazardous concentration of Cr for HC5 and ultimately established a predictive model according to HC5 and different soil properties. As a result, the EC10 (an effective concentration of Cr resulting in 10% suppression of terminal biological activity) based on 7 different soils and 4 endpoints ranged from 16.8 to 148.0 mg kg−1, and the hormesis of Cr induction reached up to 109%. Overall, the toxicity (EC10) to microorganisms was much lower, while it was higher for graminoids. All the toxicity data were corrected through an aging factor with up to 540 days of equilibration before fitting the SSD curves. After that, a prediction model considering HC5 values and soil properties was established as LogHC5 = 3.003LogpH +0.651LogOC +0.013LogCEC - 0.476. The model was well-verified in field experiments, as the actual and predicted values fell within a 2-fold error range. This approach offers a rigorous scientific foundation for determining the Cr ecological risk threshold and could be important for the conservation of ecological species in soils.

Review and Evaluate the Bioinformatics Analysis Strategies of ATAC-seq and CUT&Tag Data.

Efficient and reliable profiling methods are essential to study epigenetics. Tn5, one of the first identified prokaryotic transposases with high DNA-binding and tagmentation efficiency, is widely adopted in different genomic and epigenomic protocols for high-throughputly exploring the genome and epigenome. Based on Tn5, the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and the Cleavage Under Targets and Tagmentation (CUT&Tag) were developed to measure chromatin accessibility and detect DNA-protein interactions. These methodologies can be applied to large amounts of biological samples with low-input levels, such as rare tissues, embryos, and sorted single cells. However, fast and proper processing of these epigenomic data has become a bottleneck because massive data production continues to increase quickly. Furthermore, inappropriate data analysis can generate biased or misleading conclusions. Therefore, it is essential to evaluate the performance of Tn5-based ATAC-seq and CUT&Tag data processing bioinformatics tools, many of which were developed mostly for analyzing chromatin immunoprecipitation followed by sequencing (ChIP-seq) data. Here, we conducted a comprehensive benchmarking analysis to evaluate the performance of eight popular software for processing ATAC-seq and CUT&Tag data. We compared the sensitivity, specificity, and peak width distribution for both narrow-type and broad-type peak calling. We also tested the influence of the availability of control IgG input in CUT&Tag data analysis. Finally, we evaluated the differential analysis strategies commonly used for analyzing the CUT&Tag data. Our study provided comprehensive guidance for selecting bioinformatics tools and recommended analysis strategies, which were implemented into Docker/Singularity images for streamlined data analysis.

Trace elements and heavy metal(loid)s triggering ecological risks in a heavily polluted river-reservoir system of central Mexico: Probabilistic approaches

The contamination of trace elements and heavy metal(loid)s in water bodies has emerged as a global environmental concern due to their high toxicity at low concentrations to both biota and humans. This study aimed to evaluate the ecological risk associated with the occurrence and spatial distribution of Mn, Fe, Co, Cd, Ni, Zn, Sb, As, Tl, Cu, Pb, U, and V in the heavily polluted waters of an important river-reservoir system (Atoyac River Basin) in central Mexico, using two-level tired probabilistic approaches: Risk Quotient based on Species Sensitivity Distribution (RQSSD) and Joint Probability Curves (JPCs). The concentrations of these elements varied widely, ranging from 0.055 μg L−1 to 9200 μg L−1 and from 0.056 μg L−1 to 660 μg L−1, in both total and dissolved fractions, respectively. Although geogenic and anthropogenic sources contribute to the presence of these elements in waters, the discharge of untreated or poorly treated industrial wastewater is the main source of contamination. In this regard, the RQSSD results indicated high ecological risk for Mn, Fe, Co, Ni, Zn, and Sb, and medium or low ecological risk for As, Tl, U, and V at almost all sampling sites. The highest RQSSD values were found downstream of a large industrial corridor for Co, Zn, Tl, Pb, and V, with Tl, Pb, and V escalating to higher risk levels, highlighting the negative impact of industrial contamination on biota. The JPC results for these elements are consistent with the RQSSD approach, indicating an ecological risk to species from Mn, Fe, Co, Ni, Zn, and Sb in waters of the Atoyac River Basin. Therefore, the results of this study offer a thorough assessment of pollution risk, providing valuable insights for legislators on managing and mitigating exposure.

Assessing ecological responses of exposure to the pyrethroid insecticide lambda-cyhalothrin in sub-tropical freshwater ecosystems

Pyrethroid insecticides are widely detected in aquatic ecosystems due to their extensive use in agriculture and horticulture, which could pose a potential risk to aquatic non-target organisms. While previous ecotoxicological studies have been conducted mainly with standard tests and local species under temperate conditions, scarce information is available on the effects of pyrethroid insecticides on communities and ecosystems under (sub-)tropical conditions. A single application of lambda-cyhalothrin at concentrations of 0, 9, 30, and 100 ng/L was evaluated in outdoor mesocosms under sub-tropical conditions. Lambda-cyhalothrin was found to dissipate rapidly in the water column, with only 11 % and 7 % of the remaining dose measured at 1 and 3 days after application, respectively. Lambda-cyhalothrin concentrations disappeared considerably faster from the water compartment compared to temperate conditions. Consistent decreases in abundance were observed for Lecane lunaris at the medium and higher treatments (NOEC = 9 ng/L) and at the highest treatment (NOEC = 30 ng/L) for Keratella tropica. On the contrary, two taxa belonging to Cladocera (i.e., Ceriodaphnia sp. and Diaphanosoma sp.) showed the most prominent increase in abundance related to the lambda-cyhalothrin treatments. At the community level, a consistent no observed effect concentrations (NOECs) of 9 ng/L could be calculated for the zooplankton community. A marginal significant overall treatment related effect was observed for the macroinvertebrate community. The results of species sensitivity distribution (SSD) analysis based on results of acute toxicity experiments conducted alongside the mesocosm experiment and obtained from the literature indicated that macroinvertebrates from temperate regions may be generally more sensitive than their counterparts in (sub-)tropical regions. Overall, these findings suggest that environmentally relevant concentrations of the pyrethroid insecticide lambda-cyhalothrin may lead to different ecological outcomes in freshwater ecosystems in the (sub-)tropics relative to temperate regions.