Species Sensitivity Distribution Research Articles

Which distribution to choose for deriving a species sensitivity distribution? Implications from analysis of acute and chronic ecotoxicity data

Species sensitivity distributions (SSDs) estimated by fitting a statistical distribution to ecotoxicity data are indispensable tools used to derive the hazardous concentration for 5 % of species (HC5) and thereby a predicted no-effect concentration in environmental risk assessment. Whereas various statistical distributions are available for SSD estimation, the fundamental question of which statistical distribution should be used has received limited systematic analysis. We aimed to address this knowledge gap by applying four frequently used statistical distributions (log-normal, log-logistic, Burr type III, and Weibull distributions) to acute and chronic SSD estimation using aquatic toxicity data for 191 and 31 chemicals, respectively. Based on the differences in the corrected Akaike’s information criterion (AICc) as well as visual inspection of the fitting of the lower tails of SSD curves, the log-normal SSD was generally better or equally good for the majority of chemicals examined. Together with the fact that the ratios of HC5 values of other alternative SSDs to those of log-normal SSDs generally fell within the range 0.1–10, our findings indicate that the log-normal distribution can be a reasonable first candidate for SSD derivation, which does not contest the existing widespread use of log-normal SSDs.

Deriving ecological risk thresholds for soil molybdenum in China based on interspecies correlation estimation and quantitative ion character–activity relationship models

Soil molybdenum (Mo) levels can reach ecologically hazardous levels. China has not yet established the relevant thresholds, posing challenges for environmental management. Therefore, we present our data relevant to Mo toxicity for several important species. By normalizing soil properties, we obtained a correlation model of Mo toxicity to Hordeum vulgare, as well as 31 models for the toxicity of other elements including Cu and Ni to invertebrates and microbial processes. Using interspecies correlation estimation (ICE) extrapolation, the sensitivity coefficient (0.12–0.71) for five plants were found. For invertebrates and microbial processes lacking Mo data, we used regression analysis to establish Mo toxicity models based on the soil quantitative ion character–activity relationships (s–QICAR; R2 =0.70–0.95) and known toxicities of other metal elements to invertebrate and microbial processes. Furthermore, combining species sensitivity distribution calculations, the HC5 values for protecting 95% of soil species from Mo in three typical soil scenarios in China were calculated. After correction, the predicted no-effect concentrations were 6.8, 4.8, and 3.4 mg/kg, respectively. This study innovatively combined ICE and s − QICAR to derive soil Mo thresholds. Our results can provide a basis for decision-making in the assessment and management of soil Mo pollution.

Arsenic and fluoride in groundwater triggering a high risk: Probabilistic results using Monte Carlo Simulation and Species Sensitivity Distribution

The widespread presence of arsenic (As) and fluoride (F-) in groundwater poses substantial risks to human health on a global scale. These elements have been identified as the most prevalent geogenic contaminants in groundwater in northern Mexico. Consequently, this study aimed to evaluate the human health and ecological risks associated with the content of As and F- in the Meoqui-Delicias aquifer, which is in one of Mexico's most emblematic irrigation districts. Concentrations of As and F- were measured in 38 groundwater samples using ICP-MS and ion chromatography, respectively. Overall, these elements showed a similar trend across the aquifer, revealing a positive correlation between them and pH. The concentration of As and F- in the groundwater ranged from 5.3 μg/L to 303 μg/L and from 0.5 mg/L to 8.8 mg/L, respectively. Additionally, the levels of As and F- surpassed the established national standards for safe drinking water in 92% and 97% of samples, respectively. Given that groundwater is used for both agricultural purposes and human activities, this study also assessed the associated human health and ecological risks posed by these elements using Monte Carlo simulation and Species Sensitivity Distribution. The findings disclosed a significant noncarcinogenic health risk associated with exposure to As and F-, as well as an unacceptable carcinogenic health risk to As through water consumption for both adults and children. Furthermore, a high ecological risk to aquatic species was identified for F- and high to medium risks for As in the sampling sites. Therefore, the findings in this study provide valuable information for Mexican authorities and international organizations (e.g., WHO) about the adverse effects that any exposure without treatment to groundwater from this region represents for human health.

Determination Procedure of Ecotoxicologically Acceptable Cu Concentration in River Considering the Change of Environmental Factors

Objectives : In this study, considering the changes in the concentration of metal/metalloid and environmental factors over time of the target water system and the toxic effects of metals on various aquatic organisms, determined procedure of ecotoxicologically acceptable metal/metalloid concentration based on a biotic ligand model (BLM) was proposed in detail. As an application example, the ecotoxicologically acceptable Cu concentration for the Numedalslågen river in Norway was calculated.Methods : The Cu concentration and environmental factor time series data of the target water system were collected, and EC50[Cu]<sub>T</sub>, the total concentration of Cu in the water system showing a toxic effect of 50% on the target aquatic organisms, was calculated through BLM. In addition, the predicted no-effect concentration (PNEC) was obtained from the species sensitivity distribution using the acute-chronic ratio and adjustment factor, and the ecotoxicologically acceptable Cu concentration of the target water system was determined through the fixed monitoring benchmark (FMB).Results and Discussion : Ecotoxicologically acceptable Cu concentration of the target water system was determined as 1.15 μg/L. Dissolved organic carbon (DOC) showed the highest linear relationship with EC50[Cu]<sub>T</sub> (R<sup>2</sup> = 0.94-0.98) compared to various environmental factors, and the Cu toxicity effect on aquatic organisms tended to decrease as the DOC concentration increased. Ca showed a low linear relationship with EC50[Cu]<sub>T</sub> (R<sup>2</sup> < 0.04), which is presumed to be due to the decrease in Ca<sup>2+</sup> concentration due to the complexese formation of DOC and Ca<sup>2+</sup>, which reduced the competitive effect with Cu<sup>2+</sup>.Conclusion : The proposed procedure provides a useful method for calculating ecotoxicologically acceptable metal concentrations for the protection of aquatic organisms in water systems. In addition, it is expected that it can be used to calculate site-specific metal concentrations that can protect aquatic organisms in the target water system by reflecting the timing of sediment resuspension, which can cause rapid changes in the concentration of metals and environmental factors in the water system, and specific time points such as storm and flood seasons.

Different Sensitivity of Flower-Visiting Diptera to a Neonicotinoid Insecticide: Expanding the Base for a Multiple-Species Risk Assessment Approach

Insects play an essential role as pollinators of wild flowers and crops. At the same time, pollinators in agricultural environments are commonly exposed to pesticides, compromising their survival and the provision of pollination services. Although pollinators include a wide range of species from several insect orders, information on pesticide sensitivity is mostly restricted to bees. In addition, the disparity of methodological procedures used for different insect groups hinders the comparison of toxicity data between bees and other pollinators. Dipterans are a highly diverse insect order that includes some important pollinators. Therefore, in this study, we assessed the sensitivity of two hoverflies (Sphaerophoria rueppellii, Eristalinus aeneus) and one tachinid fly (Exorista larvarum) to a neonicotinoid insecticide (Confidor®, imidacloprid) following a comparative approach. We adapted the standardized methodology of acute contact exposure in honey bees to build dose–response curves and calculate median lethal doses (LD50) for the three species. The methodology consisted in applying 1 µL of the test solution on the thorax of each insect. Sphaerophoria rueppelli was the most sensitive species (LD50 = 10.23 ng/insect), and E. aeneus (LD50 = 18,176 ng/insect) the least. We then compared our results with those available in the literature for other pollinator species using species sensitivity distribution (SSD). Based on the SSD curve, the 95th percentile of pollinator species would be protected by a safety factor of 100 times the Apis mellifera endpoint. Overall, dipterans were less sensitive to imidacloprid than most bee species. As opposed to most bee species, oviposition and fecundity of many dipteran species can be reliably assessed in the laboratory. We measured the number of eggs laid following exposure to different insecticide doses and assessed the potential trade-off between oviposition and survival through the sublethal sensitivity index (SSI). Exposure to imidacloprid had a significant effect on fecundity, and SSI values indicated that oviposition is a sensitive endpoint for the three dipteran species tested. Future studies should integrate this information related to population dynamics in simulation models for environmental risk assessment.

A Chronic Aquatic Hazard Assessment for the Perfume Raw Material Octahydro-tetramethyl-naphthalenyl-ethanone.

Octahydro-tetramethyl-naphthalenyl-ethanone (OTNE) is a high-production volume fragrance material used in various down-the-drain consumer products. To assess aquatic risk, the Research Institute for Fragrance Materials (RIFM) uses a tiered data-driven framework to determine a risk characterization ratio, where the ratio of the predicted-environmental concentration to the predicted-no-effect concentration (PNEC) of <1 indicates an acceptable level of risk. Owing to its high production volume and the conservative nature of the RIFM framework, RIFM identified the need to utilize a species sensitivity distribution (SSD) approach to reduce the PNEC uncertainty for OTNE. Adding to the existing Daphnia magna, Danio rerio, and Desmodesmus subspicatus chronic studies, eight new chronic toxicity studies were conducted on the following species: Navicula pelliculosa, Chironomus riparius, Lemna gibba, Ceriodaphnia dubia, Hyalella azteca, Pimephales promelas, Anabaena flos-aquae, and Daphnia pulex. All toxicity data were summarized as chronic 10% effect concentration estimates using the most sensitive biological response. Daphnia magna was the most sensitive (0.032 mg/L), and D. subspicatus was the least sensitive (>2.6 mg/L, the OTNE solubility limit). The 5th percentile hazardous concentration (HC5) derived from the cumulative probability distribution of the chronic toxicity values for the 11 species was determined to be 0.0498 mg/L (95% confidence interval 0.0097-0.1159 mg/L). A series of "leave-one-out" and "add-one-in" simulations indicated the SSD was stable and robust. Add-one-in simulations determined that the probability of finding a species sensitive enough to lower the HC5 two- or threefold was 1/504 and 1/15,300, respectively. Given the high statistical confidence in this robust SSD, an additional application factor protection is likely not necessary. Nevertheless, to further ensure the protection of the environment, an application factor of 2 to the HC5, resulting in a PNEC of 0.0249 mg/L, is recommended. When combined with environmental exposure information, the overall hazard assessment is suitable for a probabilistic environmental risk assessment. Environ Toxicol Chem 2024;00:1-12. © 2024 SETAC.

Emerging Contaminants in the Effluent of Wastewater Should Be Regulated: Which and to What Extent?

Effluent discharged from urban wastewater treatment plants (WWTPs) is a major source of emerging contaminants (ECs) requiring effective regulation. To this end, we collected discharge datasets of pharmaceuticals (PHACs) and endocrine-disrupting chemicals (EDCs), representing two primary categories of ECs, from Chinese WWTP effluent from 2012 to 2022 to establish an exposure database. Moreover, high-risk ECs’ long-term water quality criteria (LWQC) were derived using the species sensitivity distribution (SSD) method. A total of 140 ECs (124 PHACs and 16 EDCs) were identified, with concentrations ranging from N.D. (not detected) to 706 μg/L. Most data were concentrated in coastal regions and Gansu, with high ecological risk observed in Gansu, Hebei, Shandong, Guangdong, and Hong Kong. Using the assessment factor (AF) method, 18 high-risk ECs requiring regulation were identified. However, only three of them, namely carbamazepine, ibuprofen, and bisphenol-A, met the derivation requirements of the SSD method. The LWQC for these three ECs were determined as 96.4, 1010, and 288 ng/L, respectively. Exposure data for carbamazepine and bisphenol-A surpassed their derived LWQC, indicating a need for heightened attention to these contaminants. This study elucidates the occurrence and risks of ECs in Chinese WWTPs and provides theoretical and data foundations for EC management in urban sewage facilities.

Spatiotemporal variation, fluxes and risk evaluation of neonicotinoid insecticides within the midsection of Yangtze River, China: An exploration as ecological protection threshold

Neonicotinoid insecticides (NNIs) have attracted global concern due to its extensive use in agricultural activities and their potential risks to the animal and human health, however, there is limited knowledge on the regional traits and ecological risks of NNIs in the aquatic environments. We herein investigated the occurrence of NNIs within the midsection of Yangtze River in China, offering the inaugural comprehensive report on NNIs within this region. In this study, eleven NNIs were analyzed in 108 river water and sediment samples from three seasons (normal, dry and wet season). We detected a minimum of seven NNIs in the water and four NNIs in the sediment, with total concentrations ranging from 12.33 to 100.5 ng/L in water and 0.08–5.68 ng/g in sediment. The levels of NNIs in both river water and sediment were primarily influenced by the extent of agricultural activities. The estimated annual load of NNIs within the midsection of Yangtze River totaled 40.27 tons, April was a critical contamination period. Relative potency factor (RPF) analysis of the human exposure risk revealed that infants faced the greatest exposure risk, with an estimated daily intake of 11.27 ng kg−1∙bw∙d−1. We established the acute and chronic thresholds for aquatic organisms by employing the Species Sensitive Distribution (SSD) method (acute: 384.1 ng/L; chronic: 168.9 ng/L). Based on the findings from this study, 33% of the river water samples exceeded the chronic ecological risks thresholds, indicating the urgent need for intervention programs to guarantee the safety of the river for aquatic life in the Yangtze River Basin.

Evaluation of the ecological risk of pesticide residues from the European LUCAS Soil monitoring 2018 survey.

The 2018 LUCAS (Land Use and Coverage Area frame Survey) Soil Pesticides survey provides a European Union (EU)-scale assessment of 118 pesticide residues in more than 3473 soil sites. This study responds to the policy need to develop risk-based indicators for pesticides in the environment. Two mixture risk indicators are presented for soil based, respectively, on the lowest and the median of available No Observed Effect Concentration (NOECsoil,min and NOECsoil,50) from publicly available toxicity datasets. Two further indicators were developed based on the corresponding equilibrium concentration in the aqueous phase and aquatic toxicity data, which are available as species sensitivity distributions. Pesticides were quantified in 74.5% of the sites. The mixture risk indicator based on the NOECsoil,min exceeds 1 in 14% of the sites and 0.1 in 23%. The insecticides imidacloprid and chlorpyrifos and the fungicide epoxiconazole are the largest contributors to the overall risk. At each site, one or a few substances drive mixture risk. Modes of actions most likely associated with mixture effects include modulation of acetylcholine metabolism (neonicotinoids and organophosphate substances) and sterol biosynthesis inhibition (triazole fungicides). Several pesticides driving the risk have been phased out since 2018. Following LUCAS surveys will determine the effectiveness of substance-specific risk management and the overall progress toward risk reduction targets established by EU and UN policies. Newly generated data and knowledge will stimulate needed future research on pesticides, soil health, and biodiversity protection. Integr Environ Assess Manag 2024;00:1-15. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Occurrence, distribution, and ecological risk assessment of heavy metals in Chao Phraya River, Thailand

Understanding heavy metals in rivers is crucial, as their presence and distribution impact water quality, ecosystem health, and human well-being. This study examined the presence and levels of nine heavy metals (Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn) in 16 surface water samples along the Chao Phraya River, identifying Fe, Mn, Zn, and Cr as predominant metals. Although average concentrations in both rainy and dry seasons generally adhered to WHO guidelines, Mn exceeded these limits yet remained within Thailand’s acceptable standards. Seasonal variations were observed in the Chao Phraya River, and Spearman’s correlation coefficient analysis established significant associations between season and concentrations of heavy metals. The water quality index (WQI) demonstrated varied water quality statuses at each sampling point along the Chao Phraya River, indicating poor conditions during the rainy season, further deteriorating to very poor conditions in the dry season. The hazard potential index (HPI) was employed to assess heavy metal contamination, revealing that during the dry season in the estuary area, the HPI value exceeded the critical threshold index, indicating the presence of heavy metal pollution in the water and unsuitable for consumption. Using the species sensitivity distribution model, an ecological risk assessment ranked the heavy metals’ HC5 values as Pb > Zn > Cr > Cu > Hg > Cd > Ni, identifying nickel as the most detrimental and lead as the least toxic. Despite Cr and Zn showing a moderate risk, and Cu and Ni posing a high risk to aquatic organisms, the main contributors to ecological risk were identified as Cu, Ni, and Zn, suggesting a significant potential ecological risk in the Chao Phraya River’s surface water. The results of this study provide fundamental insights that can direct future actions in preventing and managing heavy metal pollution in the river ecosystem.

Predictive modeling of methylmercury in rice (Oryza sativa L.) and species-sensitivity-distribution-based derivation of the threshold of soil mercury in karst mountain areas.

The bioavailable mercury (Hg) in the soil is highly active and can affect the formulation of methyl-Hg (MeHg) in soil and its accumulation in rice. Herein, we predicted the concentration of MeHg in rice using bioavailable Hg extracted from soils; additionally, we determined the threshold value of soil Hg in karst mountain areas based on species sensitivity distribution. The bioavailable Hg was extracted using calcium chloride, hydrochloric acid (HCl), diethylenetriaminepentaacetic acid mixture, ammonium acetate, and thioglycolic acid. Results showed that HCl is the best extractant, and the prediction model demonstrated good predictability of the MeHg concentration in rice based on the HCl-extractable Hg, pH, and soil organic matter (SOM) data. Compared with the actual MeHg concentration in rice, approximately 99% of the predicted values (n = 103) were within the 95% prediction range, indicating the good performance of the rice MeHg prediction model based on soil pH, SOM, and bioavailable Hg in karst mountain areas. Based on this MeHg prediction model, the safety threshold of soil Hg was calculated to be 0.0936mg/kg, which is much lower than the soil pollution risk screening value of agricultural land (0.5mg/kg), suggesting that a stricter standard should be applied regarding soil Hg in karst mountain areas. This study presents the threshold of soil Hg pollution for rice safety in karst mountain areas, and future studies should target this threshold range.

Ecological risk assessment of heavy metals in desulfurized seawater discharged from a coal-fired power plant in Qingdao.

Despite the prevalence of discharge of large volumes of heavy-metal-bearing seawater from coal-fired power plants into adjacent seas, studies on the associated ecological risks remain limited. This study continuously monitored concentrations of seven heavy metals (i.e. As, Cd, Cr, Cu, Hg, Pb, and Zn) in surface seawater near the outfall of a coal-fired power plant in Qingdao, China over three years. The results showed average concentrations of As, Cd, Cr, Cu, Hg, Pb, and Zn of 2.63, 0.33, 2.97, 4.63, 0.008, 0.85, and 25.00 μg/L, respectively. Given the lack of data on metal toxicity to local species, this study investigated species composition and biomass near discharge outfalls and constructed species sensitivity distribution (SSD) curves with biological flora characteristics. Hazardous concentrations for 5% of species (HC5) for As, Cd, Cr, Cu, Hg, Pb, and Zn derived from SSDs constructed from chronic toxicity data for native species were 3.23, 2.22, 0.06, 2.83, 0.66, 4.70, and 11.07 μg/L, respectively. This study further assessed ecological risk of heavy metals by applying the Hazard Quotient (HQ) and Joint Probability Curve (JPC) based on long-term heavy metal exposure data and chronic toxicity data for local species. The results revealed acceptable levels of ecological risk for As, Cd, Hg, and Pb, but unacceptable levels for Cr, Cu, and Zn. The order of studied heavy metals in terms of ecological risk was Cr > Cu ≈ Zn > As > Cd ≈ Pb > Hg. The results of this study can guide the assessment of ecological risk at heavy metal contaminated sites characterized by relatively low heavy metal concentrations and high discharge volumes, such as receiving waters of coal-fired power plant effluents.

Climate warming shifts riverine macroinvertebrate communities to be more sensitive to chemical pollutants.

Freshwaters are highly threatened ecosystems that are vulnerable to chemical pollution and climate change. Freshwater taxa vary in their sensitivity to chemicals and changes in species composition can potentially affect the sensitivity of assemblages to chemical exposure. Here we explore the potential consequences of future climate change on the composition and sensitivity of freshwater macroinvertebrate assemblages to chemical stressors using the UK as a case study. Macroinvertebrate assemblages under end of century (2080-2100) and baseline (1980-2000) climate conditions were predicted for 608 UK sites for four climate scenarios corresponding to mean temperature changes of 1.28 to 3.78°C. Freshwater macroinvertebrate toxicity data were collated for 19 chemicals and the hierarchical species sensitivity distribution model was used to predict the sensitivity of untested taxa using relatedness within a Bayesian approach. All four future climate scenarios shifted assemblage compositions, increasing the prevalence of Mollusca, Crustacea and Oligochaeta species, and the insect taxa of Odonata, Chironomidae, and Baetidae species. Contrastingly, decreases were projected for Plecoptera, Ephemeroptera (except for Baetidae) and Coleoptera species. Shifts in taxonomic composition were associated with changes in the percentage of species at risk from chemical exposure. For the 3.78°C climate scenario, 76% of all assemblages became more sensitive to chemicals and for 18 of the 19 chemicals, the percentage of species at risk increased. Climate warming-induced increases in sensitivity were greatest for assemblages exposed to metals and were dependent on baseline assemblage composition, which varied spatially. Climate warming is predicted to result in changes in the use, environmental exposure and toxicity of chemicals. Here we show that, even in the absence of these climate-chemical interactions, shifts in species composition due to climate warming will increase chemical risk and that the impact of chemical pollution on freshwater macroinvertebrate biodiversity may double or quadruple by the end of the 21st century.

Determining soil conservation strategies: Ecological risk thresholds of arsenic and the influence of soil properties

The establishment of ecological risk thresholds for arsenic (As) plays a pivotal role in developing soil conservation strategies. However, despite many studies regarding the toxicological profile of As, such thresholds varying by diverse soil properties have rarely been established. This study aims to address this gap by compiling and critically examining an extensive dataset of As toxicity data sourced from existing literature. Furthermore, to augment the existing information, experimental studies on As toxicity focusing on barley-root elongation were carried out across various soil types. The As concentrations varied from 12.01 to 437.25 mg/kg for the effective concentrations that inhibited 10% of barley-root growth (EC10). The present study applied a machine-learning approach to investigate the complex associations between the toxicity thresholds of As and diverse soil properties. The results revealed that Mn-/Fe-ox and clay content emerged as the most influential factors in predicting the EC10 contribution. Additionally, by using a species sensitivity distribution model and toxicity data from 21 different species, the hazardous concentration for x% of species (HCx) was calculated for four representative soil scenarios. The HC5 values for acidic, neutral, alkaline, and alkaline calcareous soils were 80, 47, 40, and 28 mg/kg, respectively. This study establishes an evidence-based methodology for deriving soil-specific guidance concerning As toxicity thresholds.

Machine learning-based models to predict aquatic ecological risk for engineered nanoparticles: using hazard concentration for 5% of species as an endpoint.

Assessment and prediction for the ecotoxicity of engineered nanoparticles (ENPs) at the community or ecosystem levels represents a critical step toward a comprehensive understanding of the ecological risks of ENPs. Current studies on predicting the ecotoxicity of ENPs primarily focus on the cellular and individual levels, with limited exploration at the community or ecosystem levels. Herein, we present the first of the reports for the direct prediction of aquatic ecological risk for ENPs at the community level using machine learning (ML) approaches in the field of computational toxicology. Specifically, we extensively collected the threshold concentrations of twelve ENPs including metal- and carbon-based nanoparticles for aquatic species, i.e., hazardous concentrations at which 5% of species are harmed (HC5), established by a species sensitivity distribution. Afterwards, we used eight supervised ML methods including Adaboost, artificial neural network, C4.5 decision tree, K-nearest neighbor, logistic regression, Naive Bayes, random forest, and support vector machine to develop nine classification models and four regression models, respectively, for the qualitative and quantitative prediction of HC5. The evaluation of model performance yielded the internal validation accuracy of all classification models ranging from 71.4 to 100%, and the determination coefficient of regression models ranging from 0.702 to 0.999, indicating that the developed models showed good performance. By using a cross-validation method and an application domain characterization, the selected models were further validated to have powerful predictive ability. Furthermore, the incorporation of three nanostructural descriptors (metal oxide sublimation enthalpy, zeta potential, and specific surface area) linked to toxicity mechanisms (the release of metal ions, the stability of dispersions of particles in aqueous suspensions, and the surface properties of the material) effectively enhanced the prediction power and mechanistic interpretability of the selected models. These findings would not only be beneficial in the screening of ENPs with potential high ecological risks that need to be tested as a priority but also contribute to the development of environmental regulations and standards for ENPs.

Exploring honey bee toxicological data as a proxy for assessing dimethoate sensitivity in stingless bees

The high diversity and distinctive characteristics of stingless bees pose challenges in utilizing toxicity test results for agrochemical registrations. Toxicity assessments were performed on 15 stingless bee species, along with the honey bee, using the insecticide dimethoate, following adapted OECD protocols. Median lethal doses over 24 h (24 h-LD50) were determined for exposure routes (acute oral or contact) and species. Species sensitivity distribution (SSD) curves were constructed and the 5% hazard doses (HD5) were estimated based on 24 h-LD50 values. The SSD curve was adjusted as the body weight and dimethoate response were correlated. Lighter bees (<10 mg) had lower 24 h-LD50 values. Contact exposure for adjusted HD5 suggested insufficient protection for Melipona mondury, whereas the oral exposure HD5 indicated no risks for the other 14 species. Comprehensive risk assessments are crucial for understanding the agrochemical impact on stingless bees, emphasizing the need for a broader species range in formulating conservation strategies.

Aquatic and sediment ecotoxicity data of difenoconazole and its potential environmental risks in ponds bordering rice paddies

Difenoconazole has a widespread agricultural use to control fungal diseases in crops, including rice. In edge-of-field surface waters the residues of this lipophilic fungicide may be toxic to both pelagic and benthic organisms. To allow an effect assessment we mined the regulatory and open literature for aquatic toxicity data. Since published sediment toxicity data were scarce we conducted 28 d sediment-spiked toxicity test with 8 species of benthic macroinvertebrates. Ecotoxicological threshold levels for effects were assessed by applying the species sensitivity distribution approach. Based on short-term L(E)C50’s for aquatic organisms from water-only tests an acute Hazardous Concentration to 5% of the species (HC5) of 100 µg difenoconazole/L was obtained, while the HC5 based on chronic NOEC values was a factor of 104 lower (0.96 µg difenoconazole/L). For benthic macroinvertebrates the chronic HC5, based on 28d-L(E)C10 values, was 0.82 mg difenoconazole/kg dry weight sediment. To allow a risk assessment for water- and sediment-dwelling organisms, exposure concentrations were predicted for the water and sediment compartment of an edge-of-field pond bordering rice paddies treated with difenoconazole using the Chinese Top-Rice modelling approach, the Chinese Nanchang exposure scenario and the Equilibrium Partitioning theory. It appeared that in the vast majority of the 20 climate years simulated, potential risks to aquatic and sediment organisms cannot be excluded. Although the HC5 values based on laboratory toxicity data provide one line of evidence only, our evaluation suggests population- and community-level effects on these organisms due to chronic risks in particular.

Neonicotinoids Persisting in the Sea Pose a Potential Chronic Risk to Marine Organisms: A Case from Xiangshan Bay, China (2015-2019).

Neonicotinoid insecticides (neonics) are extensively employed in agriculture and pervade various environmental matrices. However, few studies have documented the occurrence and potential chronic ecological risks of these chemicals in the marine environment. We collected 720 seawater samples from Xiangshan Bay during 2015-2019 and the integrated concentrations of seven neonics were determined using the relative potency factor method. Trend analyses using the Mann-Kendall test in time series, along with the estimation of the flux of neonics into the sea, were conducted. At last, the ecological risk of neonics was evaluated by water quality criteria derivation based on species sensitivity distribution. Our findings revealed that 47.6% of samples contained at least one neonic, with the integrated concentration of neonics ranging from 63.30 to 1684.14 ng/L. Imidacloprid and dinotefuran exhibited the highest frequency of detection in the analysis. The significance level of the Mann-Kendall test ranged from 2.16 × 10-10 to 1.21 × 10-5 (S > 0), indicating all neonics behaved with sharply increasing trends. Approximately 8.47 × 10-2 tons of neonics were discharged into Xiangshan Bay. Notably, the integrated concentrations of neonics represented a potential chronic ecological risk to marine organisms. This study provided novel insights into the spatial distribution, source, and migration of neonic species and their impacts on marine ecosystems.

Reciprocal Effects of Metal Mixtures on Phytoplankton

Several types of contaminants are anthropogenically introduced into natural aquatic ecosystems and interact with other chemicals and/or with living organisms. Although metal toxicity alone has been relatively well studied, the toxic metal ion effects in the mixture have been thoroughly studied only during the last decades. This review focuses on the published reciprocal effects of different metals on different species of algae, together with describing their toxic effects on studied parameters. Phytoplankton as a bioindicator can help to estimate the reciprocal metal risk factor. Many methodologies have been developed and explored, such as the biotic ligand model (BLM), concentration addition (CA), independent action (IA), sensitivity distribution of EC50 species sensitivity distribution (SSD curves), and others, to study reciprocal metal toxicity and provide promising results, which are briefly mentioned too. From our review, we can commonly conclude the following: Zn acted antagonistically with most heavy metals (Al, Cu, Cd, and Ni). The Cu interaction with Cd, Fe, and Pb was mostly antagonistic. Cd showed synergistic behaviour with Hg, Cu, Zn, and Pb and antagonistic behaviour with Co and Fe in many cases. Methods and techniques need to be developed and optimised to determine reciprocal metal toxicity so that the ecotoxicological predictions made by using phytoplankton can be more accurate and related to real-time toxic metals risks to the aquatic ecosystem. This is the main objective of ecotoxicological tests for risk assessment. Understanding how metals enter algal cells and organelles can help to solve this challenge and was one of the main parts of the review.

Distribution characteristics and ecological risk assessment of microplastics in intertidal sediments near coastal water

Plastic products are widely distributed worldwide and continue to have a negative impact on the environment and organisms. Intertidal regions, which interface between upland and marine ecosystems, are regions of high ecological importance and serve as repositories for a variety of plastic wastes. However, ecological risk assessments of microplastics (MPs) in these transitional environments are still scarce. In this study, the morphological characteristics and spatial distribution of MPs in the intertidal surface sediments of Haizhou Bay were analyzed, and an ecological risk assessment framework for MPs was developed. Overall, the average abundance of MPs in the sediments was 2.31 ± 1.35 pieces/g dw. The size of the MPs was mainly less than 1 mm, and the main shape, color and polymer type of the MPs were mainly fibrous (58%), blue (30%), and PVC (22%), respectively. Cluster analyses showed that the sites could be well distinguished by size and polymer type but not by MP shape and color. According to the hazard scores, most of the sites in this area belonged to a risk level of IV, while the pollution loading index (PLI) showed that most of the sites belonged to a risk level of II. The ecological toxicity risk from the species–sensitive distribution (SSD) model showed that one–third of the sites had ecological MPs toxicity risks to marine organisms. We believe that normalized and standardized assessment methods should be implemented to monitor and manage the risk of MPs in the intertidal sediments. Particularly, the multiple dimensions, standard abundance of MPs, as well as MPs ingestion in the intertidal organisms, should be fully considered in the next step.