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Species sensitivity distributions (SSDs) play an important role in ecological risk assessment. Estimating SSDs requires toxicity data for many species, but reports on saltwater species are often limited compared to freshwater species. This limitation can constrain informed management of saltwater quality for the protection of marine ecosystems. We investigated the relationships between the parameters (i.e., mean and standard deviation [SD]) of freshwater and saltwater log‐normal SSDs to determine how accurately saltwater toxicity could be estimated from freshwater toxicity test data. We estimated freshwater and saltwater SSDs for 104 chemicals with reported acute toxicity data for five or more species and compared their means, SDs, and hazardous concentrations for 5% of the species (HC5) derived from the acute SSDs. Standard major axis regression analyses generally showed that log–log relationships between freshwater and saltwater SSD means, SDs, and HC5 values were nearly 1:1. In addition, the ratios of freshwater‐to‐saltwater SSD means and HC5 values for most of the 104 chemicals fell within the range 0.1–10. Although such a strong correlation was not observed for SSD SDs (r2 < 0.5), differences between freshwater and saltwater SSD SDs were relatively small. These results indicate that saltwater acute SSDs can be reasonably estimated using freshwater acute SSDs. Because the differences of the means and SDs between freshwater and saltwater SSDs were larger when the number of test species used for SSD estimation was lower (i.e., five to seven species in the present study), obtaining toxicity data for an adequate number of species will be key to better approximation of a saltwater acute SSD from a freshwater acute SSD for a given chemical. Environ Toxicol Chem 2022;41:2021–2027. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. [ABSTRACT FROM AUTHOR]

Although the concept and modeling of metal bioavailability and toxicity have been well developed based largely on laboratory experiments with standard test species, additional evidence is required to demonstrate their applicability for macroinvertebrates typically found in natural lotic ecosystems. We conducted 10‐day stream mesocosm experiments to test the hypothesis that increased water hardness (in the present study, the calcium [Ca] concentration was increased by adding CaCl2) would mitigate the effects of copper (Cu) on natural benthic macroinvertebrate communities. Exposure of macroinvertebrate communities to 25 μg/L Cu for 10 days in stream mesocosm experiments resulted in significant decreases in total abundance, in number of taxa, and in abundance of many macroinvertebrate taxa. However, the addition of Ca to stream mesocosms and the associated increase in water hardness up to 250 mg/L CaCO3 did not mitigate these effects of Cu on macroinvertebrate communities. The results showed that the hardness‐based water quality criteria for Cu of the US Environmental Protection Agency were not protective under the conditions of relatively high hardness, low alkalinity, and circumneutral pH. In contrast, the water quality criteria based on the biotic ligand model predicted little protective effects of Ca on Cu toxicity, which is consistent with our results. Additional experiments are required to understand the influence of modifying factors on the toxicity of metals to macroinvertebrate communities. Environ Toxicol Chem 2022;41:1304–1310. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. [ABSTRACT FROM AUTHOR]

Environmental contamination with nano‐ and microplastic (NMP) particles is an emerging global concern. The derivation of species sensitivity distributions (SSDs) is an essential step in estimating a hazardous concentration for 5% of the species (HC5), and this HC5 value is often used as a "safe" concentration in ecological risk assessment, that is, predicted‐no‐effect concentration. Although properties of plastics such as particle size can affect toxic effect concentrations, such influences have not yet been quantitatively considered in estimating SSDs for NMP particles. We illustrate a log‐normal SSD using chronic lowest‐observed‐effect concentrations (LOECs) of NMP particles from readily available toxicity data sets, considering the influence of particle size, polymer type, and freshwater or marine test media by adopting Bayesian hierarchical modeling techniques. Results of the hierarchical SSD modeling suggest that the SSD mean was negatively associated with particle size and was lower in marine media than in freshwater media. The posterior medians of the HC5 estimated from the LOEC‐based SSD varied by a factor of 10 depending on these factors (e.g., 1.8–20 μg/L for the particle size range of 0.1–5000 μm in the marine environment). Hierarchical SSD modeling allows us to clarify the influences of important factors such as NMP properties on effect concentrations, thereby helping to guide more relevant ecological risk assessments for NMP. Environ Toxicol Chem 2022;41:954–960. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. [ABSTRACT FROM AUTHOR]

Equilibrium partitioning (EqP) theory and spiked‐sediment toxicity tests are useful methods to develop sediment quality benchmarks. However, neither approach has been directly compared based on species sensitivity distributions (SSDs) to date. In the present study, we compared SSDs for 10 nonionic hydrophobic chemicals (e.g., pyrethroid insecticides, other insecticides, and polycyclic aromatic hydrocarbons) based on 10–14‐day spiked‐sediment toxicity test data with those based on EqP theory using acute water‐only tests. Because the exposure periods were different between the two tests, effective concentrations (i.e., median effective/lethal concentration) were corrected to compare SSDs. Accordingly, we found that hazardous concentrations for 50% and 5% of species (HC50 and HC5, respectively) differed by up to a factor of 100 and 129 between the two approaches, respectively. However, when five or more species were used for SSD estimation, their differences were reduced to a factor of 1.7 and 5.1 for HC50 and HC5, respectively, and the 95% confidence intervals of HC50 values overlapped considerably between the two approaches. These results suggest that when the number of test species is adequate, SSDs based on EqP theory and spiked‐sediment tests are comparable in sediment risk assessments. Environ Toxicol Chem 2022;41:462–473. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. [ABSTRACT FROM AUTHOR]

A medial collateral ligament (MCL) tear is common in cases of isolated injury or in those combined with anterior cruciate ligament injury. Although conservative treatment for an MCL tear is popular, some cases result in residual instability. Thus, the treatment approach of grade III MCL injury remains controversial. In this Technical Note, we present the technique of arthroscopic primary MCL repair with suture anchor. With this technique, proximal MCL injuries can be repaired with minimal invasion. This technique improves valgus stability and enables early rehabilitation, including range of motion and weight-bearing exercise. Video 1 Arthroscopic primary medial collateral ligament repair with suture anchor. Preoperative radiograph shows valgus instability. Preoperative magnetic resonance imaging shows a deep MCL and superficial MCL tear. Arthroscopy shows the drive-through sign and capsular tear at the medial femoral epicondyle. This video shows an arthroscopic MCL repair. The suture anchor is inserted though the medial epicondyle portal. A 20-G needle is penetrated in to the torn joint capsule and deep MCL. Suture relay is performed using the far-anteromedial portal. This technique is repeated. After suture relay, knot tying is performed. After knot tying, the torn capsule and deep MCL are repaired. (MCL, medial collateral ligament.) [ABSTRACT FROM AUTHOR]

Which biological groups (in the present study, periphyton, macroinvertebrates, and fishes) are surveyed is a fundamental question in environmental impact assessment programs in metal‐contaminated rivers. We performed a systematic review of 202 studies that investigated the ecological impacts of metal contamination on aquatic populations and communities in streams and rivers to examine 1) which biological groups were surveyed, 2) whether their responses were correlated with each other, and 3) which biological group was most responsive to changes in metal contamination level. In these studies, published from 1991 to 2015, benthic macroinvertebrates were most frequently chosen throughout the period (59–76% in different 5‐yr periods), followed by periphyton and fishes, and the number of studies that surveyed at least 2 or 3 biological groups was very limited (10%). Pearson's correlation coefficients calculated between the metrics of different biological groups were often low, emphasizing the importance of investigating multiple biological groups to better understand the responses of aquatic communities to metal contamination in running waters. Despite the limited data collected, our meta‐analysis showed that, in most cases, biological metrics based on macroinvertebrates were more responsive to changes in metal contamination level than those based on periphyton or fishes. This finding suggests that benthic macroinvertebrates could be a reasonable choice to detect the ecological impacts of metal contamination on a local scale. Environ Toxicol Chem 2020;39:1964–1972. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. [ABSTRACT FROM AUTHOR]

Strategies for deriving predicted environmental concentrations (PECs) using environmental exposure models have become increasingly important in the environmental risk assessment of chemical substances. However, many strategies are not fully developed owing to uncertainties in the derivation of PECs across spatially extensive areas. Here, we used 3‐year environmental monitoring data (river: 11 702 points; lake: 1867 points; sea: 12 points) on linear alkylbenzene sulfonate (LAS) in Japan to evaluate the ability of the National Institute of Advanced Industrial Science and Technology (AIST)‐Standardized Hydrology‐Based Assessment Tool for the Chemical Exposure Load (SHANEL) model developed to predict chemical concentrations in major Japanese rivers. The results indicate that the estimation ability of the AIST‐SHANEL model conforms more closely to the actual measured values in rivers than it does for lakes and seas (correlation coefficient: 0.46; proportion within the 10× factor range: 82%). In addition, the 95th percentile, 90th percentile, 50th percentile, and mean values of the distributions of the measured values (14 µg/L, 8.2 µg/L, 0.88 µg/L, and 3.4 µg/L, respectively) and estimated values (19 µg/L, 13 µg/L, 1.4 µg/L, and 4.2 µg/L, respectively) showed high concordance. The results suggest that AIST‐SHANEL may be useful in estimating summary statistics (e.g., 95th and 90th percentiles) of chemical concentrations in major rivers throughout Japan. Given its practical use and high accuracy, these environmental risk assessments are suitable for a wide range of regions and can be conducted using representative estimated values, such as the 95th percentile. Integr Environ Assess Manag 2019;15:750–759. © 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Key Points: The performance of an environmental exposure model, AIST–SHANEL, for estimating chemical concentration in rivers was evaluated using comprehensive measurement data from major rivers throughout Japan.The estimated spatiotemporal LAS concentrations, especially the 95th and 90th percentiles, were in good agreement with the measured concentrations.Using representative estimated values, e.g., 95th percentile, AIST–SHANEL can precisely estimate chemical concentrations in major rivers throughout Japan, and can contribute to high–accuracy environmental risk assessments. [ABSTRACT FROM AUTHOR]

Prediction of heavy metal bioavailability in intact soil is important to manage soil pollution risks. We developed a regression model for representative Japanese soils to judge their potential vulnerability to cadmium (Cd) pollution. We added four rates of Cd to 17 sample soils to mimic artificial contamination. After aging the contaminated soils, we measured Cd’s bioavailability using the diffusive gradients in thin-films (DGT) technique. We then evaluated the relationships between bioavailability of Cd ([CdDGT]) and intact soil properties by statistical analyses. Cation exchange capacity (CEC) and pH emerged as significant factors to explain the cadmium bioavailability in Japanese soils. Specifically, lower CEC and lower pH were associated with higher [CdDGT], which poses a higher risk for soil ecosystems. The correlation between pH and [CdDGT] had a high dependence on [CdAdd], whereas that for CEC did not. Regression analysis also showed that the interaction between intact soil pH and spiked concentration ([CdAdd]) had a significant contribution to [CdDGT]. The regression model developed was rationally supported by a biotic ligand model. This simplified but realistic model would be useful in estimating the vulnerability of representative Japanese soils and determining the risk for Japanese soils in relation to Cd contamination. [ABSTRACT FROM AUTHOR]

Abstract Predicting chemical mixture toxicity is an important issue for risk assessment. Loewe's concentration addition (CA) is a major model for predicting such toxicity. The CA is an additivity-based model, and if the results of toxicity test deviate from the CA prediction, it is considered that the toxic effect of the mixture is non-additive, and that "interaction" has played some role. In the present study, using as an example a biotic ligand model (BLM), which predicts metal toxicities, we theoretically investigated the toxic effect of mixture and found that the effects are almost always non-additive if the effects are evaluated by total metal concentrations, and the non-additivity is not derived by interactions among metals but by a combination of processes of metal kinetics. Once non-additive effects are observed in chemical mixture, it is often expected that there should be some complex toxic mechanisms or some toxic interaction. Our results suggest that the expectation may not be always true. Since at least two processes are entrained in the metal toxicity (metal speciation and binding of metals to biotic ligand in BLM framework), there is a possibility that the non-additivity is generated by the combination of processes and interaction is nothing to do with it. Our results imply that toxic effects of metal mixture can be predicted more easily than we generally expected. [ABSTRACT FROM AUTHOR]

We investigated responses of macroinvertebrates to different zinc concentrations in urban rivers contaminated with organic matter in a regional-scale monitoring survey and a smaller-scale field study. The present study was designed to test our prediction that total zinc concentrations of ∼60 μg/L (twice the Japanese environmental quality standard) do not lead to significant reductions in richness or abundance of macroinvertebrates in organic-contaminated rivers (biochemical oxygen demand of >3 mg/L). At the organic-contaminated sites in both surveys, very few species were present, and metal-sensitive heptageniid and ephemerellid mayflies were generally absent. In the regional-scale study, total zinc concentrations of up to 70 μg/L resulted in little reduction in macroinvertebrate richness. In the local-scale study, macroinvertebrate richness and abundance were not greatly reduced at the polluted downstream site with a total zinc concentration of 48 μg/L. Results from both surveys support our prediction. Therefore, an important implication of this study is that macroinvertebrate taxa that are susceptible to metal pollution should be sparse or absent in organic-contaminated rivers, so the impacts of metals such as zinc may be limited owing to the species-poor communities. Further research is required to evaluate the importance of reduced zinc bioavailability associated with increased organic matter and water hardness to the species-poor communities in organic-contaminated rivers. [ABSTRACT FROM AUTHOR]

Researchers have suggested that cyprinid fishes are less sensitive to chemical stress than comparable fish families, yet few empirically based evaluations of this hypothesis have been conducted. In this study, we developed a generalized linear mixed model in which the no-effect concentrations (NECs; threshold concentration below which no effect on survival is predicted during prolonged exposure) of 29 fish species from 13 families exposed to an acetylcholinesterase inhibitor pesticide (carbaryl, chlorpyrifos, or malathion) were used as the response variable. The corresponding specific somatic maintenance (SSM) rates, as a size-independent proxy for fish metabolism and a categorical variable regarding whether the species is a cyprinid, were used as the predictor variables. We included SSM rates in the analysis because previous work demonstrated that they are negatively correlated with NECs. Our results indicate that the NECs for cyprinid fishes were significantly higher than those for other fishes, suggesting that cyprinids are indeed less sensitive to the three studied pesticides. Although the SSM rates were negatively related with the NECs, the actual relationship between the two was not clear, implying that the importance of SSM rates may depend on the taxonomic group tested. [ABSTRACT FROM AUTHOR]

The Watarase River, running through Japan's northern Kanto region, has a long history of trace-metal contamination originating from the Ashio Copper Mine. Given the historical importance of incidents at this mine, understanding spatiotemporal environmental changes in the river, including changes in water quality, is important. By using long-term water-quality monitoring data (1960-2010), we aimed to reconstruct the spatiotemporal changes in six water-quality variables-the concentrations of three metals (copper, zinc, arsenic), biochemical oxygen demand (BOD), chemical oxygen demand (COD), and concentration of nitrate-nitrogen-along the Watarase River using generalized additive mixed models. The modeling results clearly demonstrate that during the 1960 and 1970s, metal pollution levels (as represented by copper and zinc) greatly decreased (from 450-2300 to 8-39 μg Cu L and from 490-1500 to 17-52 μg Zn L), whereas organic pollution levels, as represented by the BOD and COD increased. Unique changes were observed in the cases of arsenic and nitrate-nitrogen (e.g., marked increases in the 1960s). From the 1980s until 2010, gradual decreases in the levels of metal and organic pollution were generally observed. Only in the 2000s were annual mean concentrations of copper in the lower reaches of the Watarase River lower than the US Environmental Protection Agency (EPA) water-quality criterion. [ABSTRACT FROM AUTHOR]

To use species sensitivity distributions (SSDs) for ecological risk assessment, there are various uncertainties, which require applying assessment factors (AFs) accordingly. This study aims to quantify the uncertainty of estimating statistical distributions. Given a management goal of protecting 95% of species, the concentration that affects 5% of the species (HC5) is estimated. Since the true concentration affecting 5% of the species (population HC5) is unknown, the estimated HC5 is divided by an AF to derive the predicted no-effect concentration (PNEC), which is set as the protection goal, to compensate for the deviation in the estimated HC5 from the population HC5. Although the deviation between these two HC5 values depends on the sample size and the variation in sensitivity (standard deviation of the distribution) among species, there has been little discussion of how to quantify the degree of uncertainty. By assuming that toxicity values are a random sample from a lognormal distribution, we mathematically analyzed the SSD to derive the magnitude of AF needed to achieve a given protection goal (as an example, the protection of 95% of species with a probability of 95%). We successfully derived an equation that explicitly relates the magnitude of AF to the sample size and the variation in species sensitivity, providing a new basis to statistically determine the magnitude of AF for ecological risk assessments. • Quantifying ecological risk using log-normal species sensitivity distributions. • Relationship between AF and the probability of achieving protection goals. • AF as equivalent to various types of uncertainty, such as sample size, variation among data. • Quality check for given dataset. [ABSTRACT FROM AUTHOR]

Increased concerns about the toxicity of chemical mixtures have led to greater emphasis on analyzing the interactions among the mixture components based on observed effects. The authors applied a generalized linear mixed model (GLMM) to analyze survival of brown trout ( Salmo trutta) acutely exposed to metal mixtures that contained copper and zinc. Compared with dominant conventional approaches based on an assumption of concentration addition and the concentration of a chemical that causes x% effect (ECx), the GLMM approach has 2 major advantages. First, binary response variables such as survival can be modeled without any transformations, and thus sample size can be taken into consideration. Second, the importance of the chemical interaction can be tested in a simple statistical manner. Through this application, the authors investigated whether the estimated concentration of the 2 metals binding to humic acid, which is assumed to be a proxy of nonspecific biotic ligand sites, provided a better prediction of survival effects than dissolved and free-ion concentrations of metals. The results suggest that the estimated concentration of metals binding to humic acid is a better predictor of survival effects, and thus the metal competition at the ligands could be an important mechanism responsible for effects of metal mixtures. Application of the GLMM (and the generalized linear model) presents an alternative or complementary approach to analyzing mixture toxicity. Environ Toxicol Chem 2015;34:816-820. © 2015 SETAC [ABSTRACT FROM AUTHOR]

The authors tested the applicability of a previously developed biotic ligand model (BLM) to predict acute toxicity of single metals and metal mixtures (cadmium, lead, and zinc) to rainbow trout fry ( Oncorhynchus mykiss) from a single available dataset. The BLM used in the present study hypothesizes that metals inhibit an essential cation (calcium) and organisms die as a result of its deficiency, leading to an assumption that the proportion of metal-binding ligand ( f) is responsible for the toxic effects of metals on the survival of rainbow trout. The f value is a function of free-ion concentrations of metals computed by a chemical speciation model, and the function has affinity constants as model parameters. First, the survival effects of single metals were statistically modeled separately (i.e., f-survival relationship) by using the generalized linear mixed model with binomial distribution. The modeled responses of survival rates to f overlapped reasonably irrespective of metals tested, supporting the theoretical prediction from the BLM that f-survival relationships are comparable regardless of metal species. The authors thus developed the generalized linear mixed model based on all data pooled across the single-metal tests. The best-fitted model well predicted the survival responses observed in mixture tests ( r = 0.97), providing support for the applicability of the BLM to predict effects of metal mixtures. Environ Toxicol Chem 2015;34:754-760. © 2014 SETAC [ABSTRACT FROM AUTHOR]