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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]

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]

Although species distributions can change in an unexpectedly short period of time, most species distribution models (SDMs) use only long‐term averaged environmental conditions to explain species distributions. We aimed to demonstrate the importance of incorporating antecedent environmental conditions into SDMs in comparison to long‐term averaged environmental conditions. We modeled the presence/absence of 18 fish species captured across 108 sampling events along a 50‐km length of the Sagami River in Japan throughout the 1990s (one to four times per site at 45 sites). We constructed and compared the two types of SDMs: 1) a conventional model that uses only long‐term averaged (10‐yr) environmental conditions; and 2) a proposed model that incorporates environmental conditions 2 yr prior to a sampling event (antecedent conditions) together with long‐term averages linked to life‐history stages. These models both included geomorphological, hydrological, and sampling conditions as predictors. A random forest algorithm was applied for modeling and quantifying the relative importance of the predictors. For seven species, antecedent hydrological conditions were more important than the long‐term averaged hydrological conditions. Furthermore, the distributions of two species with low prevalence could not be predicted using long‐term averaged hydrological conditions but only using antecedent hydrological conditions. In conclusion, incorporating antecedent environmental factors linked with life‐history stages at appropriate time scales can better explain changes in species distribution through time. [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]

As part of the Metal Mixture Modeling Evaluation (MMME) project, models were developed by the National Institute of Advanced Industrial Science and Technology (Japan), the US Geological Survey (USA), HDR|HydroQual (USA), and the Centre for Ecology and Hydrology (United Kingdom) to address the effects of metal mixtures on biological responses of aquatic organisms. A comparison of the 4 models, as they were presented at the MMME workshop in Brussels, Belgium (May 2012), is provided in the present study. Overall, the models were found to be similar in structure (free ion activities computed by the Windermere humic aqueous model [WHAM]; specific or nonspecific binding of metals/cations in or on the organism; specification of metal potency factors or toxicity response functions to relate metal accumulation to biological response). Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single vs multiple types of binding sites on the organism) and specific calibration strategies that affected the selection of model parameters. The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results. Less-than-additive toxicity was more difficult to describe with the available models. Because of limitations in the available datasets and the strong interrelationships among the model parameters (binding constants, potency factors, toxicity response parameters), further evaluation of specific model assumptions and calibration strategies is needed. Environ Toxicol Chem 2015;34:741-753. © 2014 SETAC [ABSTRACT FROM AUTHOR]

In our respective careers in the field of environmental toxicology, we have read many peer-reviewed papers. We believe that there are 4 stakeholder groups responsible for improving the clarity and readability of published papers: educators, authors, editors, and reviewers. Although we agree with De Vries et al. (2009) that reviewers are responsible for "critical, thorough, thoughtful, constructive and timely" review, we do not agree with an author's neglect in fine-tuning her or his writing, with the attitude that "the reviewers would fix it.". [Extracted from the article]

Estimation of population-level benchmark concentrations for protecting aquatic organisms from chemicals is important for value-relevant ecological risk assessments. By employing a species sensitivity distribution (SSD) approach, the authors aimed to derive the population-level hazardous concentration for 5% of species (PHC5) for copper. Based on available information on copper toxicity and population models, the authors estimated population threshold concentrations at which the population size is stable (that is, 0 net population growth) for 13 freshwater species (3 algal, 6 invertebrate, and 4 fish species). The PHC5 for copper was then estimated (6.8 µg/L; 95% confidence interval [CI], 1.8-13.6 µg/L), by fitting a log-normal distribution to the population threshold concentrations obtained. The close overlap between the present study's estimate of the PHC5 and a field-derived threshold concentration suggests that the population-level SSD approach provides a reasonable level of protection for species richness in the natural environment. By contrast, and counterintuitively, the authors' estimate was comparable with the individual-level HC5 reported in the European Union risk assessment. Although the present study cannot determine the underlying reasons for the similar figures, the result provides an indication that the margin between individual-level and population-level benchmarks derived from SSD approaches can be very small. The results therefore suggest that attention is needed to achieve population-level protection using an individual-level SSD approach. Environ Toxicol Chem 2013;32:1396-1402. © 2013 SETAC [ABSTRACT FROM AUTHOR]

1. River flow alterations due to climate change and increasing water usage affect freshwater biodiversity including fish species richness. Here, we statistically explored the relationships of fish species richness to 14 ecologically relevant flow metrics as well as basin area and latitude in 72 rivers worldwide. 2. The statistical models best supported by the data included three variables with positive coefficients (mean river discharge, basin area and the maximum proportion of no-flooding period) and three variables with negative coefficients (latitude, coefficients of variation in the frequency of low flow and the Julian date of annual minimum flow). 3. The model outputs have provided the first empirical indication that specific low- and high-flow characteristics may be important in explaining variations in basin-scale fish species richness. Our findings can be useful in identifying high-risk basins for conservation of fish species diversity. 4. The results not only support the adoption of mean discharge as a predictor, but also suggest the importance of basin area in predicting basin-scale fish species richness around the world. [ABSTRACT FROM AUTHOR]

We conducted field surveys at 25 sites in three Japanese catchments to provide conservative estimates of the safe concentration of zinc (Zn) for the protection of riverine macroinvertebrate diversity. The relationships between the Zn concentration and six macroinvertebrate metrics for taxon richness were determined by using regression analysis; this included a piecewise regression model, where two lines are joined at an unknown point. For each metric the piecewise regression model with a zero slope below a threshold concentration was selected as the best model to explain the influence of Zn. Under the assumption that macroinvertebrate diversity reductions of <10% are acceptable, the safe concentrations of Zn were estimated to be 84, 115, 84, 80, 85, and 70 µg/L for total taxon richness, Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness, mayfly richness, caddisfly richness, chironomid richness, and estimated total taxon richness at the riffle scale, respectively. These concentrations are more than twice the water quality standard for Zn in Japan (30 µg/L), suggesting that the standard is likely overprotective for macroinvertebrate diversity. Field studies are useful for evaluating the level of protectiveness of safe concentrations (water quality standards) based on individual-level effects from laboratory toxicity tests, and this evaluation process will have a crucial role in implementing more purpose-driven ecological risk managements that aim to protect natural populations and communities. Environ. Toxicol. Chem. 2011;30:2237-2243. © 2011 SETAC [ABSTRACT FROM AUTHOR]

We examined the influence of heavy metal pollution from an abandoned mine on benthic macroinvertebrates, at population and community levels, and the potential amount of food available for drift-feeding fish in northern Japanese streams. We studied multiple polluted and unpolluted sites with similar longitudinal positions to avoid problems caused by upstream-downstream comparisons. The ranges of zinc, copper, cadmium, and lead concentrations among the study sites were 5 to 812 μg/L, less than 0.12 to 5.2 μg/L, less than 0.0026 to 4.9 μg/L, and 0.1 to 18.6 μg/L, respectively. The abundance of several populations and community metrics showed a significant negative response to heavy metal pollution. Mayfly diversity and abundance was relatively sensitive to heavy metal pollution. In addition, the biomass of groups of macroinvertebrate taxa that are highly available for salmonids were significantly reduced at metal-polluted sites; this decrease in the most highly available group was noticeable (99% at the heavily polluted upper sites and 69% at the moderately polluted lower sites in spring). These results suggest that we should consider the indirect effect of pollution on food availability for the conservation of fish populations that depend on drifting macroinvertebrates. [ABSTRACT FROM AUTHOR]

The article reports on mixture toxicity, concentration addition and response addition approaches to understand the toxicity of mixed chemicals in the environment. It states that effects of chemical mixtures are predicted by concentration addition and applying concentration addition is first choice in ecological risk assessment. It mentions that chemical interaction can be tested in statistical manner by using a linear model and work remains to develop methods for analyzing mixture toxicity.

The article discusses the use of population level consequences as the basis in determining the x or percentage effect in effective concentration (EC)x in toxicity testing. It says that population models can be used to investigate the individual-level trait's percent reduction are linked to extinction probability and population growth rate. It states that population models can determine acceptable x values in different endpoints based on the acceptable impacts of population-level.

The article focuses on the significance of field surveys on ecological risk assessment (ERA). It states that the discourse was done relative to research on metals and macroinvertebrates. It says that safe concentrations are estimated using quantile regression analysis using field data sets. It adds that various spatiotemporal factors of macroinvertebrate responses should be considered such as larval exposure, reproduction and response of populations.