Ecological Risk Assessment Of Chemicals Research Articles

Population dynamics hide phenotypic changes driven by subtle chemical exposures: implications for risk assessments

Ecological risk assessment of chemicals focuses on the response of different taxa in isolation not taking ecological and evolutionary interplay in communities into account. Its consideration would, however, allow for an improved assessment by testing for implications within and across trophic levels and changes in the phenotypic and genotypic diversity within populations. We present a simple experimental system that can be used to evaluate the ecological and evolutionary responses to chemical exposure at microbial community levels. We exposed a microbial model system of the ciliate Tetrahymena thermophila (predator) and the bacterium Pseudomonas fluorescens (prey) to iron released from Magnetic Particles (MP-Fedis), which are Phosphorus (P) adsorbents used in lake restoration. Our results show that while the responses of predator single population size differed across concentrations of MP-Fedis and the responses of prey from communities differed also across concentration of MP-Fedis, the community responses (species ratio) were similar for the different MP-Fedis concentrations. Looking further at an evolutionary change in the bacterial preys’ defence, we found that MP-Fedis drove different patterns and dynamics of defence evolution. Overall, our study shows how similar community dynamics mask changes at evolutionary levels that would be overlooked in the design of current risk assessment protocols where evolutionary approaches are not considered.

Explicit Consideration of Temperature Improves Predictions of Toxicokinetic-Toxicodynamic Models for Flupyradifurone and Imidacloprid in Gammarus pulex.

In the face of global climate change, where temperature fluctuations and the frequency of extreme weather events are increasing, it is needed to evaluate the impact of temperature on the ecological risk assessment of chemicals. Current state-of-the-art mechanistic effect models, such as toxicokinetic-toxicodynamic (TK-TD) models, often do not explicitly consider temperature as a modulating factor. This study implemented the effect of temperature in a widely used modeling framework, the General Unified Threshold model for Survival (GUTS). We tested the model using data from toxicokinetic and toxicity experiments with Gammarus pulex exposed to the insecticides imidacloprid and flupyradifurone. The experiments revealed increased TK rates with increasing temperature and increased toxicity under chronic exposures. Using the widely used Arrhenius equation, we could include the temperature influence into the modeling. By further testing of different model approaches, differences in the temperature scaling of TK and TD model parameters could be identified, urging further investigations of the underlying mechanisms. Finally, our results show that predictions of TK-TD models improve if we include the toxicity modulating effect of temperature explicitly.

QSAR models for soil ecotoxicity: Development and validation of models to predict reproductive toxicity of organic chemicals in the collembola Folsomia candida

Soil pollution is a critical environmental challenge: the substances released in the soil can adversely affect humans and the ecosystem. Several bioassays were developed to investigate the soil ecotoxicity of chemicals with soil microbes, plants, invertebrates and vertebrates. The 28-day collembolan reproduction test with the springtail Folsomia candida is a recently introduced bioassay described by OECD guideline 232. Although the importance of springtails for maintaining soil quality, toxicity data for Collembola are still limited. We have developed two QSAR models for the prediction of reproductive toxicity induced by organic compounds in Folsomia candida using 28 days NOEC data. We assembled a dataset with the highest number of compounds available so far: 54 compounds were collected from publicly available sources, including plant protection products, reactive intermediates and industrial chemicals, household and cosmetic ingredients, drugs, environmental transformation products and polycyclic aromatic hydrocarbons. The models were developed using partial least squares regression (PLS) and the Monte Carlo technique with respectively the open source tools Small Dataset Modeler and CORAL software. Both QSAR models gave good predictive performance even though based on a small dataset, so they could serve for the ecological risk assessment of chemicals for terrestrial organisms.

Bioenergetics modelling to analyse and predict the joint effects of multiple stressors: Meta-analysis and model corroboration

Understanding the consequences of the combined effects of multiple stressors—including stress from man-made chemicals—is important for conservation management, the ecological risk assessment of chemicals, and many other ecological applications. Our current ability to predict and analyse the joint effects of multiple stressors is insufficient to make the prospective risk assessment of chemicals more ecologically relevant because we lack a full understanding of how organisms respond to stress factors alone and in combination. Here, we describe a Dynamic Energy Budget (DEB) based bioenergetics model that predicts the potential effects of single or multiple natural and chemical stressors on life history traits. We demonstrate the plausibility of the model using a meta-analysis of 128 existing studies on freshwater invertebrates. We then validate our model by comparing its predictions for a combination of three stressors (i.e. chemical, temperature, and food availability) with new, independent experimental data on life history traits in the daphnid Ceriodaphnia dubia. We found that the model predictions are in agreement with observed growth curves and reproductive traits. To the best of our knowledge, this is the first time that the combined effects of three stress factors on life history traits observed in laboratory studies have been predicted successfully in invertebrates. We suggest that a re-analysis of existing studies on multiple stressors within the modelling framework outlined here will provide a robust null model for identifying stressor interactions, and expect that a better understanding of the underlying mechanisms will arise from these new analyses. Bioenergetics modelling could be applied more broadly to support environmental management decision making.

A 3-Species Aquatic Community Model for Ecological Risk Assessment Using Basic Ecotoxicity Data.

A simplified ecosystem model, the Aquatic Tritrophic Ecological Risk Assessment Model (A-TERAM), for the ecological risk assessment of chemicals is presented. The A-TERAM comprises a linear grazer food chain with 3 trophic levels (the algae-Daphnia-fish system). The model simulates the seasonal patterns of abundance at each level observed in the field, and it translates the direct toxic effects of chemicals on algae or Daphnia to implications for fish via ecological interactions; thus, the A-TERAM evaluates ecological risk in terms of the annual population growth rate of fish. The model also incorporates toxicokinetics for fish. The minimum input data required for the A-TERAM are basic ecotoxicity endpoints (algal growth inhibition median effect concentration [EC50] or no-observed effect concentration, Daphnia immobility EC50, and fish acute mortality median lethal concentration); however, additional ecotoxicity data (Daphnia reproduction test, fish early life test, and fish reproduction test) are also relevant for improving simulations. Comparisons made across 496 chemicals (255 nonagricultural chemicals and 241 agrochemicals) indicated that the A-TERAM, in comparison with the conventional predicted-effect concentration/predicted-no-effect concentration method, tended to evaluate higher risk to chemicals that are highly bioaccumulative and toxic to fish by 2 orders of magnitude at the largest but lower or comparable risk to chemicals that are toxic only to algae or Daphnia. Environ Toxicol Chem 2020;39:1086-1100. © 2020 SETAC.

Influences of Salinity and Organic Compounds on Embryo Development in Three Medaka Oryzias Congeners with Habitats Ranging from Freshwater to Marine.

To clarify whether Oryzias congeners, including freshwater, brackish water, and marine medaka, would be useful models for evaluating environmental chemical effects in various aquatic ecosystems, we examined the influence of salinity on their embryo development. We also compared the toxicity values of the organotin compounds triphenyltin and tributyltin, which remain pollutants of marine and freshwater ecosystems, between Oryzias latipes (freshwater), Oryzias melastigma (brackish water), and Oryzias javanicus (saltwater). Hatching and survival rates of O. latipes were significantly decreased at a salinity of 34, whereas O. melastigma and O. javanicus were adaptable to various salinities from freshwater to seawater. The lowest observed effect concentrations of organotin compounds for survival and embryo development were the similar in the three species. The similarity of the species' responses to organotin compounds indicated that Oryzias congeners are useful for ecological risk assessment of chemicals in a range of aquatic ecosystems, from freshwater to marine.

Insights into pesticide toxicity against aquatic organism: QSTR models on Daphnia Magna

The toxicities of agrochemicals to non-target aquatic organisms are key items in chemical ecological risk assessment. However, it is still an urgent need to develop new tools to assess the agrochemical aquatic toxicity efficiently and accurately. In this work, QSTR studies were performed on a data set containing 639 diverse pesticides with measured EC50 toxicity against Daphnia magna, by using five machine learning methods combined with seven fingerprints and a set of molecular descriptors. The imbalance problem of the data set was successfully solved by clustering analysis. The top-10 QSTR models displayed greater predicative abilities than ECOSAR. The optimal model, Ext-SVM, showed the best performance in 10-fold cross validation (Qhigh=0.807, Qmoderate=0.806, Qlow=0.755, Qtotal=0.794), and also in the test set verification (Qhigh=0.865, Qmoderate=0.783, Qlow=0.931, Qtotal=0.848). The relevance of the key physical-chemical properties with the toxicity was also investigated, in which the MW, a_np, logP(o/w), GCUT_SLOGP_1, chilv and SMR_VSA7 values displayed positive correlation with Daphnia magna toxicity, whereas the logS and a_don showed negative correlation. The robust QSTR models provided efficient tools for assessing agrochemical aquatic toxicity, and the revealed different physical-chemical properties between the high and low toxic compounds might be useful in the discovery and design of low aquatic toxic pesticides.

“AMORE” Decision Support System for probabilistic Ecological Risk Assessment - Part II: Effect assessment of the case study on cyanide

Ecotoxicological data are highly important for risk assessment processes and are used for deriving environmental quality criteria, which are enacted for assuring the good quality of waters, soils or sediments and achieving desirable environmental quality objectives. Therefore, it is of significant importance the evaluation of the reliability and relevance of available data for analysing their possible use in the aforementioned processes. In this context, a new methodology which has been developed based on Multi-Criteria Decision Analysis (MCDA) techniques, is being used, demonstrated and tested for analysing the reliability and relevance of ecotoxicological data of cyanide (which are produced through laboratory biotests for individual effects). The proposed methodology is also used for the production of Weighted by Data Quality Species Sensitivity Distributions (SSD-WDQ), as a component of the Ecological Risk Assessment of chemicals in aquatic systems. The SSD-WDQ production resulted in the estimation of environmental quality criteria (hazard concentration affecting 5% and 50% of the species). The proposed work is part of the development of the AMORE Decision Support System (DSS) for the application of probabilistic Ecological Risk Assessment (ERA), presented in the companion paper (Isigonis et al., 2019). The DSS has been tested through a case study on ERA of cyanide in the watershed of river Selune in France. The paper presents the ‘Effect Assessment’ of cyanide, based on the aforementioned methodologies. The main results presented in the paper are the probabilistic analysis of the estimated species sensitivity on cyanide (Effect Assessment) and the calculation of Hazardous Concentration (HCx) of the same contaminant in the Selune river area, based on the functionalities of the DSS. The results are described and discussed in detail, with the use of various graphs and indices. The indices are calculated for all the available ecotoxicological data, as well as for the data on trophic levels or taxonomic groups separately. An effect comparison is presented between the innovative methodologies included in the DSS and the currently existing methodologies.

“AMORE” Decision Support System for probabilistic Ecological Risk Assessment - Part I: Exposure and risk assessment of the case study on cyanide

Ecological Risk Assessment of chemicals in fluvial systems is a highly researched topic, but its importance for the environmental protection of our planet is vital. Thus, new developments and improvements to existing methodologies are proposed constantly, for providing more advanced tools and more accurate results to researchers and other interested parties. In the field of probabilistic Ecological Risk Assessment, a new Decision Support System is proposed, developed, tested and evaluated. The AMORE DSS is a modular DSS, which incorporates a series of new methodologies, and is built upon the notions of ‘Exposure Assessment’, ‘Effect Assessment’ and ‘Risk Assessment’. The AMORE Decision Support System has been developed as part of the AMORE research project (French National Research Agency project). The DSS provides a set of tools for analysing and integrating both exposure and effect information in order to evaluate the risk for species living on a given contaminated aquatic system in terms of the Potentially Affected Fraction. The DSS has been tested through a case study on ERA of cyanide in the watershed of river Selune in France. The paper presents the ‘Exposure Assessment’ and ‘Risk Assessment’ of the cyanide case study, as well as the complete functionalities of the AMORE DSS. The main results presented in the paper are the statistical analysis of the measured environmental concentrations of cyanide (Exposure Assessment) and the probabilistic ‘Risk assessment’ of the same contaminant in the area of interest, based on the functionalities of the DSS. The results are described and discussed in detail with the use of various graphs and risk indices. The risk indices are calculated for all the available ecotoxicological data, as well as for the data on trophic levels or taxonomic groups separately. A risk comparison is presented between the innovative methodologies included in the DSS and the currently existing methodologies.

Transgenerational impairments of reproduction and development of the marine invertebrate Crepidula onyx resulted from long-term dietary exposure of 2,2',4,4'-tetrabromodiphenyl ether (BDE-47).

Polybrominated diphenyl ethers have become ubiquitous in the environment and elevated concentrations have often been found in marine organisms. Using the gastropod Crepidula onyx as a study model, this multigenerational study sets out to test the hypotheses that 1) parental dietary exposure to environmentally realistic levels of 2,2',4,4'-tetrabrominated diphenyl ether (BDE-47) would lead to transgenerational impairments on fitness traits of marine invertebrates, and 2) the organisms might develop adaptation/acclimation after exposure for one or more generations. F0 generation of C.onyx was fed with the dinoflagellate Isochrysis galbana encapsulated with two concentrations of BDE-47 (1.78 and 16.0 ng million cells-1, respectively), and half of the F1 offspring from the higher concentration treatment was returned to control condition (transgenerational group), while the other half received BDE-47 treatment continuously (continuous treatment group). Bioaccumulation and maternal transfer of BDE-47 were evident in all life stages of the F0 generation and in F1 eggs, respectively. Exposure to BDE-47 reduced fecundity, delayed sexual maturity, and impeded embryonic development in F0 to F2. In particular, developmental toxicity of F2 embryos was apparent in the transgenerational group, but not in the continuous treatment group, even when BDE-47 was not detected in the F2 embryos nor in their mothers and they have never been exposed to the chemical. This study also suggested that the offspring might have developed adaptation/acclimation to the exposure of BDE-47 within two generations of exposure, and that the physiological alterations associated with acclimation/adaptation might have hindered the normal larval development under a stress free condition. These findings highlighted the need for long-term multigenerational studies in the ecological risk assessment of chemicals alike.

Insights into the Molecular Basis of the Acute Contact Toxicity of Diverse Organic Chemicals in the Honey Bee.

Use of chemical pollutants, including pesticides and other industrial chemicals, has resulted in significant risks to the whole ecosystem. Therefore, ecological risk assessment of chemicals is vital and necessary. Since the honey bee (Apis mellifera) is probably among the most exposed species to the polluting chemicals, we focused on the in silico estimation of honey bee toxicity (HBT) of chemicals and the analysis of the relevance of chemical HBT and several key physical-chemical properties and structural characteristics. A total of 40 classification models were developed by combination of five machine learning methods along with seven kinds of fingerprints and a set of molecular descriptors. After 5-fold cross validation and external validation, several models showed good predictive power. The relevance of 12 key physical-chemical properties and chemical HBT was also investigated. Five properties, including AlogP, logD, molecular weight (MW), molecular surface area (MSA), and the number of rotatable bonds (nRTB), indicated positive correlation coefficients with HBT, while molecular solubility (logS) and the number of hydrogen bond donors (nHBD) indicated negative correlation coefficients. Finally, seven privileged substructures responsible for chemical HBT were identified from KRFP and SubFP fingerprints. The results of this study should provide critical information and useful tools for chemical HBT estimation in environmental risk assessment.

Applying adverse outcome pathways and species sensitivity-weighted distribution to predicted-no-effect concentration derivation and quantitative ecological risk assessment for bisphenol A and 4-nonylphenol in aquatic environments: A case study on Tianjin City, China.

Adverse outcome pathways (AOPs) are a novel concept that effectively considers the toxic modes of action and guides the ecological risk assessment of chemicals. To better use toxicity data including biochemical or molecular responses and mechanistic data, we further developed a species sensitivity-weighted distribution (SSWD) method for bisphenol A and 4-nonylphenol. Their aquatic predicted-no-effect concentrations (PNECs) were derived using the log-normal statistical extrapolation method. We calculated aquatic PNECs of bisphenol A and 4-nonylphenol with values of 4.01 and 0.721 µg/L, respectively. The ecological risk of each chemical in different aquatic environments near Tianjin, China, a coastal municipality along the Bohai Sea, was characterized by hazard quotient and probabilistic risk quotient assessment techniques. Hazard quotients of 7.02 and 5.99 at 2 municipal sewage sites using all of the endpoints were observed for 4-nonylphenol, which indicated high ecological risks posed by 4-nonylphenol to aquatic organisms, especially endocrine-disrupting effects. Moreover, a high ecological risk of 4-nonylphenol was indicated based on the probabilistic risk quotient method. The present results show that combining the SSWD method and the AOP concept could better protect aquatic organisms from adverse effects such as endocrine disruption and could decrease uncertainty in ecological risk assessment. Environ Toxicol Chem 2018;37:551-562. © 2017 SETAC.

Application of physiologically based toxicokinetics models in risk assessment of chemicals

External exposure concentrations were conventionally employed used to quantify toxicological effects of chemicals in their risk assessment. However, internal concentrations are more suitable for understanding the toxicological effects and conducting risk assessment. It is necessary for accurate risk assessment of chemicals to predict the internal exposure of chemicals from the external exposure, and to know distribution of chemicals in different target tissues/organs (e.g. liver, kidney) of organisms. Experimental determination can hardly get high-throughput acquisition of target concentrations due to analytical limitations and expensive cost for in vivo animal tests. Alternatively, physiologically based toxicokinetics (PBTK) models that can quantitatively predict absorption, distribution, metabolism and excretion (ADME) processes of chemicals in biota are particularly useful. PBTK models could be used to predict the target concentrations, and to relate the environmental exposure concentrations with the target concentrations. Development of PBTK models can be divided into five steps. (1) Specify the general model structure. Portal of entry, target organ, lipophilicity and metabolism of chemicals are basic factors that should be considered. (2) Determine the set of ordinary differential equations representing the ADME processes of chemicals by the organism. All of these equations are mass balance equations. (3) Define model parameters, including physiological parameters, partition coefficients, biochemical rate constants and environment parameters. (4) Solve the ordinary differential equations with proper software. (5) Validate the model. Simulation results should be compared with corresponding experimental data to evaluate whether the model is accurate enough. Sensitivity, uncertainty and variability analysis should be performed to further optimize the model. Originating as a tool for serving pharmaceutical industry, PBTK models are now used in risk assessment of chemicals. PBTK models can also relate the in vivo toxicity thresholds with the in vitro toxicity thresholds. The in vitro-in vivo extrapolation can facilitate the utilization of the vast volume of high-throughput in vitro data. Traditional in vivo tests only focus on a limited number of the diverse species residing within an ecosystem. PBTK models can provide a promising cross-species solution by establishing physiologically relevant models for various species. Besides, classical indicators for hazard assessment such as bioconcentration factors could be re-evaluated by PBTK models with upgraded accuracy and details. Furthermore, it is possible to simulate the risk of chemicals that exerted on organisms over the entire lifetime of organisms with a sequence of PBTK models representing different developmental stages of the species. The combination of PBTK models and toxicodynamics (TD) models, i.e. PBTK/TD models, can further realize the simulation of the dynamic distribution of xenobiotics as well as the effects simultaneously. The power of PBTK models intended for ecological risk assessment of chemicals is yet to be fully exploited. Current PBTK models mainly apply to chemicals of neutral states. However, the molecular structures of many organic pollutants have carboxylic, phenolic groups, etc. Thus, these compounds can ionize under environmental pH conditions. A compound with different ionized states could possess different intake pathways. Thus, certain modifications of the mathematical form of the PBTK models are necessary. Another major obstacle is that the sophisticated parameters of PBTK models cannot be easily collected. Therefore, schemes for a high-throughput acquisition of the relevant parameters (e.g. quantitative structure-activity relationship models) would be highly useful. Furthermore, PBTK models should be extended to more species of ecological importance.

化学物質の生態リスク評価 : その来歴と現在の課題( 我々は「生態リスク」とどう向き合うのか?)

化学物質の生態リスク評価 : その来歴と現在の課題( 我々は「生態リスク」とどう向き合うのか?)

Acute and chronic toxicity of diuron and carbofuran to the neotropical cladoceran Ceriodaphnia silvestrii.

In order to contribute to the increase of the body of knowledge on the sensitivity of tropical indigenous species to pesticides, acute and chronic toxicity tests were conducted with the neotropical cladoceran Ceriodaphnia silvestrii. Tests were carried out with the active ingredients diuron and carbofuran and one of their commercial formulations, the Diuron Nortox® 500 SC and the Furadan® 350 SC, respectively. For carbofuran, the active ingredient was more toxic than the commercial product, whereas for diuron, the commercial product appeared more toxic. In addition, hormetic effects on fertility were recorded for intermediate diuron concentrations. Acute and chronic toxicity data indicated that C. silvestrii was among the most sensitive invertebrate species for both test compounds. Based on concentrations measured in Brazilian water bodies, these compounds represent ecological risks for causing direct and indirect toxic effects on C. silvestrii and other aquatic organisms. Our results support previous claims on the advantages of using native species to better tune ecological risk assessment of chemicals in tropical ecosystems.

Relative influence of chemical and non-chemical stressors on invertebrate communities: a case study in the Danube River

A key challenge for the ecological risk assessment of chemicals has been to evaluate the relative contribution of chemical pollution to the variability observed in biological communities, as well as to identify multiple stressor groups. In this study we evaluated the toxic pressure exerted by >200 contaminants to benthic macroinvertebrates in the Danube River using the Toxic Unit approach. Furthermore, we evaluated correlations between several stressors (chemical and non-chemical) and biological indices commonly used for the ecological status assessment of aquatic ecosystems. We also performed several variation partitioning analyses to evaluate the relative contribution of contaminants and other abiotic parameters (i.e. habitat characteristics, hydromorphological alterations, water quality parameters) to the structural and biological trait variation of the invertebrate community. The results of this study show that most biological indices significantly correlate to parameters related to habitat and physico-chemical conditions, but showed limited correlation with the calculated toxic pressure. The calculated toxic pressure, however, showed little variation between sampling sites, which complicates the identification of pollution-induced effects. The results of this study show that the variation in the structure and trait composition of the invertebrate community are mainly explained by habitat and water quality parameters, whereas hydromorphological alterations play a less important role. Among the water quality parameters, physico-chemical parameters such as suspended solids, nutrients or dissolved oxygen explained a larger part of the variation in the invertebrate community as compared to metals or organic contaminants. Significant correlations exist between some physico-chemical measurements (e.g. nutrients) and some chemical classes (i.e. pharmaceuticals, chemicals related to human presence) which constitute important multiple stressor groups. This study demonstrates that, in large rivers like the Danube, the variation in the invertebrate community seems to be more related to varying habitat and physico-chemical conditions than to chemical pollution.

How to use mechanistic effect models in environmental risk assessment of pesticides: Case studies and recommendations from the SETAC workshop MODELINK.

Mechanistic effect models (MEMs) are useful tools for ecological risk assessment of chemicals to complement experimentation. However, currently no recommendations exist for how to use them in risk assessments. Therefore, the Society of Environmental Toxicology and Chemistry (SETAC) MODELINK workshop aimed at providing guidance for when and how to apply MEMs in regulatory risk assessments. The workshop focused on risk assessment of plant protection products under Regulation (EC) No 1107/2009 using MEMs at the organism and population levels. Realistic applications of MEMs were demonstrated in 6 case studies covering assessments for plants, invertebrates, and vertebrates in aquatic and terrestrial habitats. From the case studies and their evaluation, 12 recommendations on the future use of MEMs were formulated, addressing the issues of how to translate specific protection goals into workable questions, how to select species and scenarios to be modeled, and where and how to fit MEMs into current and future risk assessment schemes. The most important recommendations are that protection goals should be made more quantitative; the species to be modeled must be vulnerable not only regarding toxic effects but also regarding their life history and dispersal traits; the models should be as realistic as possible for a specific risk assessment question, and the level of conservatism required for a specific risk assessment should be reached by designing appropriately conservative environmental and exposure scenarios; scenarios should include different regions of the European Union (EU) and different crops; in the long run, generic MEMs covering relevant species based on representative scenarios should be developed, which will require EU-level joint initiatives of all stakeholders involved. The main conclusion from the MODELINK workshop is that the considerable effort required for making MEMs an integral part of environmental risk assessment of pesticides is worthwhile, because it will make risk assessments not only more ecologically relevant and less uncertain but also more comprehensive, coherent, and cost effective.

Effect of thiram and of a hydrocarbon mixture on freshwater macroinvertebrate communities in outdoor stream and pond mesocosms: II. Biological and ecological trait responses and leaf litter breakdown.

Higher-tier ecological risk assessment of chemicals often relies upon studies in dynamic and/or static mesocosms. Physico-chemical and hydrological properties of each type of mesocosm result in specific chemicals fate, community functioning, and potential recovery. In the present study, macroinvertebrate abundance- and biomass-weighted biological and ecological trait matrices were used to assess the effects of a dithiocarbamate fungicide, thiram (35 and 170 µg l(-1)), and of a petroleum middle distillate (0.01, 0.4, 2 and 20 mg l(-1)) in outdoor stream and pond mesocosms. Trait sensitivity was characterized using functional diversity indices and trait modality distributions to assess the influence of the type of experimental systems and the ability of traits to disentangle chemical-induced effects from temporal and stochastic variations. In addition, leaf litter breakdown was used as an integrative functional endpoint. Regardless to the substance, treatments had a direct effect on the functional structure of benthic macroinvertebrate communities in streams but not in ponds, suggesting that global functional responses to chemicals are system-specific. Although both substances had an effect in streams, differences were noticed in the nature of the affected traits suggesting that chemical mode of action plays a role in functional alterations. This was illustrated by the link between negative effects of chemical exposure on detritivorous taxa and reduced litter breakdown rate in streams. Therefore, characterisation of macroinvertebrate biological traits associated with the measurement of a functional process such as litter breakdown may provide a comprehensive understanding of the effects occurring in mesocosms exposed to organic chemicals.

A Multi-Criteria Decision Analysis based methodology for quantitatively scoring the reliability and relevance of ecotoxicological data

Ecotoxicological data are highly important for risk assessment processes and are used for deriving environmental quality criteria, which are enacted for assuring the good quality of waters, soils or sediments and achieving desirable environmental quality objectives. Therefore, it is of significant importance the evaluation of the reliability of available data for analysing their possible use in the aforementioned processes. The thorough analysis of currently available frameworks for the assessment of ecotoxicological data has led to the identification of significant flaws but at the same time various opportunities for improvement. In this context, a new methodology, based on Multi-Criteria Decision Analysis (MCDA) techniques, has been developed with the aim of analysing the reliability and relevance of ecotoxicological data (which are produced through laboratory biotests for individual effects), in a transparent quantitative way, through the use of expert knowledge, multiple criteria and fuzzy logic. The proposed methodology can be used for the production of weighted Species Sensitivity Weighted Distributions (SSWD), as a component of the ecological risk assessment of chemicals in aquatic systems. The MCDA aggregation methodology is described in detail and demonstrated through examples in the article and the hierarchically structured framework that is used for the evaluation and classification of ecotoxicological data is shortly discussed. The methodology is demonstrated for the aquatic compartment but it can be easily tailored to other environmental compartments (soil, air, sediments).

Body size-dependent toxicokinetics and toxicodynamics could explain intra- and interspecies variability in sensitivity

Ecological risk assessment of chemicals aims at quantifying the likelihood of adverse effects posed to non-target populations and the communities they constitute, often based on lethal concentration estimates for standard test species. There may, however, be intra- and interspecific differences in responses to chemical exposure. Here with the help of a toxicokinetic-toxicodynamic model, we explored whether differential body sizes might explain the observed variability in sensitivity between species and between life-stages of each individual species, for three model organisms, Daphnia magna, Chaoborus crystallinus and Mesocyclops leuckarti. While body size-dependent toxicokinetics could be used to predict intraspecies variation in sensitivity, our results also suggest that changes in both toxicokinetic and toxicodynamic parameters might be needed to describe differential species sensitivity. Accounting for biological traits, like body size, in mechanistic effect models will allow more accurate predictions of chemical effects in size structured populations, ultimately providing mechanistic explanations for species sensitivity distributions.