Toxicokinetic-toxicodynamic modeling of quantal and graded sublethal endpoints: a brief discussion of concepts

Can TK-TD modelling bridge the gap between in vitro and in vivo mammalian toxicity data?

Repeated dietary dose testing is used to assess longer term toxicity of chemicals, such as pesticides, to mammals. However, the internal pesticide concentration varies significantly as feeding rate relative to body size fluctuates over time. Toxicokinetic-toxicodynamic (TK-TD) models can estimate internal toxicant concentration over time and link this directly to observed effects on endpoints such as the growth rate of laboratory rats. Using TK-TD models it is therefore possible to predict the effects that would result from a constant internal concentration of a pesticide. This presents the possibility of comparison with data from in vitro experiments, potentially facilitating quantitative in vitro to in vivo extrapolation (QIVIVE). We used in vivo TK-TD models to identify relevant internal concentrations and then estimated the experimental conditions required to replicate these in cultured cells, using in vitro TK models. Cell population growth was measured, with a view to extrapolating through time and comparing effect sizes with in vivo predictions. However, observed cell proliferation was not significantly affected by the tested concentrations of any of the five pesticides in this study and so extrapolation was not possible. In light of this negative result, we highlight areas for future work towards QIVIVE of graded sublethal effects in mammals. The most pressing objective is improving the accuracy of in vivo TK predictions, which could be achieved with dietary dosing in TK studies.

A Review of Mechanistic Models for Predicting Adverse Effects in Sediment Toxicity Testing

Since recognizing the importance of bioavailability for understanding the toxicity of chemicals in sediments, mechanistic modeling has advanced over the last 40 years by building better tools for estimating exposure and making predictions of probable adverse effects. Our review provides an up-to-date survey of the status of mechanistic modeling in contaminated sediment toxicity assessments. Relative to exposure, advances have been most substantial for non-ionic organic contaminants (NOCs) and divalent cationic metals, with several equilibrium partitioning-based (Eq-P) models having been developed. This has included the use of Abraham equations to estimate partition coefficients for environmental media. As a result of the complexity of their partitioning behavior, progress has been less substantial for ionic/polar organic contaminants. When the EqP-based estimates of exposure and bioavailability are combined with water-only effects measurements, predictions of sediment toxicity can be successfully made for NOCs and selected metals. Both species sensitivity distributions and toxicokinetic and toxicodynamic models are increasingly being applied to better predict contaminated sediment toxicity. Furthermore, for some classes of contaminants, such as polycyclic aromatic hydrocarbons, adverse effects can be modeled as mixtures, making the models useful in real-world applications, where contaminants seldomly occur individually. Despite the impressive advances in the development and application of mechanistic models to predict sediment toxicity, several critical research needs remain to be addressed. These needs and others represent the next frontier in the continuing development and application of mechanistic models for informing environmental scientists, managers, and decisions makers of the risks associated with contaminated sediments. Environ Toxicol Chem 2024;43:1778-1794. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Reproductive toxicity in birds predicted by physiologically-based kinetics and bioenergetics modelling

Effects on the growth and reproduction of birds are important endpoints in the environmental risk assessment (ERA) of pesticides. Toxicokinetic-toxicodynamic models based on dynamic energy budget theory (DEB) are promising tools to predict these effects mechanistically and make extrapolations relevant to ERA. However, before DEB-TKTD models are accepted as part of ERA for birds, ecotoxicological case studies are required so that stakeholders can assess their capabilities. We present such a case-study, modelling the effects of the fluopyram metabolite benzamide on the northern bobwhite quail (Colinus virginianus). We parametrised a DEB-TKTD model for the embryo stage on the basis of an egg injection study, designed to provide data for model development. We found that information on various endpoints, such as survival, growth, and yolk utilisation were needed to clearly distinguish between the performance of model variants with different TKTD assumptions. The calibration data were best explained when it was assumed that chemical uptake occurs via the yolk and that benzamide places stress on energy assimilation and mobilisation. To be able to bridge from the in vitro tests to real-life exposure, we developed a physiologically-based toxicokinetic (PBK) model for the quail and used it to predict benzamide exposure inside the eggs based on dietary exposure in a standard reproductive toxicity study. We then combined the standard DEB model with the TKTD module calibrated to the egg injection studies and used it to predict effects on hatchling and 14-day chick weight based on the exposure predicted by the PBK model. Observed weight reductions, relative to controls, were accurately predicted. Thus, we demonstrate that DEB-TKTD models, in combination with suitable experimental data and, if necessary, with an exposure model, can be used in bird ERA to predict chemical effects on reproduction.

A novel approach for the assessment of invertebrate behavior and its use in behavioral ecotoxicology

Sublethal effects are becoming more relevant in ecotoxicological test methods due to their higher sensitivity compared to lethal endpoints and their preventive nature. Such a promising sublethal endpoint is the movement behavior of invertebrates which is associated with the direct maintenance of various ecosystem processes, hence being of special interest for ecotoxicology. Disturbed movement behavior is often related to neurotoxicity and can affect drift, mate-finding, predator avoidance, and therefore population dynamics. We show the practical implementation of the ToxmateLab, a new device that allows monitoring the movement behavior of up to 48 organisms simultaneously, for behavioral ecotoxicology. We quantified behavioral reactions of Gammarus pulex (Amphipoda, Crustacea) after exposure to two pesticides (dichlorvos and methiocarb) and two pharmaceuticals (diazepam and ibuprofen) at sublethal, environmentally relevant concentrations. We simulated a short-term pulse contamination event that lasted 90 min. Within this short test period, we successfully identified behavioral patterns that were most pronounced upon exposure to the two pesticides: Methiocarb initially triggered hyperactivity, after which baseline behavior was restored. On the other hand, dichlorvos induced hypoactivity starting at a moderate concentration of 5 μg/L - a pattern we also found at the highest concentration of ibuprofen (10 μg/L). An additional acetylcholine esterase inhibition assay revealed no significant impact of the enzyme activity that would explain the altered movement behavior. This suggests that in environmentally realistic scenarios chemicals can induce stress - apart from mode-of-action - that affects non-target organisms' behavior. Overall, our study proves the practical applicability of empirical behavioral ecotoxicological approaches and thus represents a next step towards routine practical use.

Phycotoxins and marine annelids - A global review

Several species of microalgae can produce potent phycotoxins that negatively affect aquatic organisms and their consumers following different exposure routes, as well as toxicokinetic (TK) and toxicodynamic (TD) processes. Benthic organisms are especially vulnerable as they are exposed to both benthic and planktonic species causative of harmful algal blooms (HABs). While benthic algae can come into direct contact with annelids during substrate remobilization, planktonic cells can settle to the bottom mostly during senescence and/or encystment stages, and in shallow and calm waters. We performed a systematic, qualitative review of the literature on the phycotoxin TK and TD processes in marine annelids, summarizing the most relevant findings and general trends. Besides, by using innovative analytical/statistical approaches, we were able to detect patterns and gaps in the current literature, thus pointing to future research directions. We retrieved and analyzed studies involving diarrhetic shellfish toxins (DSTs), paralytic shellfish toxins (PSTs), brevetoxins (PbTXs), domoic acid (DA), as well as palytoxin and its congeners, the ovatoxins (treated together as PLTXs). It is worth mentioning that studies evaluating other phycotoxins (e.g., ciguatoxins, yessotoxins) were not found in the literature. The absence of data on PbTXs, PSTs and DA is the largest gap hampering TK assessment in annelids, although some relevant information on TD is already available. Whereas lethal effects from DSTs have not been reported, more potent toxins like PbTXs, PSTs, DA and those grouped as PLTX-like compounds can cause mortality and/or marked decrease in annelid abundance. In addition, phycotoxins have been linked to sublethal effects on annelid cells. Although very sparse, field and laboratory studies offer strong evidence that annelids may be reliable indicators of toxin exposure and their negative effects during both early and later stages of HABs in marine environments. Besides quickly responding to these compounds at both organismic and suborganismic levels, annelids are easily found in areas affected by HABs. The use of annelids in future investigations evaluating the action mechanisms of toxic microalgae on marine invertebrates should be thus encouraged. In this case, the choice for widely dispersed and numerically dominant species of annelids would strengthen the validation and extrapolation of results from risk assessments in areas affected by HABs worldwide.

Toxicokinetics and toxicodynamics of chromium in the soil invertebrate Enchytraeus crypticus (Oligochaeta)

Chromium emissions led to increased concentrations in soil, where it can affect soil organisms to relevant levels. With the aim of better understanding the effects of Cr throughout time, its toxicokinetics-toxicodynamics (TKTD) were evaluated in the soil model organism Enchytraeus crypticus to assess the development of internal concentrations and consequent toxic effects. To achieve this goal, organisms were exposed in LUFA 2.2 soil spiked with increasing CrCl₃ concentrations. During the 21-day exposure period, survival, internal concentrations, and reproduction were evaluated at several time points up to 21 days. Uptake and elimination rate constants were 0.0044 kg soil/kg organism/day and 0.023 per day, respectively. Internal Cr concentrations increased with time, generally reaching equilibrium within 14 days with an estimated LC50_inter (based on internal metal concentrations) of 57.7 mg Cr/kg body DW. Internal Cr concentrations were regulated by the organisms up to exposure to 360 mg Cr/kg soil DW, where the elimination rate was highest, but at 546 mg Cr/kg soil DW the animals were no longer able to eliminate Cr, and the internal concentrations were well above the estimated LC50_inter. At day 21, exposure to 546 mg Cr/kg soil DW significantly reduced survival by 23 %, while reproduction EC50 was 344 mg Cr/kg soil DW. This study highlights the advantages of using a TKTD approach to understand the development of internal metal concentrations in time and relate it to the phenotypical effects observed. Toxicity is better understood when also taking into account time and not just exposure concentration alone.

Size- and sex-related sensitivity differences of aquatic crustaceans to imidacloprid

Field collected aquatic invertebrates are often used as test organisms in the refinement of the standard Tier 1 risk assessment of various pollutants. This approach can provide insights into the effects of pollutants on the natural environment. However, researchers often pragmatically select test organisms of a specific sex and/or size, which may not represent the sensitivity of the whole population. To investigate such intraspecies sensitivity differences, we performed standard acute toxicity and toxicokinetic tests with different size classes and sex of Gammarus pulex and Asellus aquaticus. Furthermore, toxicokinetics and toxicodynamics models were used to understand the mechanism of the intraspecies sensitivity differences. We used neonates, juveniles and male and female adults in separate dedicated experiments, in which we exposed the animals to imidacloprid and its bioactive metabolite, imidacloprid-olefin. For both species, we found that neonates were the most sensitive group. For G. pulex, the sensitivity decreased linearly with size, which can be explained by the size-related uptake rate constant in the toxicokinetic process and size-related threshold value in the toxicodynamic process. For A. aquaticus, female adults were least sensitive to imidacloprid, which could be explained by a low internal biotransformation of imidacloprid to imidacloprid-olefin. Besides, imidacloprid-olefin was more toxic than imidacloprid to A. aquaticus, with differences being 8.4 times for females and 2.7 times for males. In conclusion, we established size-related sensitivity differences for G. pulex and sex-related sensitivity for A. aquaticus, and intraspecies differences can be explained by both toxicokinetic and toxicodynamic processes. Our findings suggest that to protect populations in the field, we should consider the size and sex of focal organisms and that a pragmatic selection of test organisms of equal size and/or sex can underestimate the sensitivities of populations in the field.

TWAc-Check: A New Approach to Determine the Appropriate Use of Time-Weighted Average Concentration in Aquatic Risk Assessment

In pesticide risk assessment, regulatory acceptable concentrations for surface water bodies (RACsw,ch) are used that are derived from standard studies with continuous exposure of organisms to a test compound for days or months. These RACsw,ch are compared with the maximum tested concentration of more realistic exposure scenarios. However, the actual exposure duration could be notably shorter (e.g., hours) than the standard study, which intentionally leads to an overly conservative Tier 1 risk assessment. This discrepancy can be addressed in a risk assessment using the time-weighted average concentration (TWAc). In Europe, the applicability of TWAc for a particular risk assessment is evaluated using a complex decision scheme, which has been controversial; thus we propose an alternative approach: We used TWAc-check (which is based on the idea that the TWAc concept is just a model for aquatic risk assessment) to test whether the use of a TWAc is appropriate for such assessment. The TWAc-check method works by using predicted-measured diagrams to test how well the TWAc model predicts experimental data from peak exposure experiments. Overestimated effects are accepted because the conservatism of the TWAc model is prioritized over the goodness of fit. We illustrate the applicability of TWAc-check by applying it to various data sets for different species and substances. We demonstrate that the applicability is case dependent. Specifically, TWAc-check correctly identifies that the use of TWAc is not appropriate for early onset of effects or delayed effects. The proposed concept shows that the time window is a decisive factor as to whether or not the model is acceptable and that this concept can be used as a potential refinement option prior to the use of toxicokinetic-toxicodynamic models. Environ Toxicol Chem 2022;41:1778-1787. © 2022 Bayer AG. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Toxicokinetics and toxicodynamics of copper and cadmium in the soil invertebrate Enchytraeus crypticus (Oligochaeta)

The aim of this study was to evaluate the toxicokinetics-toxicodynamics (TKTD) of Cu and Cd in the soil model organism Enchytraeus crypticus, and assess the development of internal effect concentrations over time. Animals were exposed in LUFA 2.2 soil spiked with increasing concentrations of Cu and Cd. Survival, reproduction and internal metal concentrations in the animals were evaluated at different points in time over a period of 21 days. Internal concentrations increased with time, for Cu reaching a steady state after c. 10 days, except for the highest test concentration, and for Cd continuing to increase after 21 days. Applying a one-compartment model to all data together, estimated uptake and elimination rate constants for Cu and Cd were 0.08 and 0.45 kg soil/kg organism/day and 0.4 and 0.04 per day, respectively. Median lethal concentrations, based on total soil concentrations, decreased with time for Cu and did not reach a steady state level, but they did not change with time for Cd. The LC50_inter (based on internal concentrations) was 75 mg Cu/kg body DW and > 800 mg Cd/kg body weight. Animals were able to regulate Cu internal concentrations, keeping them low, while for Cd internal concentrations continued to increase showing lack of regulation and also the importance of exposure time. This study highlights the advantages of using a TKTD approach to understand the relation between organism survival and internal Cu or Cd concentrations over time.

(Eco)toxicological tests for assessing impacts of chemical stress to aquatic ecosystems: Facts, challenges, and future

Monitoring of chemicals in the aquatic environment by chemical analysis alone cannot completely assess and predict the effects of chemicals on aquatic species and ecosystems. This is primarily because of the increasing number of (unknown) chemical stressors and mixture effects present in the environment. In addition, the ability of ecological indices to identify underlying stressors causing negative ecological effects is limited. Therefore, additional complementary methods are needed that can address the biological effects in a direct manner and provide a link to chemical exposure, i.e. (eco)toxicological tests. (Eco)toxicological tests are defined as test systems that expose biological components (cells, individuals, populations, communities) to (environmental mixtures of) chemicals to register biological effects. These tests measure responses at the sub-organismal (biomarkers and in vitro bioassays), whole-organismal, population, or community level. We performed a literature search to obtain a state-of-the-art overview of ecotoxicological tests available for assessing impacts of chemicals to aquatic biota and to reveal datagaps. In total, we included 509 biomarkers, 207 in vitro bioassays, 422 tests measuring biological effects at the whole-organismal level, and 78 tests at the population- community- and ecosystem-level. Tests at the whole-organismal level and biomarkers were most abundant for invertebrates and fish, whilst in vitro bioassays are mostly based on mammalian cell lines. Tests at the community- and ecosystem-level were almost missing for organisms other than microorganisms and algae. In addition, we provide an overview of the various extrapolation challenges faced in using data from these tests and suggest some forward looking perspectives. Although extrapolating the measured responses to relevant protection goals remains challenging, the combination of ecotoxicological experiments and models is key for a more comprehensive assessment of the effects of chemical stressors to aquatic ecosystems.

The toxicity and toxicokinetics of imidacloprid and a bioactive metabolite to two aquatic arthropod species

Previous studies have explored effects of imidacloprid and its metabolites on terrestrial species, such as bees, and indicated the importance of some active metabolites. However, the biotransformation of IMI and the toxicity of its metabolites to aquatic arthropods are largely unknown, especially the mechanisms driving species sensitivity differences and time-cumulative toxicity effects. To assess the potential effects of the metabolization of IMI and the toxicokinetics and toxicity of the metabolite(s) on aquatic arthropods, we first studied the acute toxicity of IMI and relevant metabolites to the mayfly species Cloen dipterum (sensitive to IMI) and the amphipod species Gammarus pulex (less sensitive to IMI). Secondly, toxicokinetic experiments were conducted using both the parent compound and imidacloprid-olefin (IMI-ole), a metabolite assessed as toxic in the acute tests and defined as bioactive. Of the four tested metabolites, only IMI-ole was readily biotransformed from the parent IMI and showed similar toxicity to C. dipterum as IMI. However, C. dipterum was hardly able to eliminate IMI-ole from its body. For G. pulex, IMI-ole was also the only detected metabolite causing toxicity, but the biotransformation of IMI to IMI-ole was slower and lower in G. pulex compared to C. dipterum, and G. pulex eliminated IMI-ole quicker than C. dipterum. Our results on internal kinetics of IMI and IMI-ole, and on biotransformation of IMI indicated that the metabolite IMI-ole was toxic and was rather persistent inside the body tissue of both invertebrate species, especially for C. dipterum. In conclusion, as IMI and IMI-ole have similar toxicity and IMI was replaced rapidly by IMI-ole which in turn was poorly eliminated by C. dipterum, the overall toxicity is a function of dose and time. As a result, no long-term threshold of effects of IMI may exist for C. dipterum as the poor elimination results in an ongoing increase of toxicity over time for mayflies as also found experimentally in previous published papers.

A simulation-based evaluation of management actions to reduce the risk of contaminants of emerging concern (CECs) to walleye in the Great Lakes Basin

Contaminants of emerging concern (CECs) are ubiquitous, present in complex chemical mixtures, and represent a threat to the Great Lake ecosystem. Mitigation strategies are needed to protect populations of key species, but knowledge about ecological and biological effects of CECs at the population level are limited. In this study, we combined laboratory data on CEC effects at the individual-level with in-situ CEC concentration data in a walleye (Sander vitreus) population model to simulate the effectiveness of different CEC mitigation strategies in the Maumee River and Lake Erie. We compared the effectiveness of moderate mitigation (50% reduction in exposure level) of an entire watershed versus intensive mitigation (reduction of exposure to a level that does not affect walleye) of single river sites for three CEC mixture scenarios (agricultural, urban, and combined). We also explored the impact of hypothetical chemical toxicokinetics (the time course of chemicals in walleye) on the relative effectiveness of the mitigation strategies. Our results suggest that when CECs impact fecundity, single-site mitigation is more effective when it focuses on spawning sites and nearby downstream sites that are substantially impaired. Our simulations also suggest that chemical toxicokinetics are important when evaluating single-site mitigation strategies, but that population characteristics, such as stage-specific mortality rate, are more important when evaluating watershed mitigation strategies. Results can be used to guide fisheries management, such as choosing habitat restoration sites, and identify key knowledge gaps that direct future research and monitoring.

A Review of Key Features and Their Implementation in Unstructured, Structured, and Agent-Based Population Models for Ecological Risk Assessment

Population models can provide valuable tools for ecological risk assessment (ERA). A growing amount of work on model development and documentation is now available to guide modelers and risk assessors to address different ERA questions. However, there remain misconceptions about population models for ERA, and communication between regulators and modelers can still be hindered by a lack of clarity in the underlying formalism, implementation, and complexity of different model types. In particular, there is confusion about differences among types of models and the implications of including or ignoring interactions of organisms with each other and their environment. In this review, we provide an overview of the key features represented in population models of relevance for ERA, which include density dependence, spatial heterogeneity, external drivers, stochasticity, life-history traits, behavior, energetics, and how exposure and effects are integrated in the models. We differentiate 3 broadly defined population model types (unstructured, structured, and agent-based) and explain how they can represent these key features. Depending on the ERA context, some model features will be more important than others, and this can inform model type choice, how features are implemented, and possibly the collection of additional data. We show that nearly all features can be included irrespective of formalization, but some features are more or less easily incorporated in certain model types. We also analyze how the key features have been used in published population models implemented as unstructured, structured, and agent-based models. The overall aim of this review is to increase confidence and understanding by model users and evaluators when considering the potential and adequacy of population models for use in ERA. Integr Environ Assess Manag 2021;17:521-540. © 2020 SETAC.

Making the Biotic Ligand Model kinetic, easier to develop, and more flexible for deriving water quality criteria

In aquatic environments, the ecological risks posed by metals are greatly affected by water chemistry, thereby creating challenges for water quality management. Biotic ligand models (BLMs) have become the most widely used tools to interpret and predict water chemistry effects. Traditional BLM development methods require a large number of toxicity tests and organisms, and model predictions are limited to certain toxicity statistics (e.g., 48-h median effective concentration, 48-h EC₅₀), to which the models were calibrated. To address these limitations, we propose a new method to develop BLMs by integrating them into the toxicokinetic-toxicodynamic (TK-TD) framework. Metal bioaccumulation was predicted from metal exposure and water chemistry using the BLM-type toxicokinetics, whilst metal toxicity was predicted from metal bioaccumulation using the toxicodynamics. Using the new method, we developed a kinetic BLM of cadmium for Daphnia magna with only six toxicity tests and 1540 daphnids; this represents a 60-80% reduction compared to the traditional methods. The model was validated in the presence of commercial dissolved organic matter (DOM) and in natural waters sampled from 12 lakes. The kinetic BLM was able to accurately simulate the protective effects of the commercial DOM by employing the Stockholm humic model, whilst the complexation capabilities of some natural DOM were overestimated. We further used the model to predict Cd EC₅₀ and no-effect concentrations for different waters, generating predictions close to the effect concentrations reported in the literature. Overall, our method requires fewer resources and presents an easier approach to develop BLMs; the kinetic BLM is more flexible and can serve as a useful tool for developing water quality criteria.

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.

Sublethal effect modelling for environmental risk assessment of chemicals: Problem definition, model variants, application and challenges

Bioenergetic models, and specifically dynamic energy budget (DEB) theory, are gathering a great deal of interest as a tool to predict the effects of realistically variable exposure to toxicants over time on an individual animal. Here we use aquatic ecological risk assessment (ERA) as the context for a review of the different model variants within DEB and the closely related DEBkiss theory (incl. reserves, ageing, size & maturity, starvation). We propose a coherent and unifying naming scheme for all current major DEB variants, explore the implications of each model's underlying assumptions in terms of its capability and complexity and analyse differences between the models (endpoints, mathematical differences, physiological modes of action). The results imply a hierarchy of model complexity which could be used to guide the implementation of simplified model variants. We provide a decision tree to support matching the simplest suitable model to a given research or regulatory question. We detail which new insights can be gained by using DEB in toxicokinetic-toxicodynamic modelling, both generally and for the specific example of ERA, and highlight open questions. Specifically, we outline a moving time window approach to assess time-variable exposure concentrations and discuss how to account for cross-generational exposure. Where possible, we suggest valuable topics for experimental and theoretical research.

Comparison Among Test Substrates in Metal Uptake and Toxicity to Folsomia candida and Hordeum vulgare

The main aim of this short review was to assess the effect of test medium on the bioavailability of metals to the soil invertebrate Folsomia candida and the barley plant Hordeum vulgare. Solution-only exposures and sand-solution media were suitable media with control survival of > 80%. Comparing toxicity and accumulation data, LC₅₀ and/or EC₅₀ values as well as internal concentrations of cadmium (Cd) and copper (Cu) were similar in the tests with different porewater composition for springtails and barley plants. Similar results for toxicity and bioaccumulation of Cd and Cu using different test substrates, suggest the importance of physiological handling of the effects by the organisms rather than the influence of test medium composition.

Mechanistic Effect Modeling Approach for the Extrapolation of Species Sensitivity

In the higher-tier environmental risk assessment of chemicals, species sensitivity distributions (SSDs) are used to statistically describe differences in sensitivity between species and derive community level endpoints. SSDs are usually based on the results from short-term laboratory experiments performed under constant environmental conditions. However, different species may be kept at different "optimal" temperatures, which influence their apparent sensitivity and thus the derivation of endpoints. Also, the extrapolation capacity of SSDs is largely limited to the tested species and conditions. Time-variable exposures and effects at higher levels of biological organization, including biological interactions, are not considered. The quantitative effect prediction at higher tiers would ultimately require the extrapolation of toxicokinetics and toxicodynamics to untested species and the involvement of population and community modeling. In this regard, we tested a toxicokinetic-toxicodynamic modeling approach to mechanistically consider and correct endpoints for ambient temperature and demonstrate the significance for SSDs. We explored correlations in toxicokinetic-toxicodynamic model parameters which would allow for the extrapolation of sensitivities to untested species. Finally, we illustrate the applicability of the approach for higher level effect predictions using an individual-based model. Our results suggest that mechanistic effect modeling approaches can reduce the uncertainties in higher tier effect assessments related to knowledge gaps.

Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment

A working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS) explored the feasibility of integrating 2 complementary approaches relevant to ecological risk assessment. Adverse outcome pathway (AOP) models provide "bottom-up" mechanisms to predict specific toxicological effects that could affect an individual's ability to grow, reproduce, and/or survive from a molecular initiating event. Dynamic energy budget (DEB) models offer a "top-down" approach that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources. Thus, AOP models quantify linkages between measurable molecular, cellular, or organ-level events, but they do not offer an explicit route to integratively characterize stressor effects at higher levels of organization. While DEB models provide the inherent basis to link effects on individuals to those at the population and ecosystem levels, their use of abstract variables obscures mechanistic connections to suborganismal biology. To take advantage of both approaches, we developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates. We report on the type and structure of data that are generated for AOP models that may also be useful for DEB models. We also report on case studies under development that merge information collected for AOPs with DEB models and highlight some of the challenges. Finally, we discuss how the linkage of these 2 approaches can improve ecological risk assessment, with possibilities for progress in predicting population responses to toxicant exposures within realistic environments. Integr Environ Assess Manag 2018;14:615-624. © 2018 SETAC.

Toward sustainable environmental quality: Priority research questions for Europe

The United Nations' Sustainable Development Goals have been established to end poverty, protect the planet, and ensure prosperity for all. Delivery of the Sustainable Development Goals will require a healthy and productive environment. An understanding of the impacts of chemicals which can negatively impact environmental health is therefore essential to the delivery of the Sustainable Development Goals. However, current research on and regulation of chemicals in the environment tend to take a simplistic view and do not account for the complexity of the real world, which inhibits the way we manage chemicals. There is therefore an urgent need for a step change in the way we study and communicate the impacts and control of chemicals in the natural environment. To do this requires the major research questions to be identified so that resources are focused on questions that really matter. We present the findings of a horizon-scanning exercise to identify research priorities of the European environmental science community around chemicals in the environment. Using the key questions approach, we identified 22 questions of priority. These questions covered overarching questions about which chemicals we should be most concerned about and where, impacts of global megatrends, protection goals, and sustainability of chemicals; the development and parameterization of assessment and management frameworks; and mechanisms to maximize the impact of the research. The research questions identified provide a first-step in the path forward for the research, regulatory, and business communities to better assess and manage chemicals in the natural environment. Environ Toxicol Chem 2018;37:2281-2295. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Spatial exposure-hazard and landscape models for assessing the impact of GM crops on non-target organisms

The cultivation of Genetically Modified (GM) crops may have substantial impacts on populations of non-target organisms (NTOs) in agroecosystems. These impacts should be assessed at larger spatial scales than the cultivated field, and, as landscape-scale experiments are difficult, if not impossible, modelling approaches are needed to address landscape risk management. We present an original stochastic and spatially explicit modelling framework for assessing the risk at the landscape level. We use techniques from spatial statistics for simulating simplified landscapes made up of (aggregated or non-aggregated) GM fields, neutral fields and NTO's habitat areas. The dispersal of toxic pollen grains is obtained by convolving the emission of GM plants and validated dispersal kernel functions while the locations of exposed individuals are drawn from a point process. By taking into account the adherence of the ambient pollen on plants, the loss of pollen due to climatic events, and, an experimentally-validated mortality-dose function we predict risk maps and provide a distribution giving how the risk varies within exposed individuals in the landscape. Then, we consider the impact of the Bt maize on Inachis io in worst-case scenarii where exposed individuals are located in the vicinity of GM fields and pollen shedding overlaps with larval emergence. We perform a Global Sensitivity Analysis (GSA) to explore numerically how our input parameters influence the risk. Our results confirm the important effects of pollen emission and loss. Most interestingly they highlight that the optimal spatial distribution of GM fields that mitigates the risk depends on our knowledge of the habitats of NTOs, and finally, moderate the influence of the dispersal kernel function.

Can Toxicokinetic and Toxicodynamic Modeling Be Used to Understand and Predict Synergistic Interactions between Chemicals?

Some chemicals are known to enhance the effect of other chemicals beyond what can be predicted with standard mixture models, such as concentration addition and independent action. These chemicals are called synergists. Up until now, no models exist that can predict the joint effect of mixtures including synergists. The aim of the present study is to develop a mechanistic toxicokinetic (TK) and toxicodynamic (TD) model for the synergistic mixture of the azole fungicide, propiconazole (the synergist), and the insecticide, α-cypermethrin, on the mortality of the crustacean Daphnia magna. The study tests the hypothesis that the mechanism of synergy is the azole decreasing the biotransformation rate of α-cypermethrin and validates the predictive ability of the model on another azole with a different potency: prochloraz. The study showed that the synergistic potential of azoles could be explained by their effect on the biotransformation rate but that this effect could only partly be explained by the effect of the two azoles on cytochrome P450 activity, measured on D. magna in vivo. TKTD models of interacting mixtures seem to be a promising tool to test mechanisms of interactions between chemicals. Their predictive ability is, however, still uncertain.

Impaired ecosystem process despite little effects on populations: modeling combined effects of warming and toxicants

Freshwater ecosystems are exposed to many stressors, including toxic chemicals and global warming, which can impair, separately or in combination, important processes in organisms and hence higher levels of organization. Investigating combined effects of warming and toxicants has been a topic of little research, but neglecting their combined effects may seriously misguide management efforts. To explore how toxic chemicals and warming, alone and in combination, propagate across levels of biological organization, including a key ecosystem process, we developed an individual-based model (IBM) of a freshwater amphipod detritivore, Gammarus pseudolimnaeus, feeding on leaf litter. In this IBM, life history emerges from the individuals' energy budgets. We quantified, in different warming scenarios (+1-+4 °C), the effects of hypothetical toxicants on suborganismal processes, including feeding, somatic and maturity maintenance, growth, and reproduction. Warming reduced mean adult body sizes and population abundance and biomass, but only in the warmest scenarios. Leaf litter processing, a key contributor to ecosystem functioning and service delivery in streams, was consistently enhanced by warming, through strengthened interaction between the detritivorous consumer and its resource. Toxicant effects on feeding and maintenance resulted in initially small adverse effects on consumers, but ultimately led to population extinction and loss of ecosystem process. Warming in combination with toxicants had little effect at the individual and population levels, but ecosystem process was impaired in the warmer scenarios. Our results suggest that exposure to the same amount of toxicants can disproportionately compromise ecosystem processing depending on global warming scenarios; for example, reducing organismal feeding rates by 50% will reduce resource processing by 50% in current temperature conditions, but by up to 200% with warming of 4 °C. Our study has implications for assessing and monitoring impacts of chemicals on ecosystems facing global warming. We advise complementing existing monitoring approaches with directly quantifying ecosystem processes and services.

Aquatic ecotoxicological models and their applicability in Arctic regions

Dose-response modeling is one of the most important steps of ecological risk assessment. It requires concentration-effects relationships for the species under consideration. There are very limited studies and experimental data available for the Arctic aquatic species. Lack of toxicity data hinders obtaining dose-response relationships for lethal (LC50 values), sub-lethal and carcinogenic effects. Gaps in toxicity data could be filled using a variety of in-silico ecotoxicological methods. This paper reviews the suitability of such methods for the Arctic scenario. Mechanistic approaches like toxicokinetic and toxicodynamic analysis are found to be better suited for interspecies extrapolation than statistical methods, such as Quantitative Structure-Activity Relationships/Quantitative Structure Activity-Activity Relationship, ICE, and other empirical models, such as Haber's law and Ostwald's equation. A novel approach is proposed where the effects of the toxicant exposure are quantified based on the probability of cellular damage and metabolites interactions. This approach recommends modeling cellular damage using a toxicodynamic model and physiology or metabolites interactions using a toxicokinetic model. Together, these models provide more reliable estimates of toxicity in the Arctic aquatic species, which will assist in conducting ecological risk assessment of Arctic environment.

Pesticide exposure assessment for surface waters in the EU. Part 2: Determination of statistically based run-off and drainage scenarios for Germany

BACKGROUND

In order to assess surface water exposure to active substances of plant protection products (PPPs) in the European Union (EU), the FOCUS (FOrum for the Co-ordination of pesticide fate models and their USe) surface water workgroup introduced four run-off and six drainage scenarios for Step 3 of the tiered FOCUSsw approach. These scenarios may not necessarily represent realistic worst-case situations for the different Member States of the EU. Hence, the suitability of the scenarios for risk assessment in the national authorisation procedures is not known.

RESULTS

Using Germany as an example, the paper illustrates how national soil-climate scenarios can be developed to model entries of active substances into surface waters from run-off and erosion (using the model PRZM) and from drainage (using the model MACRO). In the authorisation procedure for PPPs on Member State level, such soil-climate scenarios can be used to determine exposure endpoints with a defined overall percentile.

CONCLUSION

The approach allows the development of national specific soil-climate scenarios and to calculate percentile-based exposure endpoints. The scenarios have been integrated into a software tool analogous to FOCUS-SWASH which can be used in the future to assess surface water exposure in authorisation procedures of PPPs in Germany. © 2017 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Cadmium Compartmentalization in the Pulmonate Snail Lymnaea stagnalis: Improving Our Understanding of Exposure

In ecotoxicology, analytical compartmentalization analysis can be used to better understand metal sequestration and detoxification. Metals are typically found in two main compartments, biologically detoxified metal (BDM) and metal sensitive fractions (MSF). The purpose of this study was to analyze the subcellular distribution of cadmium (Cd) in Lymnaea stagnalis. Adult snails were exposed to three concentrations of Cd for 56 days as part of a global ring test for L. stagnalis. At the end of the 56-day exposure, organisms were separated in two sections (viscera and foot). Each section was subsequently divided by differential centrifugation into five total fractions including (metal rich granules, debris, Organelles, heat denatured proteins, and heat stable proteins) followed by Cd analysis. The concentration in each compartment, BDM, MSF, and bioconcentration factors were estimated as well. There was significantly higher bioconcentration of Cd in the viscera section compared with the foot. Cadmium accumulation in all five fractions also increased with increasing exposure concentrations. Cadmium accumulated the most in the heat denatured protein fraction (enzymes) and accumulated the least in the heat stable protein fraction (metallothionein-like proteins). The MSF compartment (~65%) was in higher proportion than the BDM (~30%), but only in the lowest Cd exposure concentration was there a significant difference between these compartments. The results indicated that, in general, there was more Cd accumulated in the metal sensitive fractions, and that the detoxification mechanisms were not efficient enough to avoid toxicity at the two highest concentrations. This study provides evidence that improves our understanding of Cd tissue distribution in freshwater gastropods.

Toxicokinetic models and related tools in environmental risk assessment of chemicals

Environmental risk assessment of chemicals for the protection of ecosystems integrity is a key regulatory and scientific research field which is undergoing constant development in modelling approaches and harmonisation with human risk assessment. This review focuses on state-of-the-art toxicokinetic tools and models that have been applied to terrestrial and aquatic species relevant to environmental risk assessment of chemicals. Both empirical and mechanistic toxicokinetic models are discussed using the results of extensive literature searches together with tools and software for their calibration and an overview of applications in environmental risk assessment. These include simple tools such as one-compartment models, multi-compartment models to physiologically-based toxicokinetic (PBTK) models, mostly available for aquatic species such as fish species and a number of chemical classes including plant protection products, metals, persistent organic pollutants, nanoparticles. Data gaps and further research needs are highlighted.

Heavy metals (Pb, Cd, As and MeHg) as risk factors for cognitive dysfunction: A general review of metal mixture mechanism in brain

Human exposure to toxic heavy metals is a global challenge. Concurrent exposure of heavy metals, such as lead (Pb), cadmium (Cd), arsenic (As) and methylmercury (MeHg) are particularly important due to their long lasting effects on the brain. The exact toxicological mechanisms invoked by exposure to mixtures of the metals Pb, Cd, As and MeHg are still unclear, however they share many common pathways for causing cognitive dysfunction. The combination of metals may produce additive/synergetic effects due to their common binding affinity with NMDA receptor (Pb, As, MeHg), Na⁺ - K⁺ ATP-ase pump (Cd, MeHg), biological Ca⁺² (Pb, Cd, MeHg), Glu neurotransmitter (Pb, MeHg), which can lead to imbalance between the pro-oxidant elements (ROS) and the antioxidants (reducing elements). In this process, ROS dominates the antioxidants factors such as GPx, GS, GSH, MT-III, Catalase, SOD, BDNF, and CERB, and finally leads to cognitive dysfunction. The present review illustrates an account of the current knowledge about the individual metal induced cognitive dysfunction mechanisms and analyse common Mode of Actions (MOAs) of quaternary metal mixture (Pb, Cd, As, MeHg). This review aims to help advancement in mixture toxicology and development of next generation predictive model (such as PBPK/PD) combining both kinetic and dynamic interactions of metals.

Integrated presentation of ecological risk from multiple stressors

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

The pros and cons of ecological risk assessment based on data from different levels of biological organization

Ecological risk assessment (ERA) is the process used to evaluate the safety of manufactured chemicals to the environment. Here we review the pros and cons of ERA across levels of biological organization, including suborganismal (e.g., biomarkers), individual, population, community, ecosystem and landscapes levels. Our review revealed that level of biological organization is often related negatively with ease at assessing cause-effect relationships, ease of high-throughput screening of large numbers of chemicals (it is especially easier for suborganismal endpoints), and uncertainty of the ERA because low levels of biological organization tend to have a large distance between their measurement (what is quantified) and assessment endpoints (what is to be protected). In contrast, level of biological organization is often related positively with sensitivity to important negative and positive feedbacks and context dependencies within biological systems, and ease at capturing recovery from adverse contaminant effects. Some endpoints did not show obvious trends across levels of biological organization, such as the use of vertebrate animals in chemical testing and ease at screening large numbers of species, and other factors lacked sufficient data across levels of biological organization, such as repeatability, variability, cost per study and cost per species of effects assessment, the latter of which might be a more defensible way to compare costs of ERAs than cost per study. To compensate for weaknesses of ERA at any particular level of biological organization, we also review mathematical modeling approaches commonly used to extrapolate effects across levels of organization. Finally, we provide recommendations for next generation ERA, submitting that if there is an ideal level of biological organization to conduct ERA, it will only emerge if ERA is approached simultaneously from the bottom of biological organization up as well as from the top down, all while employing mathematical modeling approaches where possible to enhance ERA. Because top-down ERA is unconventional, we also offer some suggestions for how it might be implemented efficaciously. We hope this review helps researchers in the field of ERA fill key information gaps and helps risk assessors identify the best levels of biological organization to conduct ERAs with differing goals.

Internal Concentration and Time Are Important Modifiers of Toxicity: The Case of Chlorpyrifos on Caenorhabditis elegans

The internal concentration of chemicals in exposed organisms changes over time due to absorption, distribution, metabolism, and excretion processes since chemicals are taken up from the environment. Internal concentration and time are very important modifiers of toxicity when biomarkers are used to evaluate the potential hazards and risks of environmental pollutants. In this study, the responses of molecular biomarkers, and the fate of chemicals in the body, were comprehensively investigated to determine cause-and-effect relationships over time. Chlorpyrifos (CP) was selected as a model chemical, and Caenorhabditis elegans was exposed to CP for 4 h using the passive dosing method. Worms were then monitored in fresh medium during a 48-h recovery regime. The mRNA expression of genes related to CYP metabolism (cyp35a2 and cyp35a3) increased during the constant exposure phase. The body residue of CP decreased once it reached a peak level during the early stage of exposure, indicating that the initial uptake of CP rapidly induced biotransformation with the synthesis of new CYP metabolic proteins. The residual chlorpyrifos-oxon concentration, an acetylcholinesterase (AChE) inhibitor, continuously increased even after the recovery regime started. These delayed toxicokinetics seem to be important for the extension of AChE inhibition for up to 9 h after the start of the recovery regime. Comprehensive investigation into the molecular initiation events and changes in the internal concentrations of chemical species provide insight into response causality within the framework of an adverse outcome pathway.

Demographic Toxicokinetic-Toxicodynamic Modeling of Lethal Effects

The aquatic effect assessment of chemicals is largely based on standardized measures of toxicity determined in short-term laboratory tests which are designed to reduce variability. For this purpose, uniform individuals of a species are kept under environmental and chemical exposure conditions which are as constant as possible. In nature, exposure often appears to be pulsed, effects might last longer than a few days, sensitivity might vary among different sized organisms and populations are usually size or age structured and are subject to demographic processes. To overcome this discrepancy, we tested toxicokinetic-toxicodynamic models of different complexities, including body size scaling approaches, for their ability to represent lethal effects observed for Daphnia magna exposed to triphenyltin. The consequences of the different toxicokinetic and toxicodynamic assumptions for population level responses to pulsed exposure are tested by means of an individual based model and are evaluated by confronting model predictions with population data for various pulsed exposure scenarios. We provide an example where increased model complexity reduces the uncertainty in model outputs. Furthermore, our results emphasize the importance of considering population demography in toxicokinetics and toxicodynamics for understanding and predicting potential chemical impacts at higher levels of biological organization.

Modeling Macroinvertebrate Community Dynamics in Stream Mesocosms Contaminated with a Pesticide

Modeling community dynamics of aquatic invertebrates is an important but challenging task, in particular in ecotoxicological risk assessment. Systematic parameter estimation and rigorous assessment of model uncertainty are often lacking in such applications. We applied the mechanistic food web model Streambugs to investigate the temporal development of the macroinvertebrate community in an ecotoxicological mesocosm experiment with pulsed contaminations with the insecticide thiacloprid. We used Bayesian inference to estimate parameters and their uncertainty. Approx. 85% of all experimental observations lie within the 90% uncertainty intervals indicating reasonably good fits of the calibrated model. However, a validation with independent data was not possible due to lacking data. Investigation of vital rates and limiting factors in the model yielded insights into recovery dynamics. Inclusion of the emergence process and sub-lethal effects turned out to be potentially relevant model extensions. Measurements of food source dynamics, individual body size (classes), and additional knowledge on sub-lethal effects would support more accurate modeling. This application of a process-based, ecotoxicological community model with uncertainty assessment by Bayesian inference increased our process understanding of toxicant effects in macroinvertebrate communities and helped identifying potential improvements in model structure and experimental design.

Dynamic energy-based modeling of uranium and cadmium joint toxicity to Caenorhabditis elegans

Toxicokinetic - toxicodynamic energy-based models offer new alternatives to the commonly used approaches for the analysis of mixture toxicity data. Based on the Dynamic Energy Budget theory, DEBtox models enable the description of several endpoints over time simultaneously under the same framework. However, such model still has to be faced with experimental data in a multi-contamination context. In this study, the predictive capacities of a DEBtox model to describe the uranium and cadmium joint toxicity over the entire growth and reproduction period of the soil nematode Caenorhabditis elegans was examined. The two reference additivity approaches, Concentration Addition and Response addition, implemented in the DEBtox model were tested. Assuming no interaction between the two toxicants through Response addition, the DEBtox model allowed a rather accurate fit of the U and Cd joint effects on the growth and reproduction of C. elegans: an interaction between the two metals at the toxicokinetic or toxicodynamic level seems thus unlikely or has only minor consequences. Interestingly, this study underlines that even if the compounds of a mixture share the same DEBtox physiological mode of action (in this case a decrease in assimilation), the Response addition approach may provide a better fit of joint toxicity data than the Concentration addition approach. Moreover, the present work highlighted limitations in the model predictions which are related to the simplifications of the DEBtox framework and its adaptations to the physiology of C. elegans and which lead to an overestimation of the U and Cd joint toxicity in some cases.

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.

Using toxicokinetic-toxicodynamic modeling as an acute risk assessment refinement approach in vertebrate ecological risk assessment

Recent guidance identified toxicokinetic-toxicodynamic (TK-TD) modeling as a relevant approach for risk assessment refinement. Yet, its added value compared to other refinement options is not detailed, and how to conduct the modeling appropriately is not explained. This case study addresses these issues through 2 examples of individual-level risk assessment for 2 hypothetical plant protection products: 1) evaluating the risk for small granivorous birds and small omnivorous mammals of a single application, as a seed treatment in winter cereals, and 2) evaluating the risk for fish after a pulsed treatment in the edge-of-field zone. Using acute test data, we conducted the first tier risk assessment as defined in the European Food Safety Authority (EFSA) guidance. When first tier risk assessment highlighted a concern, refinement options were discussed. Cases where the use of models should be preferred over other existing refinement approaches were highlighted. We then practically conducted the risk assessment refinement by using 2 different models as examples. In example 1, a TK model accounting for toxicokinetics and relevant feeding patterns in the skylark and in the wood mouse was used to predict internal doses of the hypothetical active ingredient in individuals, based on relevant feeding patterns in an in-crop situation, and identify the residue levels leading to mortality. In example 2, a TK-TD model accounting for toxicokinetics, toxicodynamics, and relevant exposure patterns in the fathead minnow was used to predict the time-course of fish survival for relevant FOCUS SW exposure scenarios and identify which scenarios might lead to mortality. Models were calibrated using available standard data and implemented to simulate the time-course of internal dose of active ingredient or survival for different exposure scenarios. Simulation results were discussed and used to derive the risk assessment refinement endpoints used for decision. Finally, we compared the "classical" risk assessment approach with the model-based approach. These comparisons showed that TK and TK-TD models can bring more realism to the risk assessment through the possibility to study realistic exposure scenarios and to simulate relevant mechanisms of effects (including delayed toxicity and recovery). Noticeably, using TK-TD models is currently the most relevant way to directly connect realistic exposure patterns to effects. We conclude with recommendations on how to properly use TK and TK-TD model in acute risk assessment for vertebrates.

How TK-TD and population models for aquatic macrophytes could support the risk assessment for plant protection products

This case study of the Society of Environmental Toxicology and Chemistry (SETAC) workshop MODELINK demonstrates the potential use of mechanistic effects models for macrophytes to extrapolate from effects of a plant protection product observed in laboratory tests to effects resulting from dynamic exposure on macrophyte populations in edge-of-field water bodies. A standard European Union (EU) risk assessment for an example herbicide based on macrophyte laboratory tests indicated risks for several exposure scenarios. Three of these scenarios are further analyzed using effect models for 2 aquatic macrophytes, the free-floating standard test species Lemna sp., and the sediment-rooted submerged additional standard test species Myriophyllum spicatum. Both models include a toxicokinetic (TK) part, describing uptake and elimination of the toxicant, a toxicodynamic (TD) part, describing the internal concentration-response function for growth inhibition, and a description of biomass growth as a function of environmental factors to allow simulating seasonal dynamics. The TK-TD models are calibrated and tested using laboratory tests, whereas the growth models were assumed to be fit for purpose based on comparisons of predictions with typical growth patterns observed in the field. For the risk assessment, biomass dynamics are predicted for the control situation and for several exposure levels. Based on specific protection goals for macrophytes, preliminary example decision criteria are suggested for evaluating the model outputs. The models refined the risk indicated by lower tier testing for 2 exposure scenarios, while confirming the risk associated for the third. Uncertainties related to the experimental and the modeling approaches and their application in the risk assessment are discussed. Based on this case study and the assumption that the models prove suitable for risk assessment once fully evaluated, we recommend that 1) ecological scenarios be developed that are also linked to the exposure scenarios, and 2) quantitative protection goals be set to facilitate the interpretation of model results for risk assessment.

Lethal and Sublethal Effects of Ivermectin on Onthophagus landolti (Coleoptera: Scarabaeidae)

Previous work has documented toxic effects of ivermectin (IVM) on dung beetles from the Old World, but very little is known about this drug's effect on Neotropical dung beetles. Accordingly, we conducted a bioassay with dung spiked with IVM to assess its lethal and sublethal effects on the Neotropical dung beetle Onthophagus landolti Harold. The experimental design consisted of five treated groups G1, G2, G3, G4, and G5 receiving 0.001, 0.01, 0.1, 1.0, and 10 mg IVM/kg dung fresh weight, respectively, and two control groups (solvent control [CGA] and untreated control [CGU]). Adult survival and fecundity were measured throughout a 10-d period, and subsequent egg development and survival were monitored. Adult survival was only affected for treatment groups G4 and G5 groups (70 and 30%, respectively); groups G1, G2, G3 and both controls exhibited 100% survival. Fecundity was completely suppressed under treatment groups G4 and G5. Group G3 only had 1.7 and 2.1% brood mass production relative to CGA and CGU, respectively. Additionally, for groups G1 and G2 the proportion of adults emerging from brood masses was lower relative to CGA. Furthermore, development time for the second generation in groups G1 and G2 was 12.5% slower relative to control groups. Finally, dung removal by beetles from groups G3, G4, and G5 was significantly lower relative to control groups. In conclusion, toxic effects of IVM on O. landolti are associated mainly with reduced fecundity and lower dung-removal by adult beetles as well as reduced survival and slower development of offspring.

Analyzing the effectiveness of using branchial NKA activity as a biomarker for assessing waterborne copper toxicity in tilapia (Oreochromis mossambicus): A damage-based modeling approach

Branchial Na(＋)-K(＋)-ATPase (NKA) activity has been suggested as a promising biomarker for assessing metal stress in aquatic organisms. However, studies that systematically show the effectiveness of using NKA activity to detect metal exposure and toxicity at the individual level are limited. In this study, we aimed to determine whether branchial NKA activity mechanistically responds to the accumulation of waterborne copper (Cu) and accounts for observed toxicity over time under environmentally-relevant and aquafarming Cu exposure levels (0.2, 1 and 2 mg L(-1)). Temporal trends in Cu accumulation and the corresponding responses of branchial NKA activity resulting from Cu exposure were investigated in laboratory experiments conducted on juvenile tilapia (Oreochromis mossambicus), a freshwater teleost that shows potential as a bioindicator of real-time and historical metal pollution. We used the process-based damage assessment model (DAM) to inspect the time course of Cu toxicity by integrating the compensation process between Cu-induced inhibition and repair of branchial NKA activity. NKA activity acted as a sensitive biomarker for Cu exposure and accumulation in tilapia, which showed induced impairment of osmoregulation and lethality when they were exposed to environmentally relevant levels (0.2 mg L(-1)), but not to higher exposure levels (1 and 2 mg L(-1)) in aquaculture farms or contaminated aquatic ecosystems. This study highlights the benefits and limitations of using branchial NKA activity as a sensitive biomarker to assess the health status of a fish population and its ecosystem.

An individual-based model of zebrafish population dynamics accounting for energy dynamics

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level.

Development and application of the adverse outcome pathway framework for understanding and predicting chronic toxicity: I. Challenges and research needs in ecotoxicology

To elucidate the effects of chemicals on populations of different species in the environment, efficient testing and modeling approaches are needed that consider multiple stressors and allow reliable extrapolation of responses across species. An adverse outcome pathway (AOP) is a concept that provides a framework for organizing knowledge about the progression of toxicity events across scales of biological organization that lead to adverse outcomes relevant for risk assessment. In this paper, we focus on exploring how the AOP concept can be used to guide research aimed at improving both our understanding of chronic toxicity, including delayed toxicity as well as epigenetic and transgenerational effects of chemicals, and our ability to predict adverse outcomes. A better understanding of the influence of subtle toxicity on individual and population fitness would support a broader integration of sublethal endpoints into risk assessment frameworks. Detailed mechanistic knowledge would facilitate the development of alternative testing methods as well as help prioritize higher tier toxicity testing. We argue that targeted development of AOPs supports both of these aspects by promoting the elucidation of molecular mechanisms and their contribution to relevant toxicity outcomes across biological scales. We further discuss information requirements and challenges in application of AOPs for chemical- and site-specific risk assessment and for extrapolation across species. We provide recommendations for potential extension of the AOP framework to incorporate information on exposure, toxicokinetics and situation-specific ecological contexts, and discuss common interfaces that can be employed to couple AOPs with computational modeling approaches and with evolutionary life history theory. The extended AOP framework can serve as a venue for integration of knowledge derived from various sources, including empirical data as well as molecular, quantitative and evolutionary-based models describing species responses to toxicants. This will allow a more efficient application of AOP knowledge for quantitative chemical- and site-specific risk assessment as well as for extrapolation across species in the future.

A combined toxicokinetics and toxicodynamics approach to assess the effect of porewater composition on cadmium bioavailability to Folsomia candida

The aim of the present study was to improve our understanding of cadmium bioavailability by linking toxicokinetics and toxicodynamics. The springtail Folsomia candida was exposed to different cadmium concentrations in solutions embedded in inert quartz sand. Survival and cadmium uptake in the animals were followed for 21 d. After 10 d, some animals were transferred to clean medium to assess cadmium elimination. Using a first-order one-compartment model, an overall uptake rate constant (k1) of 0.18 L kg(animal)(-1) d(-1) and an elimination rate constant (k(2-TK)) of 0.02 d(-1) were calculated. Survival decreased with time, resulting in an estimated final median lethal concentration (LC50) of 0.51 mM. A lethal body concentration (LBC) of 4.6 µmol Cd g(-1) dry body weight was estimated by multiplying the final LC50 by the bioconcentration factor (k1/k(2-TK)). The LC50(animal) values based on internal cadmium concentrations were between 3.56 µmol Cd g(-1) and 9.91 µmol Cd g(-1) dry body weight, with an overall value of 7.9 µmol Cd g(-1) dry body weight (95% confidence interval [CI]: 3.8-12.0 µmol Cd g(-1) dry body wt). Because the 95% CI of the LC50(animal) included the LBC, there was good agreement of cadmium toxicokinetics and toxicodynamics.

Modeling the contribution of toxicokinetic and toxicodynamic processes to the recovery of Gammarus pulex populations after exposure to pesticides

Because aquatic macroinvertebrates may be exposed regularly to pesticides in edge-of-the-field water bodies, an accurate assessment of potential adverse effects and subsequent population recovery is essential. Standard effect risk assessment tools are not able to fully address the complexities arising from multiple exposure patterns, nor can they properly address the population recovery process. In the present study, we developed an individual-based model of the freshwater amphipod Gammarus pulex to evaluate the consequences of exposure to 4 compounds with different modes of action on individual survival and population recovery. Effects on survival were calculated using concentration-effect relationships and the threshold damage model (TDM), which accounts for detailed processes of toxicokinetics and toxicodynamics. Delayed effects as calculated by the TDM had a significant impact on individual survival and population recovery. We also evaluated the standard assessment of effects after short-term exposures using the 96-h concentration-effect model and the TDM, which was conservative for very short-term exposure. An integration of a TKTD submodel with a population model can be used to explore the ecological relevance of ecotoxicity endpoints in different exposure environments.

Dynamic modeling of sublethal mixture toxicity in the nematode Caenorhabditis elegans

Dynamic models for toxic effects [toxicokinetic-toxicodynamic (TKTD) models] are increasingly used in the analysis of toxicity data for single-chemical exposure. However, these models also offer a natural extension to the effects of chemical mixtures. Here, we demonstrate how a simple model for the energy budget (DEBkiss) can be used to interpret the effects of cadmium and fluoranthene, in both single and mixed exposure, on the nematode Caenorhabditis elegans. The data for all time points and all end points (growth and reproduction) are combined into a single coherent framework. These modeling results are compared to a more traditional independent-action approach based on the dose-response curves for a single end point at a single time point. The analysis with DEBkiss does not lead to a radically different interpretation of the mixture effects, both indicating an antagonistic interaction in the mixture. The DEBkiss analysis does, however, provide much more insight into the relevant dynamic processes underlying the toxic effect on the organism and allows for the generation of mechanistic hypotheses that can be used to guide further research.

The ChimERA project: coupling mechanistic exposure and effect models into an integrated platform for ecological risk assessment

Current techniques for the ecological risk assessment of chemical substances are often criticised for their lack of environmental realism, ecological relevance and methodological accuracy. ChimERA is a 3-year project (2013-2016), funded by Cefic's Long Range Initiative (LRI) that aims to address some of these concerns by developing and testing mechanistic fate and effect models, and coupling of these models into one integrated platform for risk assessment. This paper discusses the backdrop against which this project was initiated and lists its objectives and planned methodology.