Physiological modes of action of toxic chemicals in the nematode Acrobeloides nanus

Modeling temperature-dependent life-cycle toxicity of thiamethoxam in Chironomus riparius using a DEB-TKTD model

The neonicotinoid insecticide thiamethoxam (TMX) is widely used to protect crops against insect pests. Despite some desirable properties such as its low toxicity to birds and mammals, concerns have been raised about its toxicity to non-target arthropods, including freshwater insects like chironomids. Whereas multiple studies have investigated chronic effects of neonicotinoids in chironomid larvae at standardized laboratory conditions, a better understanding of their chronic toxicity under variable temperatures and exposure is needed for coherent extrapolation from the laboratory to the field. Here, we developed a quantitative mechanistic effect model for Chironomus riparius, to simulate the species' life history under dynamic temperatures and exposure concentrations of TMX. Laboratory experiments at four different temperatures (12, 15, 20, 23 °C) and TMX concentrations between 4 and 51 µg/L were used to calibrate the model. Observed concentration-dependent effects of TMX in C. riparius included slower growth, later emergence, and higher mortality rates with increasing concentrations. Furthermore, besides a typical accelerating effect on the organisms' growth and development, higher temperatures further increased the effects associated with TMX. With some data-informed modeling decisions, most prominently the inclusion of a size dependence that makes larger animals more sensitive to TMX, the model was parametrized to convincingly reproduce the data. Experiments at both a constant (20 °C) and a dynamically increasing temperature (15-23 °C) with pulsed exposure were used to validate the model. Finally, the model was used to simulate realistic exposure conditions using two reference exposure scenarios measured in Missouri and Nebraska, utilizing a moving time window (MTW) and either a constant temperature (20 °C) or the measured temperature profiles belonging to each respective scenario. Minimum exposure multiplication factors leading to a 10% effect (EP10) in the survival at pupation, i.e., the most sensitive endpoint found in this study, were 25.67 and 21.87 for the Missouri scenario and 38.58 and 44.64 for the Nebraska scenario, when using the respective temperature assumptions. While the results illustrate that the use of real temperature scenarios does not systematically modify the EPx in the same direction (making it either more or less conservative when used as a risk indicator), the advantage of this approach is that it increases the realism and thus reduces the uncertainty associated with the model predictions.

Extrapolating Metal (Cu, Ni, Zn) Toxicity from Individuals to Populations Across Daphnia Species Using Mechanistic Models: The Roles of Uncertainty Propagation and Combined Physiological Modes of Action

Mechanistic effect modeling is a promising tool to improve the ecological realism of environmental risk assessment. An open question for the mechanistic modeling of metal toxicity is whether the same physiological mode of action (PMoA) could be assumed for closely related species. The implications of various modeling choices, such as the use of parameter point estimates and assumption of simplistic toxicodynamic models, are largely unexplored. We conducted life-table experiments with Daphnia longispina, Daphnia magna, and Daphnia pulex exposed to the single metals Cu, Ni, and Zn, and calibrated toxicokinetic-toxicodynamic (TKTD) models based on dynamic energy budget theory. We developed TKTD models with single and combined PMoAs to compare their goodness-of-fit and predicted population-level sensitivity. We identified the PMoA reproduction efficiency as most probable in all species for Ni and Zn, but not for Cu, and found that combined-PMoA models predicted higher population-level sensitivity than single-PMoA models, which was related to the predicted individual-level sensitivity, rather than to mechanistic differences between models. Using point estimates of parameters, instead of sampling from the probability distributions of parameters, could also lead to differences in the predicted population-level sensitivity. According to model predictions, apical chronic endpoints (cumulative reproduction, survival) are conservative for single-metal population effects across metals and species. We conclude that the assumption of an identical PMoA for different species of Daphnia could be justified for Ni and Zn, but not for Cu. Single-PMoA models are more appropriate than combined-PMoA models from a model selection perspective, but propagation of the associated uncertainty should be considered. More accurate predictions of effects at low concentrations may nevertheless motivate the use of combined-PMoA models. Environ Toxicol Chem 2024;43:338-358. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Extrapolation of Metal Toxicity Data for the Rotifer Brachionus calyciflorus Using an Individual-Based Population Model

Ecological risk assessment (ERA) of metals typically starts from standardized toxicity tests, the data from which are then extrapolated to derive safe concentrations for the envisioned protection goals. Because such extrapolation in conventional ERA lacks ecological realism, ecological modeling is considered as a promising new approach for extrapolation. Many published population models are complex, that is, they include many processes and parameters, and thus require an extensive dataset to calibrate. In the present study, we investigated how individual-based models based on a reduced version of the Dynamic Energy Budget theory (DEBkiss IBM) could be applied for metal effects on the rotifer Brachionus calyciflorus. Data on survival over time and reproduction at different temperatures and food conditions were used to calibrate and evaluate the model for copper effects. While population growth and decline were well predicted, the underprediction of population density and the mismatch in the onset of copper effects were attributed to the simplicity of the approach. The DEBkiss IBM was applied to toxicity datasets for copper, nickel, and zinc. Predicted effect concentrations for these metals based on the maximum population growth rate were between 0.7 and 3 times higher in all but one case (10 times higher) than effect concentrations based on the toxicity data. The size of the difference depended on certain characteristics of the toxicity data: both the steepness of the concentration-effect curve and the relative sensitivity of lethal and sublethal effects played a role. Overall, the present study is an example of how a population model with reduced complexity can be useful for metal ERA. Environ Toxicol Chem 2024;43:324-337. © 2023 SETAC.

Impact of the antidepressant Bupropion on the Dynamic Energy Budget of Daphnia magna

Psychiatric drugs are considered among the emerging contaminants of concern in ecological risk assessment, due to their potential to disrupt homeostasis in aquatic organisms. Bupropion is an antidepressant that acts by selective reuptake inhibition of norepinephrine and dopamine. Little is known about this compound's effects on aquatic organisms, despite being detected in significant concentrations in both water and biota close to waste-water treatment plants and densely populated areas. Dynamic Energy Budget (DEB) models are flexible mechanistic tools that can be applied to understand toxic effects and extrapolate individual responses to higher biological levels and under untested environmental conditions. In this work, we used the stdDEB-TKTD (an application of the DEB theory to ecotoxicology) approach to investigate the possible physiological mode of action of Bupropion on the model organism Daphnia magna. Next, Dynamic Energy Budget Individual-Based Models (DEB-IBM) were used to extrapolate the results to the population level and to predict the combined effects of Bupropion exposure and food availability on the daphnids. Our results revealed an increasing negative effect of this antidepressant on the reproduction and survival of the animals with increasing concentration (0.004, 0.058, 0.58 and 58 μM). At the population level, we found that even the lowest used doses of Bupropion could reduce the population density and its reproductive output. The impacts are predicted to be stronger under limited food conditions.

Connecting Suborganismal Data to Bioenergetic Processes: Killifish Embryos Exposed to a Dioxin-Like Compound

A core challenge for ecological risk assessment is to integrate molecular responses into a chain of causality to organismal or population-level outcomes. Bioenergetic theory may be a useful approach for integrating suborganismal responses to predict organismal responses that influence population dynamics. We describe a novel application of dynamic energy budget (DEB) theory in the context of a toxicity framework (adverse outcome pathways [AOPs]) to make quantitative predictions of chemical exposures to individuals, starting from suborganismal data. We use early-life stage exposure of Fundulus heteroclitus to dioxin-like chemicals (DLCs) and connect AOP key events to DEB processes through "damage" that is produced at a rate proportional to the internal toxicant concentration. We use transcriptomic data of fish embryos exposed to DLCs to translate molecular indicators of damage into changes in DEB parameters (damage increases somatic maintenance costs) and DEB models to predict sublethal and lethal effects on young fish. By changing a small subset of model parameters, we predict the evolved tolerance to DLCs in some wild F. heteroclitus populations, a data set not used in model parameterization. The differences in model parameters point to reduced sensitivity and altered damage repair dynamics as contributing to this evolved resistance. Our methodology has potential extrapolation to untested chemicals of ecological concern. Environ Toxicol Chem 2023;42:2040-2053. © 2023 Oak Ridge National Laboratory and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Development of a mechanistic model for analyzing avian reproduction data for pesticide risk assessment

Mechanistic effect models are increasingly recommended as tools for refining evaluations of risk from exposure to pesticides. In the context of bird and mammal risk assessments, DEB-TKTD models have been recommended for characterizing sublethal effects at lower tiers. However, there are currently no such models. Currently, chronic, multi-generational studies are performed to characterize potential effects of pesticides on avian reproduction, but it is has not been established to what extent results from these studies can inform effect models. Here, a standard Dynamic Energy Budget (DEB) model was extended to account for the avian toxicity endpoints observed in regulatory studies. We linked this new implementation to a toxicological module to capture observed pesticide effects on reproduction via a decreased efficiency of egg production. We analysed ten reproduction studies with five different pesticides conducted with the mallard (Anas platyrhynchos) and the northern bobwhite (Colinus virginianus). The new model implementation accurately distinguished between effects on egg production from direct mechanism of toxicity and from food avoidance. Due to the specific nature of regulatory studies, model applicability for risk refinement is currently limited. We provide suggestions for next steps in model development.

Population modeling to inform management and recovery efforts for lake sturgeon, Acipenser fulvescens

Lake sturgeon (Acipenser fulvescens) populations have significantly declined across their historic range, in large part due to anthropogenic impacts that have likely been exacerbated by the life-history traits of this slow-growing and long-lived species. We developed a population model to explore how Contaminants of Emerging Concern (CECs) impact lake sturgeon populations. We explored how different physiological modes of action (pMoAs) of CECs impacted population abundance and recovery and how different simulated management actions could enable recovery. We first estimated the impacts on population abundance and recovery by comparing the trajectory of an unexposed population to a population that had been exposed to a CEC with a specific pMoA after the end of the exposure. We then predicted how different management actions would impact population recovery by comparing the trajectories of an unexposed population to an exposed population for which a management action started at a fixed time without discontinuation of the exposure. Our results predicted that the individual-level pMoA of CECs has an important impact on population-level effects because different stressor's pMoA impacts the life-history traits of sturgeon differently. For example, the feeding and reproduction pMoAs caused the strongest and weakest population declines, respectively. For the same reason, pMoA also impacted recovery. For example, recovery was delayed when the pMoA was growth, maintenance, or feeding, but it was immediate when the pMoA was reproduction. We found that management actions that increased the egg survival rate or the stocking of fingerlings resulted in faster and stronger recovery than management actions that increased the juvenile or adult survival rate. This result occurred because the first two management actions immediately impacted recruitment, whereas the impact was delayed for the last two. Finally, there was greater potential for recovery when management action targeted eggs and fingerlings because these life stages have lower natural survival rates. Integr Environ Assess Manag 2022;18:1597-1608. © 2022 Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by US Government employees and their work is in the public domain in the USA.

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.

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.

Applying a mechanistic model to predict interacting effects of chemical exposure and food availability on fish populations

The potential environmental impacts of chemical exposures on wildlife are of growing concern. Freshwater ecosystems are vulnerable to chemical effects and wildlife populations, including fish, can be exposed to concentrations known to cause adverse effects at the individual level. Wild fish populations are also often subjected to numerous other stressors simultaneously which in temperate climates often include sustained periods of food limitation. The potential interactive effects of chemical exposures and food limitation on fish populations are however difficult to establish in the field. Mechanistic modelling approaches can be employed to help predict how the physiological effects of chemicals and food limitation on individuals may translate to population-level effects. Here an energy budget-individual-based model was developed and the control (no chemical) model was validated for the three-spined stickleback. Findings from two endocrine active chemical (EAC) case studies, (ethinyloestradiol and trenbolone) were then used to investigate how effects on individual fecundity translated into predicted population-level effects for environmentally relevant exposures. The cumulative effects of chemical exposure and food limitation were included in these analyses. Results show that effects of each EAC on the population were dependent on energy availability, and effects on population abundance were exacerbated by food limitation. Findings suggest that chemical effects and density dependent food competition interact to determine population responses to chemical exposures. Our study illustrates how mechanistic modelling approaches might usefully be applied to account for specific chemical effects, energy budgets and density-dependent competition, to provide a more integrated evaluation of population outcomes in chemical risk assessments.

Towards a spatiotemporally explicit toxicokinetic-toxicodynamic model for earthworm toxicity

The aim of the environmental risk assessment of chemicals is the prevention of unacceptable adverse effects on the environment. Therefore, the risk assessment for in-soil organisms, such as earthworms, is based on two key elements: the exposure assessment and the effect assessment. In the current risk assessment scheme, these two elements are not linked. While for the exposure assessment, advanced exposure models can take the spatial and temporal scale of substances into account, the effect assessment in the lower tiers considers only a limited temporal and spatial variability. However, for soil organisms, such as earthworms, those scales play a significant role as species move through the soil in response to environmental factors. To overcome this gap, we propose a conceptual integration of pesticide exposure, ecology, and toxicological effects on earthworms using a modular modeling approach. An essential part of this modular approach is the environment module, which utilizes exposure models to provide spatially and temporally explicit information on environmental variables (e.g., temperature, moisture, organic matter content) and chemical concentrations. The behavior module uses this information and simulates the feeding and movement of different earthworm species using a trait-based approach. The resulting exposure can be processed by a toxicokinetic-toxicodynamic (TKTD) module. TKTD models are particularly suitable to make effect predictions for time-variable exposure situations as they include the processes of uptake, elimination, internal distribution, and biotransformation of chemicals and link the internal concentration to an effect at the organism level. The population module incorporates existing population models of different earthworm species. The modular approach is illustrated using a case study with an insecticide. Our results emphasize that using a modular model approach will facilitate the integration of exposure and effects and thus enhance the risk assessment of soil organisms.

Modeling Sublethal Effects of Chemicals: Application of a Simplified Dynamic Energy Budget Model to Standard Ecotoxicity Data

To assess ecological risks from chemical exposure, we need tools to extrapolate from the sublethal effects observed in the laboratory under constant exposure to realistic time-varying exposures. Dynamic energy budget (DEB) theory offers a mechanistic modeling approach to describe the entire life history of a single organism and the effects of toxicant exposure. We use a simplified model, which can be wholly calibrated from standard chronic bioassay data. Case studies on standard test organisms (Americamysis bahia and Pimephales promelas) are presented to demonstrate the calibration procedure, and for the second case, data are available to pseudovalidate model performance. We use these results to highlight gaps and shortcomings in the current state of the science, and we discuss how these can be overcome to maximize the potential of DEB theory in ecological risk assessment.

Short-term Effects of Cadmium and Mercury on Soil Nematode Communities in a Pot Experiment

Analysis of soil nematode feeding groups and functional guilds were used as a valuable tool to detect heavy metal pollution. Effects of cadmium (Cd) at 5 mg/kg, mercury (Hg) at 20mg/kg, combined Cd and Hg at 5+20mg/kg on the nematode communities were studied after three months application. Nematodes were collected from soil in rhizosphere of Morning glories (Pharhiris nil) which were applied as heavy metal accumulators and were grown in the experimental pots. Both single and combined heavy metals had marked effects on the nematode abundance, life-history strategies and feeding type composition. Bacteriovores and c-p 2 group were found to be the most abundant trophic group and functional guild, respectively. Acrobeloides and Pratylenchus were the most two abundant genera, decreasing number of them was responsible for the significant difference between control and polluted treatments. Cd-5 and Cd-Hg 5+20 presented lower values of nematode diversity index (H') and evenness index (J') than Hg-20. The combination of Cd and Hg showed lower nematode trophic diversity (TD), in comparison with single Cd or Hg. Conversely, heavy metals addition exhibited no pronounced effect on Maturity index (MI), structural index (SI) and enrichment index (EI). Our results demonstrate that genera composition is a better indicator to short-term heavy metal effects than some common indicator indices and emphasize that deeper assemblage analyses are needed for a correct interpretation of short-term disturbance on soil nematodes.

Toxicokinetic-Toxicodynamic Modeling of the Effects of Pesticides on Growth of Rattus norvegicus

Ecological risk assessment is carried out for chemicals such as pesticides before they are released into the environment. Such risk assessment currently relies on summary statistics gathered in standardized laboratory studies. However, these statistics extract only limited information and depend on duration of exposure. Their extrapolation to realistic ecological scenarios is inherently limited. Mechanistic effect models simulate the processes underlying toxicity and so have the potential to overcome these issues. Toxicokinetic-toxicodynamic (TK-TD) models operate at the individual level, predicting the internal concentration of a chemical over time and the stress it places on an organism. TK-TD models are particularly suited to addressing the difference in exposure patterns between laboratory (constant) and field (variable) scenarios. So far, few studies have sought to predict sublethal effects of pesticide exposure to wild mammals in the field, even though such effects are of particular interest with respect to longer term exposure. We developed a TK-TD model based on the dynamic energy budget (DEB) theory, which can be parametrized and tested solely using standard regulatory studies. We demonstrate that this approach can be used effectively to predict toxic effects on the body weight of rats over time. Model predictions separate the impacts of feeding avoidance and toxic action, highlighting which was the primary driver of effects on growth. Such information is relevant to the ecological risk posed by a compound because in the environment alternative food sources may or may not be available to focal species. While this study focused on a single end point, growth, this approach could be expanded to include reproductive output. The framework developed is simple to use and could be of great utility for ecological and toxicological research as well as to risk assessors in industry and regulatory agencies.

Recommendations to address uncertainties in environmental risk assessment using toxicokinetic-toxicodynamic models

Providing reliable environmental quality standards (EQSs) is a challenging issue in environmental risk assessment (ERA). These EQSs are derived from toxicity endpoints estimated from dose-response models to identify and characterize the environmental hazard of chemical compounds released by human activities. These toxicity endpoints include the classical x% effect/lethal concentrations at a specific time t (EC/LC(x, t)) and the new multiplication factors applied to environmental exposure profiles leading to x% effect reduction at a specific time t (MF(x, t), or denoted LP(x, t) by the EFSA). However, classical dose-response models used to estimate toxicity endpoints have some weaknesses, such as their dependency on observation time points, which are likely to differ between species (e.g., experiment duration). Furthermore, real-world exposure profiles are rarely constant over time, which makes the use of classical dose-response models difficult and may prevent the derivation of MF(x, t). When dealing with survival or immobility toxicity test data, these issues can be overcome with the use of the general unified threshold model of survival (GUTS), a toxicokinetic-toxicodynamic (TKTD) model that provides an explicit framework to analyse both time- and concentration-dependent data sets as well as obtain a mechanistic derivation of EC/LC(x, t) and MF(x, t) regardless of x and at any time t of interest. In ERA, the assessment of a risk is inherently built upon probability distributions, such that the next critical step is to characterize the uncertainties of toxicity endpoints and, consequently, those of EQSs. With this perspective, we investigated the use of a Bayesian framework to obtain the uncertainties from the calibration process and to propagate them to model predictions, including LC(x, t) and MF(x, t) derivations. We also explored the mathematical properties of LC(x, t) and MF(x, t) as well as the impact of different experimental designs to provide some recommendations for a robust derivation of toxicity endpoints leading to reliable EQSs: avoid computing LC(x, t) and MF(x, t) for extreme x values (0 or 100%), where uncertainty is maximal; compute MF(x, t) after a long period of time to take depuration time into account and test survival under pulses with different periods of time between them.

Automated, high-throughput measurement of size and growth curves of small organisms in well plates

Organism size and growth curves are important biological characteristics. Current methods to measure organism size, and in particular growth curves, are often resource intensive because they involve many manual steps. Here we demonstrate a method for automated, high-throughput measurements of size and growth in individual aquatic invertebrates kept in microtiter well-plates. We use a spheroid counter (Cell³iMager, cc-5000) to automatically measure size of seven different freshwater invertebrate species. Further, we generated calibration curves (linear regressions, all p < 0.0001, r² >=0.9 for Ceriodaphnoa dubia, Asellus aquaticus, Daphnia magna, Daphnia pulex; r² >=0.8 for Hyalella azteca, Chironomus spec. larvae and Culex spec. larvae) to convert size measured on the spheroid counter to traditional, microscope based, length measurements, which follow the longest orientation of the body. Finally, we demonstrate semi-automated measurement of growth curves of individual daphnids (C. dubia and D. magna) over time and find that the quality of individual growth curves varies, partly due to methodological reasons. Nevertheless, this novel method could be adopted to other species and represents a step change in experimental throughput for measuring organisms’ shape, size and growth curves. It is also a significant qualitative improvement by enabling high-throughput assessment of inter-individual variation of growth.

Dynamic energy budget models in ecological risk assessment: From principles to applications

In ecological risk assessment of chemicals, hazard identification and hazard characterisation are most often based on ecotoxicological tests and expressed as summary statistics such as No Observed Effect Concentrations or Lethal Concentration values and No Effect Concentrations. Considerable research is currently ongoing to further improve methodologies to take into account toxico kinetic aspects in toxicological assessments, extrapolations of toxic effects observed on individuals to population effects and combined effects of multiple chemicals effects. In this context, the principles of the Dynamic Energy Budget (DEB), namely the conserved allocation of energy to different life-supporting processes in a wide variety of different species, have been applied successfully to the development of a number of DEB models. DEB models allow the incorporation of effects on growth, reproduction and survival within one consistent framework. This review aims to discuss the principles of the DEB theory together with available DEB models, databases available and applications in ecological risk assessment of chemicals for a wide range of species and taxa. Future perspectives are also discussed with particular emphasis on ongoing research efforts to develop DEB models as open source tools to further support the research and regulatory community to integrate quantitative biology in ecotoxicological risk assessment.

Physiological modes of action across species and toxicants: the key to predictive ecotoxicology

As ecotoxicologists we strive for a better understanding of how chemicals affect our environment. Humanity needs tools to identify those combinations of man-made chemicals and organisms most likely to cause problems. In other words: which of the millions of species are at risk from pollution? And which of the tens of thousands of chemicals contribute most to the risk? We identified our poor knowledge on physiological modes of action (how a chemical affects the energy allocation in an organism), and how they vary across species and toxicants, as a major knowledge gap. We also find that the key to predictive ecotoxicology is the systematic, rigorous characterization of physiological modes of action because that will enable more powerful in vitro to in vivo toxicity extrapolation and in silico ecotoxicology. In the near future, we expect a step change in our ability to study physiological modes of action by improved, and partially automated, experimental methods. Once we have populated the matrix of species and toxicants with sufficient physiological mode of action data we can look for patterns, and from those patterns infer general rules, theory and models.

Fish life-history traits are affected after chronic dietary exposure to an environmentally realistic marine mixture of PCBs and PBDEs

Polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) are persistent organic pollutants that have been shown to affect fish life-history traits such as reproductive success, growth and survival. At the individual level, their toxicity and underlying mechanisms of action have been studied through experimental exposure. However, the number of experimental studies approaching marine environmental situations is scarce, i.e., in most cases, individuals are exposed to either single congeners, or single types of molecules, or high concentrations, so that results can hardly be transposed to natural populations. In the present study, we evaluated the effect of chronic dietary exposure to an environmentally realistic marine mixture of PCB and PBDE congeners on zebrafish life-history traits from larval to adult stage. Exposure was conducted through diet from the first meal and throughout the life cycle of the fish. The mixture was composed so as to approach environmentally relevant marine conditions in terms of both congener composition and concentrations. Life-history traits of exposed fish were compared to those of control individuals using several replicate populations in each treatment. We found evidence of slower body growth, but to a larger asymptotic length, and delayed spawning probability in exposed fish. In addition, offspring issued from early spawning events of exposed fish exhibited a lower larval survival under starvation condition. Given their strong dependency on life-history traits, marine fish population dynamics and associated fisheries productivity for commercial species could be affected by such individual-level effects of PCBs and PBDEs on somatic growth, spawning probability and larval survival.

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.

Toxicity-based toxicokinetic/toxicodynamic assessment of bioaccumulation and nanotoxicity of zerovalent iron nanoparticles in Caenorhabditis elegans

Elucidating the relationships between the toxicity-based-toxicokinetic (TBTK)/toxicodynamic (TD) properties of engineered nanomaterials and their nanotoxicity is crucial for human health-risk analysis. Zerovalent iron (Fe⁰) nanoparticles (NPs) are one of the most prominent NPs applied in remediating contaminated soils and groundwater. However, there are concerns that Fe⁰NP application contributes to long-term environmental and human health impacts. The nematode Caenorhabditis elegans is a surrogate in vivo model that has been successfully applied to assess the potential nanotoxicity of these nanomaterials. Here we present a TBTK/TD approach to appraise bioaccumulation and nanotoxicity of Fe⁰NPs in C. elegans. Built on a present C. elegans bioassay with estimated TBTK/TD parameters, we found that average bioconcentration factors in C. elegans exposed to waterborne and food-borne Fe⁰NPs were ~50 and ~5×10^-3, respectively, whereas 10% inhibition concentrations for fertility, locomotion, and development, were 1.26 (95% CI 0.19-5.2), 3.84 (0.38-42), and 6.78 (2.58-21) μg·g^-1, respectively, implicating that fertility is the most sensitive endpoint in C. elegans. Our results also showed that biomagnification effects were not observed in waterborne or food-borne Fe⁰NP-exposed worms. We suggest that the TBTK/TD assessment for predicting NP-induced toxicity at different concentrations and conditions in C. elegans could enable rapid selection of nanomaterials that are more likely to be nontoxic in larger animals. We conclude that the use of the TBTK/TD scheme manipulating C. elegans could be used for rapid evaluation of in vivo toxicity of NPs or for drug screening in the field of nanomedicine.

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.

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.

Reproductive and developmental toxicity of the herbicide Betanal® Expert and corresponding active ingredients to Daphnia spp

The commercial herbicide formulation Betanal® Expert and its active ingredients (a.i.s) ethofumesate, phenmedipham and desmedipham were focused in this study. Following questions yielding from a previous study, an in-depth analysis of the reproductive toxicity of the pesticide was made. Long-term exposures of Daphnia magna and Daphnia longispina to Betanal® Expert, to each a.i. and to a customised mixture matching the a.i.s ratio within the commercial formulation were carried out, and deleterious effects in the offspring were recorded. This intended to clarify whether (1) the tested compounds induce reproductive injury; (2) there is interspecific variation in daphnids tolerance to the compounds; (3) there is an interaction between chemicals in combined treatments; and (4) the so-called inert ingredients added to the commercial formulation contribute to the toxicity of the herbicide. Generally, developmental impair was observed in both species (egg abortion and release of undeveloped embryos or dead offspring) at concentrations of any of the a.i.s below 1 mg L(-1). Ethofumesate was invariably the least toxic pesticide, and D. magna tended to be of slightly higher sensitivity to the exposures compared to D. longispina. Joint exposures indicated that the a.i.s can interact, inducing more than and less than additive effects for Betanal® Expert and the customised a.i. mixture, respectively. This indicates that inert ingredients co-formulating the commercial pesticide (which are absent from the customised a.i. mixture) actually contribute to its overall toxicity. This study constitutes an add-on to the discussion on the ecotoxicological framework required for authorisation of pesticide trade and usage. The results support the need to consider test species, long-term hazardous potential and toxicity of commercial formulations rather than solely that of active ingredients, as relevant variables in pesticide regulation.

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.

Variable Temperature Stress in the Nematode Caenorhabditis elegans (Maupas) and Its Implications for Sensitivity to an Additional Chemical Stressor

A wealth of studies has investigated how chemical sensitivity is affected by temperature, however, almost always under different constant rather than more realistic fluctuating regimes. Here we compared how the nematode Caenorhabditis elegans responds to copper at constant temperatures (8-24°C) and under fluctuation conditions of low (±4°C) and high (±8°C) amplitude (averages of 12, 16, 20°C and 16°C respectively). The DEBkiss model was used to interpret effects on energy budgets. Increasing constant temperature from 12-24°C reduced time to first egg, life-span and population growth rates consistent with temperature driven metabolic rate change. Responses at 8°C did not, however, accord with this pattern (including a deviation from the Temperature Size Rule), identifying a cold stress effect. High amplitude variation and low amplitude variation around a mean temperature of 12°C impacted reproduction and body size compared to nematodes kept at the matching average constant temperatures. Copper exposure affected reproduction, body size and life-span and consequently population growth. Sensitivity to copper (EC50 values), was similar at intermediate temperatures (12, 16, 20°C) and higher at 24°C and especially the innately stressful 8°C condition. Temperature variation did not increase copper sensitivity. Indeed under variable conditions including time at the stressful 8°C condition, sensitivity was reduced. DEBkiss identified increased maintenance costs and increased assimilation as possible mechanisms for cold and higher copper concentration effects. Model analysis of combined variable temperature effects, however, demonstrated no additional joint stressor response. Hence, concerns that exposure to temperature fluctuations may sensitise species to co-stressor effects seem unfounded in this case.

Predicting environmental risk: A road map for the future

Frameworks for environmental risk assessment (ERA) focus on comparing results from separate exposure and effect assessments. Exposure assessment generally relies on mechanistic fate models, whereas the effects assessment is anchored in standard test protocols and descriptive statistics. This discrepancy prevents a useful link between these two pillars of ERA, and jeopardizes the realism and efficacy of the entire process. Similar to exposure assessment, effects assessment requires a mechanistic approach to translate the output of fate models into predictions for impacts on populations and food webs. The aim of this study was to discuss (1) the central importance of the individual level, (2) different strategies of dealing with biological complexity, and (3) the role that toxicokinetic-toxicodynamic (TKTD) models, energy budgets, and molecular biology play in a mechanistic revision of the ERA framework. Consequently, an outline for a risk assessment paradigm was developed that incorporates a mechanistic effects assessment in a consistent manner, and a "roadmap for the future." Such a roadmap may play a critical role to eventually arrive at a more scientific and efficient ERA process, and needs to be used to shape our long-term research agendas.

Hormesis depends upon the life-stage and duration of exposure: Examples for a pesticide and a nanomaterial

Tests to assess toxic effects on the reproduction of adult C. elegans after 72h exposure for two chemicals, (3-(3,4-dichlorophenyl)-1,1-dimethylurea (DCMU)), also known as diuron, and silver nanoparticles (Ag NPs) indicated potential, although not significant hormesis. Follow up toxicity tests comparing the potential hormesis concentrations with controls at high replication confirmed that the stimulatory effect was repeatable and also statistically significant within the test. To understand the relevance of the hormesis effects for overall population fitness, full life-cycle toxicity tests were conducted for each chemical. When nematodes were exposed to DCMU over the full life-span, the hormesis effect for reproduction seen in short-term tests was no longer evident. Further at the putative hormesis concentrations, a negative effect of DCMU on time to maturation was also seen. For the Ag NPs, the EC50 for effects on reproduction in the life-cycle exposure was substantially lower than in the short-term test, the EC50s estimated by a three parameter log logistic model being 2.9mg/L and 0.75mg/L, respectively. This suggests that the level of toxicity for Ag NPs for C. elegans reproduction is dependant on the life stage exposed and possibly the duration of the exposure. Further, in the longer duration exposures, hormesis effects on reproduction seen in the short-term exposures were no longer apparent. Instead, all concentrations reduced both overall brood size and life-span. These results for both chemicals suggest that the hormesis observed for a single endpoint in short-term exposure may be the result of a temporary reallocation of resources between traits that are not sustained over the full life-time. Such reallocation is consistent with energy budget theories for organisms subject to toxic stress.

Susceptibility of preparasitic stages of Chordodes nobilii (Gordiida, Nematomorpha) to the fungicide carbendazim

We evaluated the effect of carbendazim on non-target organisms using the parasite Chordodes nobilii as a test organism. The Gordiida act as a link between freshwater and terrestrial ecosystems; and C. nobilii, a neotropical representative species of this group, has been shown to be sensitive to other contaminants even at environmentally acceptable concentrations. The taxa susceptible to carbendazim, however, may not be adequately represented among the standard aquatic test species used in ecotoxicological risk assessment. Moreover, the autochthonous organisms in this area that could be used as bioindicators still need to be found. The aim of the present work was therefore to assess the susceptibility of the preparasitic stages of C. nobilii to noxious effects by carbendazim. The assay protocol consisted in 96- and 48-h acute exposures of early embryonic stages and larvae, respectively, to concentrations ranging from 10 to 360 μg/l. Embryonic development was not inhibited by carbendazim at any of the evaluated concentrations, but the infectivity of larvae emerging from the exposed eggs was significantly diminished. Larval survival rate was also affected at the lowest concentration assayed. Values of the mean inhibition concentration (IC50) were 7 and 11 μg/l for embryos and larvae, respectively. Compared to other freshwater organisms, C. nobilii can be considered a species moderately to highly susceptible to carbendazim. As the expected environmental concentrations of carbendazim range from 6.25 to 41.3 μg/l, C. nobilii could well be a species in danger when exposed to this fungicide.

Considerations for test design to accommodate energy-budget models in ecotoxicology: a case study for acetone in the pond snail Lymnaea stagnalis

Toxicokinetic-toxicodynamic (TKTD) modeling offers many advantages in the analysis of ecotoxicity test data. Calibration of TKTD models, however, places different demands on test design compared with classical concentration-response approaches. In the present study, useful complementary information is provided regarding test design for TKTD modeling. A case study is presented for the pond snail Lymnaea stagnalis exposed to the narcotic compound acetone, in which the data on all endpoints were analyzed together using a relatively simple TKTD model called DEBkiss. Furthermore, the influence of the data used for calibration on accuracy and precision of model parameters is discussed. The DEBkiss model described toxic effects on survival, growth, and reproduction over time well, within a single integrated analysis. Regarding the parameter estimates (e.g., no-effect concentration), precision rather than accuracy was affected depending on which data set was used for model calibration. In addition, the present study shows that the intrinsic sensitivity of snails to acetone stays the same across different life stages, including the embryonic stage. In fact, the data on egg development allowed for selection of a unique metabolic mode of action for the toxicant. Practical and theoretical considerations for test design to accommodate TKTD modeling are discussed in the hope that this information will aid other researchers to make the best possible use of their test animals.

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.

Double trouble at high density: cross-level test of resource-related adaptive plasticity and crowding-related fitness

Population size is often regulated by negative feedback between population density and individual fitness. At high population densities, animals run into double trouble: they might concurrently suffer from overexploitation of resources and also from negative interference among individuals regardless of resource availability, referred to as crowding. Animals are able to adapt to resource shortages by exhibiting a repertoire of life history and physiological plasticities. In addition to resource-related plasticity, crowding might lead to reduced fitness, with consequences for individual life history. We explored how different mechanisms behind resource-related plasticity and crowding-related fitness act independently or together, using the water flea Daphnia magna as a case study. For testing hypotheses related to mechanisms of plasticity and crowding stress across different biological levels, we used an individual-based population model that is based on dynamic energy budget theory. Each of the hypotheses, represented by a sub-model, is based on specific assumptions on how the uptake and allocation of energy are altered under conditions of resource shortage or crowding. For cross-level testing of different hypotheses, we explored how well the sub-models fit individual level data and also how well they predict population dynamics under different conditions of resource availability. Only operating resource-related and crowding-related hypotheses together enabled accurate model predictions of D. magna population dynamics and size structure. Whereas this study showed that various mechanisms might play a role in the negative feedback between population density and individual life history, it also indicated that different density levels might instigate the onset of the different mechanisms. This study provides an example of how the integration of dynamic energy budget theory and individual-based modelling can facilitate the exploration of mechanisms behind the regulation of population size. Such understanding is important for assessment, management and the conservation of populations and thereby biodiversity in ecosystems.

Limitations of extrapolating toxic effects on reproduction to the population level

For the ecological risk assessment of toxic chemicals, standardized tests on individuals are often used as proxies for population-level effects. Here, we address the utility of one commonly used metric, reproductive output, as a proxy for population-level effects. Because reproduction integrates the outcome of many interacting processes (e.g., feeding, growth, allocation of energy to reproduction), the observed toxic effects in a reproduction test could be due to stress on one of many processes. Although this makes reproduction a robust endpoint for detecting stress, it may mask important population-level consequences if the different physiological processes stress affects are associated with different feedback mechanisms at the population level. We therefore evaluated how an observed reduction in reproduction found in a standard reproduction test translates to effects at the population level if it is caused by hypothetical toxicants affecting different physiological processes (physiological modes of action; PMoA). For this we used two consumer–resource models: the Yodzis-Innes (YI) model, which is mathematically tractable, but requires strong assumptions of energetic equivalence among individuals as they progress through ontogeny, and an individual-based implementation of dynamic energy budget theory (DEB-IBM), which relaxes these assumptions at the expense of tractability. We identified two important feedback mechanisms controlling the link between individual- and population-level stress in the YI model. These mechanisms turned out to also be important for interpreting some of the individual-based model results; for two PMoAs, they determined the population response to stress in both models. In contrast, others stress types involved more complex feedbacks, because they asymmetrically stressed the production efficiency of reproduction and somatic growth. The feedbacks associated with different PMoAs drastically altered the link between individual- and population-level effects. For example, hypothetical stressors with different PMoAs that had equal effects on reproduction had effects ranging from a negligible decline in biomass to population extinction. Thus, reproduction tests alone are of little use for extrapolating toxicity to the population level, but we showed that the ecological relevance of standard tests could easily be improved if growth is measured along with reproduction.

The use of elements as a substitute for biomass in toxicokinetic studies in small organisms

Determining pollutant concentrations in the tissues of experimental test organisms is necessary for understanding uptake and excretion mechanisms of toxicants. Using small organisms can make the determination of organism biomass inaccurate. We here propose the use of selected tissue element contents as a proxy for tissue biomass. Forty different elements were determined in tissues of the two worm species Enchytraeus crypticus and Caenorhabditis elegans derived from cultures exposed to combinations of varying temperatures and sublethal concentrations of Cu and Cd. Three criteria were used to select good biomass indicators: The element concentration must (1) be present in concentrations above the limit of quantification of the analytical method, (2) must be stable and (3) must not be affected by the treatment. If the organisms are believed to have significant amounts of soil in their gut, the element must also be present at higher concentrations in the tissue compared to the soil. The three elements K, Mg and P all lived up to the first three criteria for both worm species, showing correlation coefficients between element content and tissue biomass of 0.97, 0.96 and 0.97 (n = 25) and 0.997, 0.998 and 0.992 (n = 10) for K, Mg and P in the E. crypticus and C. elegans, respectively. Only P would be an appropriate biomass indicator for organisms with a soil gut uptake assuming the tissue concentrations in soil eating organisms are similar to those measured in the present study. Using Mg as a biomass indicator on a verification dataset of Cu and Cd uptake in E. crypticus, compared to giving Cu and Cd content per individual organism, decreased the coefficient of variation from 31 ± 21 to 21 ± 17 % and from 34 ± 22 to 9.3 ± 6.4 % for tissue Cu and Cd, respectively. We therefore conclude that the use of an element as a biomass indicator can reduce tissue concentration variability.

Mechanistic effect modeling for ecological risk assessment: where to go from here?

Mechanistic effect models (MEMs) consider the mechanisms of how chemicals affect individuals and ecological systems such as populations and communities. There is an increasing awareness that MEMs have high potential to make risk assessment of chemicals more ecologically relevant than current standard practice. Here we discuss what kinds of MEMs are needed to improve scientific and regulatory aspects of risk assessment. To make valid predictions for a wide range of environmental conditions, MEMs need to include a sufficient amount of emergence, for example, population dynamics emerging from what individual organisms do. We present 1 example where the life cycle of individuals is described using Dynamic Energy Budget theory. The resulting individual-based population model is thus parameterized at the individual level but correctly predicts multiple patterns at the population level. This is the case for both control and treated populations. We conclude that the state-of-the-art in mechanistic effect modeling has reached a level where MEMs are robust and predictive enough to be used in regulatory risk assessment. Mechanistic effect models will thus be used to advance the scientific basis of current standard practice and will, if their development follows Good Modeling Practice, be included in a standardized way in future regulatory risk assessments.

Hormesis on life-history traits: is there such thing as a free lunch?

The term "hormesis" is used to describe dose-response relationships where the response is reversed between low and high doses of a stressor (generally, stimulation at low doses and inhibition at high ones). A mechanistic explanation is needed to interpret the relevance of such responses, but there does not appear to be a single universal mechanism underlying hormesis. When the endpoint is a life-history trait such as growth or reproduction, a stimulation of the response comes with costs in terms of resources. Organisms have to obey the conservation laws for mass and energy; there is no such thing as a free lunch. Based on the principles of Dynamic Energy Budget theory, we introduce three categories of explanations for hormesis that obey the conservation laws: acquisition (i.e., increasing the input of energy into the individual), allocation (i.e., rearranging the energy flows over various traits) and medication (e.g., the stressor is an essential element or acts as a cure for a disease or infection). In this discussion paper, we illustrate these explanations with cases where they might apply, and elaborate on the potential consequences for field populations.

Effects of a bioassay-derived ivermectin lowest observed effect concentration on life-cycle traits of the nematode Caenorhabditis elegans

The pharmaceutical ivermectin is used to treat parasitic infections, such as those caused by nematodes. While several studies have demonstrated the severe effects of ivermectin on non-target organisms, little is known about the drug's impact on free-living nematodes. In the present work, a full life-cycle experiment was conducted to estimate how an ivermectin lowest observed effect concentration derived from a Caenorhabditis elegans bioassay (endpoint reproduction) might translate into effects at the population level of this free-living nematode. The results showed that fecundity decreased to levels similar to those determined in the bioassay after a time of corresponding duration (18.6 % inhibition compared to the control), but the impact then rather weakened until the end of the experiment, at which point the net reproductive rate (R(0)) was still, but not significantly, reduced by 12.4 %. Moreover, the average lifespan, length of the reproductive period, maximum daily reproduction rate, and intrinsic rate of increase (r(m)) were significantly reduced by 30.0, 25.9, 11.2, and 3.5 %, respectively. The experiment revealed that a 4-day bioassay is protective enough for C. elegans with respect to ivermectin's effects on fecundity. However, the pronounced effects of a low drug concentration on survival, a highly elastic trait, may better account for the observed population-level response, i.e., a decrease of r(m), than the effects on fecundity. These results emphasize that full life-cycle experiments are valuable for assessment of pollutants, because the effects on several life-cycle traits can be simultaneously measured and integrated into an ecologically relevant parameter, the population growth rate, that reflects a population's response to a specific pollutant.

Juvenile food limitation in standardized tests: a warning to ecotoxicologists

Standard ecotoxicological tests are as simple as possible and food sources are mainly chosen for practical reasons. Since some organisms change their food preferences during the life-cycle, they might be food limited at some stage if we do not account for such a switch. As organisms tend to respond more sensitively to toxicant exposure under food limitation, the interpretation of test results may then be biased. Using a reformulation of the von Bertalanffy model to analyze growth data of the pond snail Lymnaea stagnalis, we detected food limitation in the early juvenile phase. The snails were held under conditions proposed for a standardized test protocol, which prescribes lettuce as food source. Additional experiments showed that juveniles grow considerably faster when fed with fish flakes. The model is based on Dynamic Energy Budget (DEB) theory, which allows for mechanistic interpretation of toxic effects in terms of changes in energy allocation. In a simulation study with the DEB model, we compared the effects of three hypothetical toxicants in different feeding situations. The initial food limitation when fed with lettuce always intensified the effect of the toxicants. When fed with fish flakes, the predicted effect of the toxicants was less pronounced. From this study, we conclude that (i) the proposed test conditions for L. stagnalis are not optimal, and require further investigation, (ii) fish flakes are a better food source for juvenile pond snails than lettuce, (iii) analyzing data with a mechanistic modeling approach such as DEB allows identifying deviations from constant conditions, (iv) being unaware of food limitation in the laboratory can lead to an overestimation of toxicity in ecotoxicological tests.

How does growth temperature affect cadmium toxicity measured on different life history traits in the soil nematode Caenorhabditis elegans?

Environmental factors, in particular temperature, have been shown to affect the toxicity of chemicals. In the present study the authors exposed the nematode Caenorhabditis elegans to five concentrations of Cd (2, 4, 6, 8, and 10 mg Cd/L agar) at four constant temperatures (11, 15, 18, and 21°C) and monitored survival and reproduction on a daily basis. Data were incorporated in a population matrix model to determine the population growth rate (PGR). An additional experiment at 15 and 20°C and 0, 1, 5, and 10 mg Cd/L was performed to include growth measurements in order to relate changes in reproduction to resource allocations between investments in growth and reproduction. The impacts of Cd on PGR increased with increasing temperature, shifting the median effective concentration (EC50) for PGR from 11.6 ± 5.4 and 9.2 ± 1.3 at 11°C and 15°C, to 2.1 ± 0.1 and 1.7 ± 0.4 at 18°C and 21°C. Cadmium and temperature decreased growth rates, but Cd also increased maturation times and decreased final body size. It is hypothesized that Cd toxicity leads to a decrease in nutrient assimilation and that this "chemical anorexia" is more severe at high temperatures, where energy demands for growth and reproduction are the highest.

Biology-based modeling to analyze uranium toxicity data on Daphnia magna in a multigeneration study

Recent studies have investigated chronic toxicity of waterborne depleted uranium on the life cycle and physiology of Daphnia magna. In particular, a reduction in food assimilation was observed. Our aims here were to examine whether this reduction could fully account for observed effects on both growth and reproduction, for three successive generations, and to investigate through microscope analyses whether this reduction resulted from direct damage to the intestinal epithelium. We analyzed data obtained by exposing Daphnia magna to uranium over three successive generations. We used energy-based models, which are both able to fit simultaneously growth and reproduction and are biologically relevant. Two possible modes of action were compared - decrease in food assimilation rate and increase in maintenance costs. In our models, effects were related either to internal concentration or to exposure concentration. The model that fitted the data best represented a decrease in food assimilation related to exposure concentration. Furthermore, observations of consequent histological damage to the intestinal epithelium, together with uranium precipitates in the epithelial cells, supported the assumption that uranium has direct effects on the digestive tract. We were able to model the data in all generations and showed that sensitivity increased from one generation to the next, in particular through a significant increase of the intensity of effect, once the threshold for appearance of effects was exceeded.

Application of physiologically based modelling and transcriptomics to probe the systems toxicology of aldicarb for Caenorhabditis elegans (Maupas 1900)

The toxicity of aldicarb on movement, life cycle, population growth rate and resource allocation, and the gene expression changes underpinning these effects, were investigated for Caenorhabditis elegans. A clear effect of aldicarb on nematode movement was found suggesting that this pesticide acts as a neurotoxicant. Aldicarb also had an effect on life cycle traits including low concentration life-span extension; high concentration brood size reduction and a high concentration extension of time to first egg. All life-cycle and growth data were integrated into a biology-based model (DEBtox) to characterise aldicarb effects on life-history traits, resource allocation and population growth rate within a single modelling framework. The DEBtox fits described concentration dependent effects on individual traits and population growth rate and indicated that the most probable mechanism of action of the pesticide was an increase in energy demands for somatic and reproductive tissue maintenance. Transcriptomic profiling indicated that aldicarb was associated with changes in amino acid metabolism, DNA structure, fatty acid metabolism and cytochrome P450 mediated xenobiotic metabolism. The changes in the amino acid and fatty acid pathways suggest an effect of aldicarb on protein integrity; while effects on DNA suggests that aldicarb influence DNA morphology or replication. Both these effects have the potential to incur increased costs for structural maintenance of macromolecules. These effects, coupled to the effect on biotransformation enzymes also seen, represent the materialisation of the maintenance costs indicated by DEBtox modelling.

Extrapolating toxic effects on individuals to the population level: the role of dynamic energy budgets

The interest of environmental management is in the long-term health of populations and ecosystems. However, toxicity is usually assessed in short-term experiments with individuals. Modelling based on dynamic energy budget (DEB) theory aids the extraction of mechanistic information from the data, which in turn supports educated extrapolation to the population level. To illustrate the use of DEB models in this extrapolation, we analyse a dataset for life cycle toxicity of copper in the earthworm Dendrobaena octaedra. We compare four approaches for the analysis of the toxicity data: no model, a simple DEB model without reserves and maturation (the Kooijman-Metz formulation), a more complex one with static reserves and simplified maturation (as used in the DEBtox software) and a full-scale DEB model (DEB3) with explicit calculation of reserves and maturation. For the population prediction, we compare two simple demographic approaches (discrete time matrix model and continuous time Euler-Lotka equation). In our case, the difference between DEB approaches and population models turned out to be small. However, differences between DEB models increased when extrapolating to more field-relevant conditions. The DEB3 model allows for a completely consistent assessment of toxic effects and therefore greater confidence in extrapolating, but poses greater demands on the available data.

Crucial role of mechanisms and modes of toxic action for understanding tissue residue toxicity and internal effect concentrations of organic chemicals

This article reviews the mechanistic basis of the tissue residue approach for toxicity assessment (TRA). The tissue residue approach implies that whole-body or organ concentrations (residues) are a better dose metric for describing toxicity to aquatic organisms than is the aqueous concentration typically used in the external medium. Although the benefit of internal concentrations as dose metrics in ecotoxicology has long been recognized, the application of the tissue residue approach remains limited. The main factor responsible for this is the difficulty of measuring internal concentrations. We propose that environmental toxicology can advance if mechanistic considerations are implemented and toxicokinetics and toxicodynamics are explicitly addressed. The variability in ecotoxicological outcomes and species sensitivity is due in part to differences in toxicokinetics, which consist of several processes, including absorption, distribution, metabolism, and excretion (ADME), that influence internal concentrations. Using internal concentrations or tissue residues as the dose metric substantially reduces the variability in toxicity metrics among species and individuals exposed under varying conditions. Total internal concentrations are useful as dose metrics only if they represent a surrogate of the biologically effective dose, the concentration or dose at the target site. If there is no direct proportionality, we advise the implementation of comprehensive toxicokinetic models that include deriving the target dose. Depending on the mechanism of toxicity, the concentration at the target site may or may not be a sufficient descriptor of toxicity. The steady-state concentration of a baseline toxicant associated with the biological membrane is a good descriptor of the toxicodynamics of baseline toxicity. When assessing specific-acting and reactive mechanisms, additional parameters (e.g., reaction rate with the target site and regeneration of the target site) are needed for characterization. For specifically acting compounds, intrinsic potency depends on 1) affinity for, and 2) type of interaction with, a receptor or a target enzyme. These 2 parameters determine the selectivity for the toxic mechanism and the sensitivity, respectively. Implementation of mechanistic information in toxicokinetic-toxicodynamic (TK-TD) models may help explain time-delayed effects, toxicity after pulsed or fluctuating exposure, carryover toxicity after sequential pulses, and mixture toxicity. We believe that this mechanistic understanding of tissue residue toxicity will lead to improved environmental risk assessment.

Impacts of metal oxide nanoparticles on marine phytoplankton

Information on the toxicity of environmentally relevant concentrations of nanoparticles in marine ecosystems is needed for informed regulation of these emerging materials. We tested the effects of two types of metal oxide nanoparticles, TiO(2) and ZnO, on population growth rates of four species of marine phytoplankton representing three major coastal groups (diatoms, chlorophytes, and prymnesiophytes). These metal oxide nanoparticles (NPs) are becoming common components in many industrial, household, and cosmetic products that are released into coastal ecosystems. Titania NPs showed no measurable effect on growth rates of any species, while ZnO NPs significantly depressed growth rate of all four species. ZnO NPs aggregated rapidly in seawater, forming particles >400 nm hydrodynamic diameter within 30 min, and dissolved quickly, reaching equilibrium concentrations within 12 h. Toxicity of ZnO NPs to phytoplankton was likely due to dissolution, release, and uptake of free zinc ions, but specific nanoparticulate effects may be difficult to disentangle from effects due to free zinc ions. A modeling approach based on a Dynamic Energy Budget (DEB) framework was used to estimate sublethal effects of the two NPs on phytoplankton populations. Concentrations that were estimated to have no effect on population growth (NEC) were (one standard error in parentheses) 428 (58) μg L(-1) ZnO for the diatom Skeletonema marinoi and 223 (56) μg L(-1) for Thalassiosira pseudonana. NEC could not be estimated for the other taxa but were within the range of 500-1000 μg L(-1). Our results suggest that effects of metal oxide NPs on marine organisms is likely to vary with particle type and organism taxonomy.