Effects of mine tailing exposure on the development of early life stages of the marine copepod Calanus finmarchicus.

The demand for mineral resources is increasing mining activities worldwide. In Norway, marine tailing disposal (MTD) is practiced, introducing mineral particles into fjord ecosystems. We investigated the effects of two concentrations (high and low) of fine tailings from a CaCO3 processing plant on early life stages of the marine copepod Calanus finmarchicus. Results show that the exposure did not significantly impact hatching success or development in non- and early feeding life stages. However, feeding stage nauplii ingested tailings, which caused a significantly slower development in later nauplii stages in high exposure groups, with most individuals being two stages behind the control group. Further, high mortality occurred in late nauplii and early copepodite stages in low exposure groups, which could be caused by insufficient energy accumulation and depleted energy reserves during development. Individuals exposed to high exposure concentrations seemed to survive by arresting development and potentially by reduced activity, thereby conserving energy reserves. In nature, slower development could affect lipid storage buildup and reproduction.

Modelling the effects of the pyrethroid insecticide cypermethrin on the life cycle of the soil dwelling annelid Enchytraeus crypticus, an original experimental design to calibrate a DEB-TKTD model.

The Dynamic Energy Budget theory (DEB) enables ecotoxicologists to model the effects of chemical stressors on organism life cycles through the coupling of toxicokinetic-toxicodynamic (TK-TD) models. While good progress has been made in the application of DEB-TKTD models for aquatic organisms, applications for soil fauna are scarce, due to the lack of dedicated experimental designs suitable for collecting the required time series effect data. Enchytraeids (Annelida: Clitellata) are model organisms in soil ecology and ecotoxicology. They are recognised as indicators of biological activity in soil, and chemical stress in terrestrial ecosystems. Despite this, the application of DEB-TKTD models to investigate the impact of chemicals has not yet been tested on this family. Here we assessed the impact of the pyrethroid insecticide cypermethrin on the life cycle of Enchytraeus crypticus. We developed an original experimental design to collect the data required for the calibration of a DEB-TKTD model for this species. E. crypticus presented a slow initial growth phase that has been successfully simulated with the addition of a size-dependent food limitation for juveniles in the DEB model. The DEB-TKTD model simulations successfully agreed with the data for all endpoints and treatments over time. The highlighted physiological mode of action (pMoA) for cypermethrin was an increase of the growth energy cost. The threshold for effects on survival was estimated at 73.14 mg kg- 1, and the threshold for effects on energy budget (i.e., sublethal effects) at 19.21 mg kg- 1. This study demonstrates that DEB-TKTD models can be successfully applied to E. crypticus as a representative soil species, and may improve the ecological risk assessment for terrestrial ecosystems, and our mechanistic understanding of chemical effects on non-target species.

Predicting Mixture Effects over Time with Toxicokinetic-Toxicodynamic Models (GUTS): Assumptions, Experimental Testing, and Predictive Power.

Current methods to assess the impact of chemical mixtures on organisms ignore the temporal dimension. The General Unified Threshold model for Survival (GUTS) provides a framework for deriving toxicokinetic-toxicodynamic (TKTD) models, which account for effects of toxicant exposure on survival in time. Starting from the classic assumptions of independent action and concentration addition, we derive equations for the GUTS reduced (GUTS-RED) model corresponding to these mixture toxicity concepts and go on to demonstrate their application. Using experimental binary mixture studies with Enchytraeus crypticus and previously published data for Daphnia magna and Apis mellifera, we assessed the predictive power of the extended GUTS-RED framework for mixture assessment. The extended models accurately predicted the mixture effect. The GUTS parameters on single exposure data, mixture model calibration, and predictive power analyses on mixture exposure data offer novel diagnostic tools to inform on the chemical mode of action, specifically whether a similar or dissimilar form of damage is caused by mixture components. Finally, observed deviations from model predictions can identify interactions, e.g., synergism or antagonism, between chemicals in the mixture, which are not accounted for by the models. TKTD models, such as GUTS-RED, thus offer a framework to implement new mechanistic knowledge in mixture hazard assessments.

Gill damage and delayed mortality of Northern shrimp (Pandalus borealis) after short time exposure to anti-parasitic veterinary medicine containing hydrogen peroxide.

Hydrogen peroxide (H2O2) is used as anti-parasitic veterinary medicine in salmon farms worldwide. In the period from 2009 to 2018 a total of 135 million kg of H2O2 was used in Norway, the world's largest producer of Atlantic salmon. Since the treatment water is discharged to the sea, concerns have been raised about effects of H2O2 on the coastal ecosystem. In the present study, Northern shrimp (Pandalus borealis) have been exposed to short pulses of H2O2 in the PARAMOVE® formulation, followed by a recovery period in clean seawater. The exposure concentrations represented 100, 1000 and 10 000 times dilutions of the prescribed treatment concentration for salmon; 15 mg/L, 1.5 mg/L and 0.15 mg/L H2O2. Significantly increased mortality was observed after 2 h exposure to 15 mg/L H2O2 (50%) and after 2 h exposure to 1.5 mg/L H2O2 on 3 consecutive days (33%), but no mortality was observed after 2 h exposure to 0.15 mg/L. The mortality occurred 2-4 days after the first pulse of exposure. The patterns of acute effects (immobility and death) could be captured with a toxicokinetic-toxicodynamic model (GUTS), which allows extrapolations to LC50s for constant exposure, or thresholds for effects given untested exposure profiles. Effects of H2O2 were also detected in shrimp that survived until the end of the recovery period. The feeding rate was 66% lower than in the control after 12 days of recovery for the three-pulse 1.5 mg/L exposure. Furthermore, dose dependent tissue damage was detected in the gills and evidence of lipid peroxidation in the hepatopancreas in shrimp exposed for 1 h to 1.5 mg/L and 15 mg/L and kept in recovery for 8 days. Fluorescence intensity in the hepatopancreas of treated shrimp increased 47% and 157% at 1.5 mg/L and 15 mg/L, respectively, compared to the control. Local hydrodynamic conditions will determine how fast the concentration of H2O2 will be diluted and how far it will be transported horizontally and vertically. Results from dispersion modelling (literature data) together with the current experiments indicate that treatment water with toxic concentrations of H2O2 (1.5 mg/L) could reach P. borealis living more than 1 km from a treated salmon farm.

Toxicokinetics of Crude Oil Components in Arctic Copepods.

The risk of accidental oil spills in the Arctic is on the rise due to increased shipping and oil exploration activities, making it essential to calibrate parameters for risk assessment of oil spills to Arctic conditions. The toxicokinetics of crude oil components were assessed by exposing one lipid-poor (CIII) and one lipid-rich (CV) stage of the Arctic copepod Calanus hyperboreus to crude oil WSF (water-soluble fraction). Water concentrations and total body residues (BR), as well as lipid volume fractions, were measured at regular intervals during exposure and recovery. Bioconcentration factors (BCFs) and elimination rates ( ke) for 26 petrogenic oil components were estimated from one-compartment models fitted to the BR data. Our parameters were compared to estimations made by the OMEGA bioaccumulation model, which uses the octanol-water partitioning coefficient ( KOW) in QSAR (quantitative structure-activity relationship) predictions. Our parameters for the lipid-poor CIIIs generally agreed with the OMEGA predictions, while neither the BCFs nor the kes for the lipid-rich CVs fitted within the realistic range of the OMEGA parameters. Both the uptake and elimination rates for the CVs were in general half an order of magnitude lower than the OMEGA predictions, showing an overestimation of these parameters by the OMEGA model.

Dynamic Links between Lipid Storage, Toxicokinetics and Mortality in a Marine Copepod Exposed to Dimethylnaphthalene.

Efficiently assessing and managing the risks of pollution in the marine environment requires mechanistic models for toxic effects. The General Unified Threshold model for Survival (GUTS) provides a framework for deriving toxicokinetic-toxicodynamic (TKTD) models for the end point survival. Two recurring questions in the application of GUTS concern the most appropriate death mechanism, and whether the total body residue is a proper dose metric for toxic effects. We address these questions with a case study for dimethylnaphthalene in the marine copepod Calanus finmarchicus. A detailed analysis revealed that body residues were best explained by representing copepods with two toxicokinetic compartments: separating structural biomass and lipid storage. Toxicity is most likely related to the concentration in structure, which led to identification of "stochastic death" as the most appropriate death mechanism. Interestingly, the parametrized model predicts that lipid content will have only minor influence on short-term toxicity. However, the toxicants stored in lipids may have more substantial impacts in situations not included in our experiments (e.g., during diapause and gonad maturation), and for contaminant transfer to eggs and copepod predators.

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.

Acute toxicity of dispersed crude oil on the cold-water copepod Calanus finmarchicus: Elusive implications of lipid content.

In this investigation, acute toxicity data were used from two previously reported studies where cold-water copepods were exposed to mechanically dispersed (MD) and chemically (CD) dispersed oil. In one of these studies, concentration-dependent mortality was observed, whereas no apparent relationship between exposure concentration and mortality was found in the other. The only marked difference between the studies is that copepods in the first experiment displayed a lower lipid sac volume (on average) than in the second one. In this study additional biometric data on lipid content were utilized and observed effects and toxicokinetics modeling applied in order to investigate whether differences in sensitivity between copepod cohorts might be explained by differences in lipid content. Results suggest that although a considerable lipid sac might retard toxicokinetics, the observed differences in lipid volume are not sufficient to explain differences in toxicity. Further, there are no apparent indications that acute toxic stress leads to lipid depletion, or that acute increased mortality rate selectively affects lipid-poor individuals. It is conceivable that other potential explanations exist, but the causal relationship between lipid content and increased mortality frequency remains elusive.

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 consumer­resource 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.

Body size-mediated starvation resistance in an insect predator.

Individual organisms have to endure transient periods of low-food supply with consequences for growth, reproduction and survival. To resist starvation, animals usually store resources in their bodies: the larger the animals are, the more resources they can carry, but the more energy they need to allocate for maintaining bodily functions. It is unclear how survival relates to body size when food is scarce or absent, and how to characterize individual differences in survival within a population. We use a dynamic energy budget (DEB) model to describe food acquisition, subsequent reserve dynamics and allocation of reserve to body maintenance, growth and maturation of an aquatic insect predator, Notonecta maculata. In a DEB context, we can assume that starvation-induced death strikes when the reserve of an organism is depleted to a certain extent. The way reserve dynamics change upon starvation might thereby influence the ability to survive in the absence of food. Moreover, individuals in a starved population do not die at the same time, even though they might be of the same body size with similar life histories. To describe individual differences in starvation resistance, we link the reserve dynamics derived from the DEB model to the general unified threshold model of survival (GUTS). We tested two different special cases within GUTS, individual tolerance (IT) and stochastic death (SD), and three different starvation options for their suitability in representing experimental data on body size-related starvation resistance. The DEB model reproduced laboratory data on the development of juvenile N. maculata under different food conditions well and closely predicted the weight loss of individuals during prolonged starvation. Both the combined IT-model and the combined SD-model closely fit survival for different food conditions including starvation. However, the two models make different predictions for survival under repeated transient starvation periods. Our results suggest that larger N. maculata specimens are able to resist starvation to a greater extent than smaller conspecifics. The DEB model provides a mechanistic explanation for the positive relationship between body size and starvation resistance, and offers testable hypotheses for possible deviations from this general trend.

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.

Reconsidering sufficient and optimal test design in acute toxicity testing.

In dose-response analysis, regression analysis and hypothesis testing are the main tools of choice. These methods, however, have specific requirements for the design of acute toxicity experiments. To produce meaningful results, both approaches require a constant exposure concentration over the duration of the test, and regression analysis makes an additional demand for at least two doses with partial mortality at the end of the test. These requirements, however, result from the limitations of the statistical techniques, which only use the observations at the end of the test. In practice, most standard protocols for acute testing prescribe that observations are made at several points in time (often daily). In this contribution, I demonstrate how dynamic modelling can make use of this information to produce robust estimates of LC50 as function of time, with confidence intervals, from data sets that violate the requirements for standard dose-response analysis. This form of modelling invites an entirely different, more flexible, view on experimental design, which could lead to a more efficient use of test animals and, at the same time, a stronger support for environmental risk assessment as well as the science of ecotoxicology.

Identifying and Predicting Delayed Mortality with Toxicokinetic-Toxicodynamic Models.

The prevalence of standardized toxicity testing in ecotoxicology has largely obscured the notion that toxicity is a function of time as well. The necessity of considering time is vividly demonstrated by observations of delayed mortality, that is, deaths continue to occur even when animals are no longer exposed to a toxicant. In this contribution, I explore to what extent toxicokinetic-toxicodynamic (TKTD) models from the framework of the General Unified Threshold model for Survival (GUTS) can capture delayed mortality, and to what extent this phenomenon can be predicted from short-term standard tests. I use a previously published data set for fluoroquinolones in Daphnia magna that shows strongly delayed mortality (using immobilization as a proxy for death). The model analysis shows that the GUTS stochastic death models can capture delayed mortality in the complete data set with a long recovery phase, but that the delayed effects would not have been predicted from a 2-day standard test. The study underlines the limited information content of standard acute test designs. Toxicokinetic-toxicodynamic modeling offers a handle on the time aspects of toxicity but cannot always be relied on to provide accurate extrapolations based on severely limited standard tests. The phenomenon of delayed toxicity requires more structured study to clarify its prevalence and impact; I discuss several avenues for further investigation. Environ Toxicol Chem 2024;43:1030-1035. © 2024 SETAC.

Environmental Risk Assessment with Energy Budget Models: A Comparison Between Two Models of Different Complexity.

The extrapolation of effects from controlled standard laboratory tests to real environmental conditions is a major challenge facing ecological risk assessment (ERA) of chemicals. Toxicokinetic-toxicodynamic (TKTD) models, such as those based on dynamic energy budget (DEB) theory, can play an important role in filling this gap. Through the years, different practical TKTD models have been derived from DEB theory, ranging from the full "standard" DEB animal model to simplified "DEBtox" models. It is currently unclear what impact a different level of model complexity can have on the regulatory risk assessment. In the present study, we compare the performance of two DEB-TKTD models with different levels of complexity, focusing on model calibration on standard test data and on forward predictions for untested time-variable exposure profiles. The first model is based on the standard DEB model with primary parameters, whereas the second is a reduced version with compound parameters, based on DEBkiss. After harmonization of the modeling choices, we demonstrate that these two models can achieve very similar performances both in the calibration step and in the forward prediction step. With the data presented in the present study, selection of the most suitable TKTD model for ERA therefore cannot be based alone on goodness-of-fit or on the precision of model predictions (within current ERA procedures for pesticides) but would likely be based on the trade-off between ease of use and model flexibility. We also stress the importance of modeling choices, such as how to fill gaps in the information content of experimental toxicity data and how to accommodate differences in growth and reproduction between different data sets for the same chemical-species combination. Environ Toxicol Chem 2024;43:440-449. © 2023 ibacon GmbH. Bayer AG and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Predicting population dynamics from the properties of individuals: a cross-level test of dynamic energy budget theory.

Individual-based models (IBMs) are increasingly used to link the dynamics of individuals to higher levels of biological organization. Still, many IBMs are data hungry, species specific, and time-consuming to develop and analyze. Many of these issues would be resolved by using general theories of individual dynamics as the basis for IBMs. While such theories have frequently been examined at the individual level, few cross-level tests exist that also try to predict population dynamics. Here we performed a cross-level test of dynamic energy budget (DEB) theory by parameterizing an individual-based model using individual-level data of the water flea, Daphnia magna, and comparing the emerging population dynamics to independent data from population experiments. We found that DEB theory successfully predicted population growth rates and peak densities but failed to capture the decline phase. Further assumptions on food-dependent mortality of juveniles were needed to capture the population dynamics after the initial population peak. The resulting model then predicted, without further calibration, characteristic switches between small- and large-amplitude cycles, which have been observed for Daphnia. We conclude that cross-level tests help detect gaps in current individual-level theories and ultimately will lead to theory development and the establishment of a generic basis for individual-based models and ecology.

DEBkiss or the quest for the simplest generic model of animal life history.

Understanding the life cycle of individual animals, and how it responds to stress, requires a model that causally links life-history traits (feeding, growth, development and reproduction). Dynamic Energy Budget (DEB) theory offers a powerful and formalised framework for building process-based models for organism life cycles. However, it takes some serious investment to understand the resulting equations and to implement them into software, and a substantial amount of data to parameterise. For many practical applications, there is therefore a need for further simplification. Here, we present a simple and transparent model that fully specifies the life cycle of an (invertebrate) animal, applies a strict mass balance, and has direct access to the primary parameters that determine the metabolic processes. We derive our 'DEBkiss' in a formalised manner, starting from an explicit formulation of the simplifying assumptions. The presented model can serve as a teaching tool and a smooth introduction into the much richer world of DEB theory. Furthermore, the model may prove useful as a building block for individual-based population modelling (where simplicity of the blocks is essential), and for the analysis of toxicity data (where ease of model verification and parameterisation is crucial). The model is illustrated using a fit on growth and reproduction data for the pond snail (Lymnaea stagnalis) at three food levels, and subsequent predictions for embryonic growth and respiration (oxygen use), and weight loss on starvation, for the same species.

All individuals are not created equal; accounting for interindividual variation in fitting life-history responses to toxicants.

The individuals of a species are not equal. These differences frustrate experimental biologists and ecotoxicologists who wish to study the response of a species (in general) to a treatment. In the analysis of data, differences between model predictions and observations on individual animals are usually treated as random measurement error around the true response. These deviations, however, are mainly caused by real differences between the individuals (e.g., differences in physiology and in initial conditions). Understanding these intraspecies differences, and accounting for them in the data analysis, will improve our understanding of the response to the treatment we are investigating and allow for a more powerful, less biased, statistical analysis. Here, I explore a basic scheme for statistical inference to estimate parameters governing stress that allows individuals to differ in their basic physiology. This scheme is illustrated using a simple toxicokinetic-toxicodynamic model and a data set for growth of the springtail Folsomia candida exposed to cadmium in food. This article should be seen as proof of concept; a first step in bringing more realism into the statistical inference for process-based models in ecotoxicology.

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.

Extrapolating ecotoxicological effects from individuals to populations: a generic approach based on Dynamic Energy Budget theory and individual-based modeling.

Individual-based models (IBMs) predict how dynamics at higher levels of biological organization emerge from individual-level processes. This makes them a particularly useful tool for ecotoxicology, where the effects of toxicants are measured at the individual level but protection goals are often aimed at the population level or higher. However, one drawback of IBMs is that they require significant effort and data to design for each species. A solution would be to develop IBMs for chemical risk assessment that are based on generic individual-level models and theory. Here we show how one generic theory, Dynamic Energy Budget (DEB) theory, can be used to extrapolate the effect of toxicants measured at the individual level to effects on population dynamics. DEB is based on first principles in bioenergetics and uses a common model structure to model all species. Parameterization for a certain species is done at the individual level and allows to predict population-level effects of toxicants for a wide range of environmental conditions and toxicant concentrations. We present the general approach, which in principle can be used for all animal species, and give an example using Daphnia magna exposed to 3,4-dichloroaniline. We conclude that our generic approach holds great potential for standardized ecological risk assessment based on ecological models. Currently, available data from standard tests can directly be used for parameterization under certain circumstances, but with limited extra effort standard tests at the individual would deliver data that could considerably improve the applicability and precision of extrapolation to the population level. Specifically, the measurement of a toxicant's effect on growth in addition to reproduction, and presenting data over time as opposed to reporting a single EC50 or dose response curve at one time point.