Integrating the lethal and sublethal effects of toxic compounds into the population dynamics of Daphnia magna: A combination of the DEBtox and matrix population models

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.

Combining short-term bioassays using fish and crustacean model organisms with ToxCast in vitro data and broad-spectrum chemical analysis for environmental risk assessment of the river water (Sava, Croatia)

This study focused on the short-term whole organism bioassays (WOBs) on fish (Danio rerio) and crustaceans (Gammarus fossarum and Daphnia magna) to assess the negative biological effects of water from the major European River Sava and the comparison of the obtained results with in vitro toxicity data (ToxCast database) and Risk Quotient (RQ) methodology. Pollution profiles of five sampling sites along the River Sava were assessed by simultaneous chemical analysis of 562 organic contaminants (OCs) of which 476 were detected. At each sampling site, pharmaceuticals/illicit drugs category was mostly represented by their cumulative concentration, followed by categories industrial chemicals, pesticides and hormones. An exposure-activity ratio (EAR) approach based on ToxCast data highlighted steroidal anti-inflammatory drugs, antibiotics, antiepileptics/neuroleptics, industrial chemicals and hormones as compounds with the highest biological potential. Summed EAR-based prediction of toxicity showed a good correlation with the estimated toxicity of assessed sampling sites using WOBs. WOBs did not exhibit increased mortality but caused various sub-lethal biological responses that were dependant relative to the sampling site pollution intensity as well as species sensitivity. Exposure of G. fossarum and D. magna to river water-induced lower feeding rates increased GST activity and TBARS levels. Zebrafish D. rerio embryo exhibited a significant decrease in heartbeat rate, failure in pigmentation formation, as well as inhibition of ABC transporters. Nuclear receptor activation was indicated as the biological target of greatest concern based on the EAR approach. A combined approach of short-term WOBs, with a special emphasis on sub-lethal endpoints, and chemical characterization of water samples compared against in vitro toxicity data from the ToxCast database and RQs can provide a comprehensive insight into the negative effect of pollutants on aquatic organisms.

Evaluation of the combined effect of elevated temperature and cadmium toxicity on Daphnia magna using a simplified DEBtox model

Thermal discharge and heatwaves under climate change may increase water temperature. In this study, the individual and combined effect of elevated temperature and cadmium (Cd) toxicity on somatic growth and reproduction of Daphnia magna was evaluated using a simplified dynamic energy budget model (DEBtox). The model predicted that the maximum body length (L_m) would be shorter (3.705 mm) at an elevated temperature of 25 °C than at 20 °C (3.974 mm), whereas the maximum reproduction rate (R˙_m) would be higher at 25 °C (5.735) than at 20 °C (5.591). The somatic growth and reproduction of D. magna were significantly (p < 0.05) reduced with increasing Cd concentrations, and the reduction was greater at 25 than at 20 °C. Potentiation of Cd toxicity by elevated temperature was correctly simulated by assuming four toxicological modes of action influencing assimilation, somatic maintenance and growth, and reproduction. Overall, the population growth rate of D. magna was expected to decrease linearly with increasing Cd concentrations, and the decrease was expected to be higher at 25 than at 20 °C. These findings suggest a significant ecological risk of toxic metals at elevated temperature, with a mechanistic interpretation of the potentiation effect using a DEBtox modeling approach.

A tale of two metrics: the EPA Risk Quotient Approach versus the delay in Population Growth Index for determination of pesticide risk to aquatic species

The potential risk that two closely related insecticides, spinetoram and spinosad, posed to three Cladoceran species, Ceriodaphnia dubia, Daphnia pulex, and D. magna was determined using two approaches, the USEPA Risk Quotient method and the Delay in Population Growth Index (DPGI). Results of the RQ method showed that spinetoram posed a risk to all three species, but spinosad posed a risk only to C. dubia. The DPGI analysis showed that exposure to spinetoram resulted in populations of all three species being delayed ≥ 3 generation times. Exposure to the LC₅₀ and the lower 95% CL resulted in delayed populations while exposure to the upper 95% CL concentration of spinetoram resulted in no recovery of any of the three species over the course of the modeling exercise (88 d). Exposure to the lower and upper 95% Cl and the LC₅₀ of spinosad resulted in C. dubia populations being delayed ≥ 3 generations. D. pulex populations were not negatively affected after exposure to spinosad. D. magna populations were delayed ≥ 3 generations, but only after exposure to the upper 95% Cl of spinosad. These results illustrate that although the EPA risk quotient method indicated that spinetoram posed a risk to all three species and that spinosad only posed a risk to C. dubia, the DPGI showed that D. magna would be negatively affected by spinosad and none of the three species would reach a predetermined number of individuals after exposure to the upper 95% CL of spinetoram. Because the DPGI uses the 95% Cl as well as the LC₅₀ in its calculation and produces a measure of population growth it provides more detailed information in terms of the potential risk of pesticides to populations than the RQ method.

Interactive Metal Mixture Toxicity to Daphnia magna Populations as an Emergent Property in a Dynamic Energy Budget Individual-Based Model

Environmental risk assessment of metal mixtures is challenging due to the large number of possible mixtures and interactions. Mixture toxicity data cannot realistically be generated for all relevant scenarios. Therefore, methods for prediction of mixture toxicity from single-metal toxicity data are needed. We tested how well toxicity of Cu-Ni-Zn mixtures to Daphnia magna populations can be predicted based on the Dynamic Energy Budget theory with an individual-based model (DEB-IBM), assuming non-interactivity of metals on the physiological level. We exposed D. magna populations to Cu, Ni, and Zn and their mixture at a fixed concentration ratio. We calibrated the DEB-IBM with single-metal data and generated blind predictions of mixture toxicity (population size over time), with account for uncertainty. We compared the predictive performance of the DEB-IBM with respect to mixture effects on population density and population growth rates with that of two reference models applied on the population level, independent action and concentration addition. Our inferred physiological modes of action (pMoA) differed from literature-reported pMoAs, raising the question of whether this is a result of different model selection approaches, intraspecific variability, or whether different pMoAs might actually drive toxicity in a population context. Observed mixture effects were concentration- and endpoint-dependent. The independent action was overall more accurate than the concentration addition but concentration addition-predicted effects on population growth rate were slightly better. The DEB-IBM most accurately predicted effects on 6-week density, including antagonistic effects at high concentrations, which emerged from non-interactivity at the physiological level. Mixture effects on initial population growth rate appear to be more difficult to predict. To explain why model accuracy is endpoint-dependent, relationships between individual-level and population-level endpoints should be illuminated. Environ Toxicol Chem 2021;40:3034-3048. © 2021 SETAC.

Bioenergetics-adverse outcome pathway: Linking organismal and suborganismal energetic endpoints to adverse outcomes

Adverse outcome pathways (AOPs) link toxicity across levels of biological organization, and thereby facilitate the development of suborganismal responses predictive of whole-organism toxicity and provide the mechanistic information necessary for science-based extrapolation to population-level effects. Thus far AOPs have characterized various acute and chronic toxicity pathways; however, the potential for AOPs to explicitly characterize indirect, energy-mediated effects from toxicants has yet to be fully explored. Indeed, although exposure to contaminants can alter an organism's energy budget, energetic endpoints are rarely incorporated into ecological risk assessment because there is not an integrative framework for linking energetic effects to organismal endpoints relevant to risk assessment (e.g., survival, reproduction, growth). In the present analysis, we developed a generalized bioenergetics-AOP in an effort to make better use of energetic endpoints in risk assessment, specifically exposure scenarios that generate an energetic burden to organisms. To evaluate empirical support for a bioenergetics-AOP, we analyzed published data for links between energetic endpoints across levels of biological organization. We found correlations between 1) cellular energy allocation and whole-animal growth, and 2) metabolic rate and scope for growth. Moreover, we reviewed literature linking energy availability to nontraditional toxicological endpoints (e.g., locomotor performance), and found evidence that toxicants impair aerobic performance and activity. We conclude by highlighting current knowledge gaps that should be addressed to develop specific bioenergetics-AOPs. Environ Toxicol Chem 2019;38:27-45. © 2018 SETAC.

Coupling toxicokinetic-toxicodynamic and population models for assessing aquatic ecological risks to time-varying pesticide exposures

Population modeling evaluations of pesticide exposure time series were compared with aspects of a currently used risk assessment process. The US Environmental Protection Agency's Office of Pesticide Programs models daily aquatic 30-yr pesticide exposure distributions in its risk assessments, but does not routinely make full use of the information in such time series. We used mysid shrimp Americamysis bahia toxicity and demographic data to demonstrate the value of a toxicokinetic-toxicodynamic model coupled with a series of matrix population models in risk assessment refinements. This species is a small epibenthic marine crustacean routinely used in regulatory toxicity tests. We demonstrate how the model coupling can refine current risk assessments using only existing standard regulatory toxicity test results. Several exposure scenarios (each with the same initial risk characterization as determined by a more traditional organism-based approach) were created within which population modeling documented risks different from those of assessments based on the traditional approach. We also present different acute and chronic toxicity data scenarios by which toxicokinetic-toxicodynamic coupled with population modeling can distinguish responses that traditional risk evaluations are not designed to detect. Our results reinforce the benefits of this type of modeling in risk evaluations, especially related to time-varying exposure concentrations. Environ Toxicol Chem 2018;37:2633-2644. Published 2018 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

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.

The Role of AChE in Swimming Behavior of Daphnia magna: Correlation Analysis of Both Parameters Affected by Deltamethrin and Methomyl Exposure

The unpredictable toxicity of insecticides may cause behavior disorder of biological organisms. In order to assess the role of acetylcholinesterase (AChE) in swimming behavior of Daphnia magna, a correlation analysis of both parameters in 24 h exposure of deltamethrin (DM) and methomyl (MT) was investigated. The behavior responses of D. magna in DM (13.36 μg/L and 33.40 μg/L) and MT (19.66 μg/L and 49.15 μg/L) suggested that recovery behavior in the adjustment phase was crucial, and behavior homeostasis provided them with an optimal way to achieve a wider tolerance against environmental stress. During the experiment, positive effects on AChE activity occurred in the beginning of the exposure. Even though the de novo synthesis of AChE in D. magna might help it recover, the AChE inhibition in different treatments could be observed. Some induction effects on AChE activity at the beginning of exposure occurred, and a 50% decrease may cause toxic effects on behavior. In most treatments, the results showed that both behavior strength and AChE activity stayed in the same field within a correlation circle. These results illustrated that the environmental stress caused by both DM and MT could inhibit AChE activity and subsequently induce a stepwise behavior response, though both pesticides affect it as direct and indirect inhibitors, respectively.

A dynamic energy-based model to analyze sublethal effects of chronic gamma irradiation in the nematode Caenorhabditis elegans

Understanding how toxic contaminants affect wildlife species at various levels of biological organization (subcellular, histological, physiological, organism, and population levels) is a major research goal in both ecotoxicology and radioecology. A mechanistic understanding of the links between different observed perturbations is necessary to predict the consequences for survival, growth, and reproduction, which are critical for population dynamics. In this context, experimental and modeling studies were conducted using the nematode Caenorhabditis elegans. A chronic exposure to external gamma radiation was conducted under controlled conditions. Results showed that somatic growth and reproduction were reduced with increasing dose rate. Modeling was used to investigate whether radiation effects might be assessed using a mechanistic model based upon the dynamic energy budget (DEB) theory. A DEB theory in toxicology (DEB-tox), specially adapted to the case of gamma radiation, was developed. Modelling results demonstrated the suitability of DEB-tox for the analysis of radiotoxicity and suggested that external gamma radiation predominantly induced a direct reduction in reproductive capacity in C. elegans and produced an increase in costs for growth and maturation, resulting in a delay in growth and spawning observed at the highest tested dose rate.

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

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

Modelling algae-duckweed interaction under chemical pressure within a laboratory microcosm

Contaminant effects on species are generally assessed with single-species bioassays. As a consequence, interactions between species that occur in ecosystems are not taken into account. To investigate the effects of contaminants on interacting species dynamics, our study describes the functioning of a 2-L laboratory microcosm with two species, the duckweed Lemna minor and the microalgae Pseudokirchneriella subcapitata, exposed to cadmium contamination. We modelled the dynamics of both species and their interactions using a mechanistic model based on coupled ordinary differential equations. The main processes occurring in this two-species microcosm were thus formalised, including growth and settling of algae, growth of duckweeds, interspecific competition between the two species and cadmium effects. We estimated model parameters by Bayesian inference, using simultaneously all the data issued from multiple laboratory experiments specifically conducted for this study. Cadmium concentrations ranged between 0 and 50 μg·L(-1). For all parameters of our model, we obtained biologically realistic values and reasonable uncertainties. Only duckweed dynamics was affected by interspecific competition, while algal dynamics was not impaired. Growth rate of both species decreased with cadmium concentration, as well as competition intensity showing that the interspecific competition pressure on duckweed decreased with cadmium concentration. This innovative combination of mechanistic modelling and model-guided experiments was successful to understand the algae-duckweed microcosm functioning without and with contaminant. This approach appears promising to include interactions between species when studying contaminant effects on ecosystem functioning.

Variation in variance means more than mean variations: what does variability tell us about population health status?

In environmental science, the variability of biological responses in natural or laboratory populations is a well known and documented phenomenon. However, while an extensive literature aims to explain and understand the origin of variability, few try to use it as a demonstration of the population's response facing a stress. We propose here a theoretical framework that explores various patterns of variability both within and among populations, and seeks methods useful in bioevaluation methodologies. We also introduce the concept of "ecotoxicological niche" to characterize the ability of a population to endure contamination.

In vitro-to-in vivo correlation of the skin penetration, liver clearance and hepatotoxicity of caffeine

This work illustrates the use of Physiologically-Based Toxicokinetic (PBTK) modelling for the healthy Caucasian population in in vitro-to-in vivo correlation of kinetic measures of caffeine skin penetration and liver clearance (based on literature experiments), as well as dose metrics of caffeine-induced measured HepaRG toxicity. We applied a simple correlation factor to quantify the in vitro and in vivo differences in the amount of caffeine permeated through the skin and concentration-time profiles of caffeine in the liver. We developed a multi-scale computational approach by linking the PBTK model with a Virtual Cell-Based Assay to relate an external oral and dermal dose with the measured in vitro HepaRG cell viability. The results revealed higher in vivo skin permeation profiles than those determined in vitro using identical exposure conditions. Liver clearance of caffeine derived from in vitro metabolism rates was found to be much slower than the optimised in vivo clearance with respect to caffeine plasma concentrations. Finally, HepaRG cell viability was shown to remain almost unchanged for external caffeine doses of 5-400 mg for both oral and dermal absorption routes. We modelled single exposure to caffeine only.

Three-dimensional analysis of the swimming behavior of Daphnia magna exposed to nanosized titanium dioxide

Due to their surface characteristics, nanosized titanium dioxide particles (nTiO₂) tend to adhere to biological surfaces and we thus hypothesize that they may alter the swimming performance and behavior of motile aquatic organisms. However, no suitable approaches to address these impairments in swimming behavior as a result of nanoparticle exposure are available. Water fleas Daphnia magna exposed to 5 and 20 mg/L nTiO₂ (61 nm; polydispersity index: 0.157 in 17.46 mg/L stock suspension) for 96 h showed a significantly (p<0.05) reduced growth rate compared to a 1-mg/L treatment and the control. Using three-dimensional video observations of swimming trajectories, we observed a treatment-dependent swarming of D. magna in the center of the test vessels during the initial phase of the exposure period. Ensemble mean swimming velocities increased with increasing body length of D. magna, but were significantly reduced in comparison to the control in all treatments after 96 h of exposure. Spectral analysis of swimming velocities revealed that high-frequency variance, which we consider as a measure of swimming activity, was significantly reduced in the 5- and 20-mg/L treatments. The results highlight the potential of detailed swimming analysis of D. magna for the evaluation of sub-lethal mechanical stress mechanisms resulting from biological surface coating and thus for evaluating the effects of nanoparticles in the aquatic environment.

Rapid phenotypic changes in Caenorhabditis elegans under uranium exposure

Pollutants can induce selection pressures on populations, and the effects may be concentration-dependant. The main ways to respond to the stress are acclimation (i.e. plastic changes) and adaptation (i.e. genetic changes). Acclimation provides a short-term response to environmental changes and adaptation can have longer-term implications on the future of the population. One way of studying these responses is to conduct studies on the phenotypic changes occurring across generations in populations experimentally subjected to a selective factor (i.e. multigenerational test). To our knowledge, such studies have not been performed with uranium (U). Here, the phenotypic changes were explored across three generations in experimental Caenorhabditis elegans populations exposed to different U-concentrations. Significant negative effects of U were detected on survival, generation time, brood size, body length and body bend. At lower U-concentrations, the negative effects were reduced in the second or the third generation, indicating an improvement by acclimation. In contrast, at higher U-concentrations, the negative effects on brood size were amplified across generations. Consequently, under high U-concentrations acclimation may not be sufficient, and adaptation of individuals would be required, to permit the population to avoid extinction. The results highlight the need to consider changes across generations to enhance environmental risk assessment related to U pollution.

Consequences of a multi-generation exposure to uranium on Caenorhabditis elegans life parameters and sensitivity

The assessment of toxic effects at biologically and ecologically relevant scales is an important challenge in ecosystem protection. Indeed, stressors may impact populations at much longer term than the usual timescale of toxicity tests. It is therefore important to study the evolutionary response of a population under chronic stress. We performed a 16-generation study to assess the evolution of two populations of the ubiquitous nematode Caenorhabditis elegans in control conditions or exposed to 1.1 mM of uranium. Several generations were selected to assess growth, reproduction, survival, and dose-responses relationships, through exposure to a range of concentrations (from 0 to 1.2 mM U) with all endpoints measured daily. Our experiment showed an adaptation of individuals to experimental conditions (increase of maximal length and decrease of fecundity) for both populations. We also observed an increase of adverse effects (reduction of growth and fertility) as a function of uranium concentration. We pointed out the emergence of population differentiation for reproduction traits. In contrast, no differentiation was observed on growth traits. Our results confirm the importance of assessing environmental risk related to pollutant through multi-generational studies.

The use of traits-based approaches and eco(toxico)logical models to advance the ecological risk assessment framework for chemicals

This article presents a framework to diagnose and predict the effects of chemicals, integrating 2 promising tools to incorporate more ecology into ecological risk assessment, namely traits-based approaches and ecological modeling. Traits-based approaches are used increasingly to derive correlations between the occurrence of species traits and chemical exposure from biological and chemical monitoring data. This assessment can also be used in a diagnostic way, i.e., to identify the chemicals probably posing the highest risks to the aquatic ecosystems. The article also describes how ecological models can be used to explore how traits govern the species-substance interactions and to predict effects at the individual, population, and community and ecosystem level, i.e., from the receptor to the landscape level. This can be done by developing models describing the toxicokinetics and toxicodynamics of the chemical in the individual, the life-history of species and the connectivity of populations, determining their recovery, and the food web relations at the community and ecosystem level that determine the indirect effects. Special attention is given on how spatial aspects can be included in the ecological risk assessments using ecological models. The components of the framework are introduced and critically discussed. We describe how the different tools and data generated through experimentation (laboratory and semifield) and biomonitoring can be integrated. The article uses examples from the aquatic compartment, but the concepts that are used, and their integration within the framework, can be generalized to other environmental compartments.

Population-level modeling to account for multigenerational effects of uranium in Daphnia magna

As part of the ecological risk assessment associated with radionuclides in freshwater ecosystems, toxicity of waterborne uranium was recently investigated in the microcrustacean Daphnia magna over a three-generation exposure (F0, F1, and F2). Toxic effects on daphnid life history and physiology, increasing over generations, were demonstrated at the organism level under controlled laboratory conditions. These effects were modeled using an approach based on the dynamic energy budget (DEB). For each of the three successive generations, DEBtox (dynamic energy budget applied to toxicity data) models were fitted to experimental data. Lethal and sublethal DEBtox outcomes and their uncertainty were projected to the population level using population matrix techniques. To do so, we compared two modeling approaches in which experimental results from F0, F1, and F2 generations were either considered separately (F0-, F1-, and F2-based simulations) or together in the actual succession of F0, F1, and F2 generations (multi-F-based simulation). The first approach showed that considering results from F0 only (equivalent to a standard toxicity test) would lead to a severe underestimation of uranium toxicity at the population level. Results from the second approach showed that combining effects in successive generations cannot generally be simplified to the worst case among F0-, F1-, and F2-based population dynamics.

A biology-based dynamic approach for the reconciliation of acute and chronic toxicity tests: application to Daphnia magna

There is the need to integrate existing toxicity data in a coherent framework for extending their domain of applicability as well as their extrapolation potential. This integration would also reduce time and cost-consuming aspects of these tests and reduce animal usage. In this work, based on data extracted from literature, we have assessed the advantages that a dynamic biology-toxicant fate coupled model for Daphnia magna could provide when assessing toxicity data, in particular, the possibility to obtain from short-term (acute) toxicity test long-term (chronic) toxicity values taking into account the inherent variability of D. magna populations and the multiple sources of data. The results show that this approach overcomes some of the limitations of existing toxicity tests and that the prediction errors are considerably reduced when compared with the factor from 2 to 5 obtained using acute-to-chronic ratios.

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.

Potential application of population models in the European ecological risk assessment of chemicals. II. Review of models and their potential to address environmental protection aims

Whereas current chemical risk assessment (RA) schemes within the European Union (EU) focus mainly on toxicity and bioaccumulation of chemicals in individual organisms, most protection goals aim at preserving populations of nontarget organisms rather than individuals. Ecological models are tools rarely recommended in official technical documents on RA of chemicals, but are widely used by researchers to assess risks to populations, communities and ecosystems. Their great advantage is the relatively straightforward integration of the sensitivity of species to chemicals, the mode of action and fate in the environment of toxicants, life-history traits of the species of concern, and landscape features. To promote the usage of ecological models in regulatory risk assessment, this study tries to establish whether existing, published ecological modeling studies have addressed or have the potential to address the protection aims and requirements of the chemical directives of the EU. We reviewed 148 publications, and evaluated and analyzed them in a database according to defined criteria. Published models were also classified in terms of 5 areas where their application would be most useful for chemical RA. All potential application areas are well represented in the published literature. Most models were developed to estimate population-level responses on the basis of individual effects, followed by recovery process assessment, both in individuals and at the level of metapopulations. We provide case studies for each of the proposed areas of ecological model application. The lack of clarity about protection goals in legislative documents made it impossible to establish a direct link between modeling studies and protection goals. Because most of the models reviewed here were not developed for regulatory risk assessment, there is great potential and a variety of ecological models in the published literature.

The use of surrogate species in risk assessment: using life history data to safeguard against false negatives

The use of surrogate species is an important tool in predicting the effects of management decisions or the establishment of protective measures for endangered/threatened species. While relying on a handful of model species to predict the fate of scores of distantly related target species has been criticized, a quantitative measure linking life history traits and population predictions has been sorely missing. We derive here a closed-form expression aimed at determining conditions under which sublethal effects of a toxicant on surrogate species population outcomes will reliably predict outcomes of target (listed) species. We develop a critical threshold in fecundity reduction above which the surrogate species outcomes indicate positive population growth, while the listed species is driven to extinction. Thus we have established a means of determining conditions under which we are prone to making a "Type II" error in assessing ecological risk using surrogate species. Finally, we use the derived expression and life history data to compare outcomes from four different commonly used fish surrogate species (round goby, fathead minnow, smallmouth bass, cutthroat trout) and their target listed species (Chinook and Coho salmon). We illustrate that all four surrogate species fail to predict population outcomes for the listed species in cases of as little as 15% fecundity reduction due to toxicant exposure. Furthermore, surrogate species reliability is a function of toxicant level, so that some species are reliable at some levels but not at others. We discuss the implications of these findings, and outline further analyses that occur as a natural extension of the criteria developed here.

Sublethal toxicant effects with dynamic energy budget theory: application to mussel outplants

We investigate the effectiveness of a sublethal toxic effect model embedded in Dynamic Energy Budget (DEB) theory for the analysis of field data. We analyze the performance of two species of mussels, Mytilus galloprovincialis and M. californianus, near a diffuser discharging produced water in the Southern California Bight, California. Produced water is a byproduct of oil production consisting of fossil water together with compounds added during the extraction process, and generally contains highly elevated levels of pollutants relative to sea water. Produced water negatively affects the production of somatic and reproductive biomass in both mussel species; we show that these negative effects can be quantified with our DEB-based modeling framework through the estimation of toxic effect scaling parameters. Our analyses reveal that the toxic impact of produced water on growth and reproduction of M. californianus is substantially higher than for M. galloprovincialis. Projections of the expected lifetime production of gonad biomass indicate that the environmental impact of produced water can be as large as 100%, whereas short-term assessment without the use of DEB theory projects a maximum effect of only 30%.

Sublethal toxicant effects with dynamic energy budget theory: model formulation

We develop and test a general modeling framework to describe the sublethal effects of pollutants by adding toxicity modules to an established dynamic energy budget (DEB) model. The DEB model describes the rates of energy acquisition and expenditure by individual organisms; the toxicity modules describe how toxicants affect these rates by changing the value of one or more DEB parameters, notably the parameters quantifying the rates of feeding and maintenance. We investigate four toxicity modules that assume: (1) effects on feeding only; (2) effects on maintenance only; (3) effects on feeding and maintenance with similar values for the toxicity parameters; and (4) effects on feeding and maintenance with different values for the toxicity parameters. We test the toxicity modules by fitting each to published data on feeding, respiration, growth and reproduction. Among the pollutants tested are metals (mercury and copper) and various organic compounds (chlorophenols, toluene, polycyclic aromatic hydrocarbons, tetradifon and pyridine); organisms include mussels, oysters, earthworms, water fleas and zebrafish. In most cases, the data sets could be adequately described with any of the toxicity modules, and no single module gave superior fits to all data sets. We therefore propose that for many applications, it is reasonable to use the most general and parameter sparse module, i.e. module 3 that assumes similar effects on feeding and maintenance, as a default. For one example (water fleas), we use parameter estimates to calculate the impact of food availability and toxicant levels on the long term population growth rate.

Gaining insight in the interaction of zinc and population density with a combined dynamic energy budget and population model

Laboratory tests are typically conducted under optimal conditions testing the single effect of a toxicant In the field, due to suboptimal conditions, density dependence can both diminish and enhance effects of toxicants on populations. A review of the literature indicated that general insight on interaction of density and toxicants is lacking, and therefore no predictions on their combined action can be made. In this paper the influence of zinc was tested at different population densities on the demographic rates: growth, reproduction, and survival in the earthworm Lumbricus rubellus. Changes in these rates were extrapolated with a combined Dynamic energy budget (DEB) and a population model to assess consequences at the population level. Inference from the DEB model indicated that density decreased the assimilation of food whereas zinc increased the maintenance costs. The combined effects of density and zinc resulted in a decrease in the intrinsic rate of population increase which suddenly dropped to zero at combinations of zinc and density where development is so strongly retarded that individuals do not mature. This already happened at zinc levels where zinc induced mortality is low and therefore density enhances zinc effects and density dependent compensation is not expected.

A Bayesian approach to analyzing ecotoxicological data

Standardized chronic toxicity tests are usually analyzed using a NOEC (no observed effect concentration) or ECx (x% effect concentration) calculation. However,these methods provide very little information for the material cost they entail. It has been proposed that biology-based methods, such as the DEBtox approach, would make better use of the data available. DEBtox deals with the energy balance between physiological processes, and gives insight on how a compound disturbs it. We propose that data analysis can be further improved by estimating the DEBtox parameters using the considerable expertise available in laboratories and/or the literature. The Bayesian inference appears to be an appropriate estimation method for this purpose, as this technique takes expertise into account as prior probability distribution for each parameter, and provides the corresponding posterior distributions given the data. From these posterior distributions, point estimates can easily be deduced, but also credible intervals which are ideal for use in risk assessment. In this paper, we demonstrate this approach through the analysis of two 21-day Daphnia reproduction tests.

DEBtox theory and matrix population models as helpful tools in understanding the interaction between toxic cyanobacteria and zooplankton

Bioassays were performed to find out how field samples of the toxic cyanobacteria Microcystis aeruginosa affect Moina micrura, a cladoceran found in the tropical Jacarepagua Lagoon (Rio de Janeiro, Brazil). The DEBtox (Dynamic Energy Budget theory applied to toxicity data) approach has been proposed for use in analysing chronic toxicity tests as an alternative to calculating the usual safety parameters (NOEC, ECx). DEBtox theory deals with the energy balance between physiological processes (assimilation, maintenance, growth and reproduction), and it can be used to investigate and compare various hypotheses concerning the mechanism of action of a toxicant. Even though the DEBtox framework was designed for standard toxicity bioassays carried out with standard species (fish, daphnids), we applied the growth and reproduction models to M. micrura, by adapting the data available using a weight-length allometric relationship. Our modelling approach appeared to be very relevant at the individual level, and confirmed previous conclusions about the toxic mechanism. In our study we also wanted to assess the toxic effects at the population level, which is a more relevant endpoint in risk assessment. We therefore incorporated both lethal and sublethal toxic effects in a matrix population model used to calculate the finite rate of population change as a continuous function of the exposure concentration. Alongside this calculation, we constructed a confidence band to predict the critical exposure concentration for population health. Finally, we discuss our findings with regard to the prospects for further refining the analysis of ecotoxicological data.