Death Dilemma and Organism Recovery in 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.

Mortality Pattern of Poecilus cupreus Beetles after Repeated Topical Exposure to Insecticide─Stochastic Death or Individual Tolerance?

The mortality of organisms exposed to toxicants has been attributed to either stochastic processes or individual tolerance (IT), leading to the stochastic death (SD) and IT models. While the IT model follows the principles of natural selection, the relevance of the SD model has been debated. To clarify why the idea of stochastic mortality has found its way into ecotoxicology, we investigated the mortality of Poecilus cupreus (Linnaeus, 1758) beetles from pesticide-treated oilseed rape (OSR) fields and unsprayed meadows, subjected to repeated insecticide treatments. We analyzed the mortality with the Kaplan-Meier estimator and general unified threshold model for survival (GUTS), which integrates SD and IT assumptions. The beetles were exposed three times, ca. monthly, to the same dose of Proteus 110 OD insecticide containing thiacloprid and deltamethrin, commonly used in the OSR fields. Kaplan-Meier analysis showed that the mortality of beetles from meadows was much higher after the first treatment than after the next two, indicating the IT model. Beetles from the OSR displayed approximately constant mortality after the first and second treatments, consistent with the SD model. GUTS analysis did not conclusively identify the better model, with the IT being marginally better for beetles from meadows and the SD better for beetles from OSR fields.

Behavioral toxicity, histopathological alterations and oxidative stress in Tubifex tubifex exposed to aromatic carboxylic acids- acetic acid and benzoic acid: A comparative time-dependent toxicity assessment

This study evaluated Acetic acid (AA) and Benzoic acid's (BA) acute and sublethal toxicity by observing mortality, behavioral responses, and changes in the levels of oxidative stress enzymes in Tubifex tubifex. Exposure-induced changes in antioxidant activity (Catalase, Superoxide dismutase), oxidative stress (Malondialdehyde concentrations), and histopathological alterations in the tubificid worms were also noted across exposure intervals. The 96 h LC₅₀ values of AA and BA to T. tubifex were 74.99 and 37.15 mg/l, respectively. Severity in behavioral alterations (including increased mucus production, wrinkling, and reduction in clumping) and autotomy showed concentration-dependent trends for both toxicants. Although histopathological effects also showed marked degeneration in the alimentary and integumentary systems in highest exposure groups (worms exposed to 14.99 mg/l for AA and 7.42 mg/l for BA) for both toxicants. Antioxidant enzymes (catalase and superoxide dismutase) also showed a marked increase of up to 8-fold and 10-fold for the highest exposure group of AA and BA respectively. While species sensitivity distribution analysis revealed T. tubifex as most sensitive to AA and BA compared to other freshwater vertebrates and invertebrates, General Unified Threshold model of Survival (GUTS) predicted individual tolerance effects (GUTS-IT), with slower potential for toxicodynamic recovery, as a more likely pathway for population mortality. Study findings demonstrate BA with greater potential for ecological effects compared to AA within 24 h of exposure. Furthermore, ecological risks to critical detritus feeders like T. tubifex may have severe implications for ecosystem services and nutrient availability within freshwater habitats.

Recovery of Ceratophrys ornata tadpoles exposed to environmental concentrations of chlorpyrifos: evaluation of biomarkers of exposure

Chlorpyrifos (CPF) is one of the most widely used insecticides worldwide despite the fact that many authors have warned about its effects in non-target biota. The effects of CPF on anurans are well known, but the process of recovery from these effects after exposure is less explored. The aim of this study was to evaluate the duration of sublethal effects induced by environmental concentrations of CPF on Ceratophrys ornata tadpoles after exposure. The experimental design consisted of an exposure phase (96 h) in which tadpoles were individually exposed to three concentrations of CPF (0, 0.01 and 0.02 mg CPF/L) and a post-exposure phase (72 h) in which exposed tadpoles were transferred to CPF-free media. Individuals that survived the exposure phase to CPF showed neither long-term lethal effects nor long-term swimming alterations and altered prey consumption after being transferred to CPF-free media. No morphological abnormalities were observed either. However, at the end of both phases, tadpoles emitted shorter sounds with a higher dominant frequency than the tadpoles in the control group, i.e., the tadpoles did not recover their normal sounds. Thus, for the first time in this species, we have shown that effects on sounds should be prioritized as biomarkers of exposure, as they not only provide longer detection times after cessation of exposure, but also involve non-destructive methods. The following order of priority could be established for the selection of biomarkers that diagnose the health status of individuals and precede irreversible responses such as mortality: alterations in sounds > swimming alterations > prey consumption.

A review of hybrid enzymatic-chemical treatment for wastewater containing antiepileptic drugs

Epilepsy is one of the most common neurological diseases worldwide and requires treatment with antiepileptic drugs for many years or for life. This fact leads to the need for constant production and use of these compounds, placing them among the four pharmaceutical classes most found in wastewater. Even at low concentrations, antiepileptics pose risks to human and environmental health and are considered organic contaminants of emerging concern. Conventional treatments have shown low removal of these drugs, requiring advanced and innovative approaches. In this context, this review covers the results and perspectives on (1) consumption and occurrence of antiepileptics in water, (2) toxicological effects in aquatic ecosystems, (3) enzymatic and advanced oxidation processes for degrading antiepileptics drugs from a molecular point of view (biochemical and chemical phenomena), (4) improvements in treatment efficiency by hybridization, and (5) technical aspects of the enzymatic-AOP reactors.

Joint survival modelling for multiple species exposed to toxicants

In environmental risk assessment (ERA), the multitude of compounds and taxa demands cross-species extrapolation to cover the variability in sensitivity to toxicants. However, only the impact of a single compound to a single species is addressed by the general unified threshold model of survival (GUTS). The reduced GUTS is the recommended model to analyse lethal toxic effects in regulatory aquatic ERA. GUTS considers toxicokinetics and toxicodynamics. Two toxicodynamic approaches are considered: Stochastic death (SD) assumes that survival decreases with an increasing internalized amount of the toxicant. Individual tolerance (IT) assumes that individuals vary in their tolerance to toxic exposure. Existing theory suggests that the product of the threshold z_w and killing rate b_w (both SD toxicodynamic parameters) are constant across species or compounds if receptors and target sites are shared. We extend that theory and show that the shape parameter β of the loglogistic threshold distribution in IT is also constant. To verify the predicted relationships, we conducted three tests using toxicity studies for eight arthropods exposed to the insecticide flupyradifurone. We confirmed previous verifications of the relation- between SD parameters, and the newly established relation for the IT parameter β. We enhanced GUTS to jointly model survival for multiple species with shared receptors and pathways by incorporating the relations among toxicodynamic parameters described above. The joint GUTS exploits the shared parameter relations and therefore constrains parameter uncertainty for each of the separate species. Particularly for IT, the joint GUTS more precisely predicted risk to the separate species than the standard single species GUTS under environmentally realistic exposure. We suggest that joint GUTS modelling can improve cross-species extrapolation in regulatory ERA by increasing the reliability of risk estimates and reducing animal testing. Furthermore, the shared toxicodynamic response provides potential to reduce complexity of ecosystem models.

Three perspectives on the prediction of chemical effects in ecosystems

The increasing production, use and emission of synthetic chemicals into the environment represents a major driver of global change. The large number of synthetic chemicals, limited knowledge on exposure patterns and effects in organisms and their interaction with other global change drivers hamper the prediction of effects in ecosystems. However, recent advances in biomolecular and computational methods are promising to improve our capacity for prediction. We delineate three idealised perspectives for the prediction of chemical effects: the suborganismal, organismal and ecological perspective, which are currently largely separated. Each of the outlined perspectives includes essential and complementary theories and tools for prediction but captures only part of the phenomenon of chemical effects. Links between the perspectives may foster predictive modelling of chemical effects in ecosystems and extrapolation between species. A major challenge for the linkage is the lack of data sets simultaneously covering different levels of biological organisation (here referred to as biological levels) as well as varying temporal and spatial scales. Synthesising the three perspectives, some central aspects and associated types of data seem particularly necessary to improve prediction. First, suborganism- and organism-level responses to chemicals need to be recorded and tested for relationships with chemical groups and organism traits. Second, metrics that are measurable at many biological levels, such as energy, need to be scrutinised for their potential to integrate across levels. Third, experimental data on the simultaneous response over multiple biological levels and spatiotemporal scales are required. These could be collected in nested and interconnected micro- and mesocosm experiments. Lastly, prioritisation of processes involved in the prediction framework needs to find a balance between simplification and capturing the essential complexity of a system. For example, in some cases, eco-evolutionary dynamics and interactions may need stronger consideration. Prediction needs to move from a static to a real-world eco-evolutionary view.

Modeling Time-Dependent Aquatic Toxicity of Hydrocarbons: Role of Organism Weight, Temperature, and Substance Hydrophobicity

Oil spill exposures are highly dynamic and are not comparable to laboratory exposures used in standard toxicity tests. Toxicokinetic-toxicodynamic (TKTD) models allow translation of effects observed in the laboratory to the field. To improve TKTD model calibration, new and previously published data from 148 tests were analyzed to estimate rates characterizing the time course of toxicity for 10 fish and 42 invertebrate species across 37 hydrocarbons. A key parameter in the TKTD model is the first-order rate that incorporates passive elimination, biotransformation, and damage repair processes. The results indicated that temperature (4-26 °C), organism size (0.0001-10 g), and substance log octanol-water partition coefficient (2-6) had limited influence on this parameter, which exhibited a 5th to 95th percentile range of 0.2-2.5 day-1 (median 0.7 day-1 ). A species sensitivity distribution approach is proposed to quantify the variability of this parameter across taxa, with further studies needed for aliphatic hydrocarbons and plant species. Study findings allow existing oil spill models to be refined to improve effect predictions. Environ Toxicol Chem 2022;41:3070-3083. © 2022 ExxonMobil Biomedical Science Inc. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

The Capacity of Freshwater Ecosystems to Recover from Exceedences of Aquatic Life Criteria

In the United States, national chemical water quality criteria for the protection of aquatic life assume that aquatic ecosystems have sufficient resiliency to recover from criteria exceedences occurring up to once every 3 years. This resiliency assumption was critically reviewed through two approaches: (1) synthesis of case studies, and (2) population modeling. The population modeling examined differences in recovery of species with widely different life histories. One invertebrate (Hyalella azteca) and four fish species were modeled (fathead minnow, brook trout, lake trout, and shortnose sturgeon) with various disturbance magnitudes and intervals. The synthesis of ecosystem case studies showed generally faster recoveries for insect communities rather than fish, and recoveries from pulse (acute) disturbances were often faster than recoveries from press (chronic) disturbances. When the recovery dataset excluded severe disturbances that seemed unrepresentative of common facility discharge upsets that might cause criteria exceedences, the median recovery time was 1 year, 81% of the cases were considered recovered within 3 years, and 95% were considered recovered within 10 years. The modeling projected that short-lived fish species with high recovery times could thrive despite enduring 50% mortality disturbances every other year. However, long-lived fish species had longer recovery times and declined under the one disturbance every 3 years scenario. Overall, the analyses did not refute the long-standing judgements that 3 years is generally sufficient for recovery from nonrepetitive, moderate intensity disturbances of a magnitude up to 2× the chronic criteria in waters without other pollution sources or stresses. However, these constraints may not always be met and if long-lived fish species are a concern, longer return intervals such as 5-10 years could be indicated. Environ Toxicol Chem 2022;41:2887-2910. Published 2022. This article is a U.S. Government work and is in the public domain in the USA.

Deltamethrin-Induced Respiratory and Behavioral Effects and Adverse Outcome Pathways (AOP) in Short-Term Exposed Mozambique Tilapia, Oreochromis mossambicus

Disrupted behavior and respiratory distress effects of 96-h acute deltamethrin exposures in adult Mozambique tilapia, Oreochromis mossambicus, were investigated using behavioral indices and opercular movement, respectively. Deltamethrin concentrations were found to be associated with toxicological (lethal and sublethal) responses. At 24, 48, 72, and 96 h, the LC50 values and 95% confidence limits were 12.290 (11.174-14.411 µg/L), 12.671 (11.334-15.649 µg/L), 10.172 (9.310-11.193 µg/L), and 8.639 (7.860-9.417 µg/L), respectively. The GUTS-model analysis showed that GUTS-SD (stochastic death) with a narrow tolerance distribution in deltamethrin exposed O. mossambicus populations was more sensitive than the GUTS-IT (individual tolerance) model. Prior to death, exposed fish demonstrated concentration-dependent mortality and disturbed behavioral responses, including uncoordinated swim motions, increased mucus secretion, unbalanced and unpredictable swimming patterns, and inactivity. The altered behavioral patterns and increased opercular movement with increased deltamethrin levels and exposure time are strongly suggestive of neurotoxicity and respiratory distress, respectively. Adverse Outcome Pathways (AOPs), describing biological mechanisms and plausible pathways, highlighted oxidative stress and cholinergic effects as intermediate steps linked to respiratory distress and behavioral toxicity.

Comparative toxicity of hydrocarbons for evaluation of Lysmata boggessi as an experimental proxy for deep-water column micronekton

The potential impacts of sub-surface hydrocarbon plumes to deep-water column micronekton are an important consideration in a more complete understanding of ecosystem effects resulting from deep-sea oil spills. However, evaluating toxicity in these organisms presents multiple challenges, and the use of a shallow-water proxy species allows comparison and validation of experimental results. This study thus examined the suitability of the peppermint shrimp, Lysmata boggessi, as an experimental proxy for ecologically important deep-sea zooplankton/micronekton in hydrocarbon toxicity assays. This crustacean species occurs in shallow coastal marine environments throughout the western Atlantic, Caribbean and Gulf of Mexico, is similar in size to the mesopelagic organisms previously tested and is readily available via commercial aquaculture. The effects of 1-methylnaphthalene and fresh Macondo oil (MC252) on L. boggessi were assessed in 48-h constant-exposure toxicity tests, and acute thresholds were compared to previously determined LC50s for oceanic mid water Euphausiidae, Janicella spinacauda, Systellaspis debilis, Sergestes sp., Sergia sp. and the mysid shrimp Americamysis bahia. Acute thresholds and the calculated critical target lipid body burden (CTLBB) for the shallow-water L. boggessi were comparable to the deep-water species tested, suggesting that L. boggessi may be a suitable proxy for some mesopelagic micronekton species in acute hydrocarbon exposures.

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Acute endpoints for L. boggessi were comparable to mesopelagic crustaceans.

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CTLBBs for L. boggessi were similar to those determined for mesopelagic crustaceans.

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L. boggessi may be a suitable proxy for some micronekton in hydrocarbon exposures.

Chemical Pollution Levels in a River Explain Site-Specific Sensitivities to Micropollutants within a Genetically Homogeneous Population of Freshwater Amphipods

Anthropogenic micropollutants alter chemical and ecological conditions of freshwater ecosystems and impact aquatic species that live along the pollution gradient of a river. Species sensitivity to micropollutants depends on the site-specific exposure; however, it remains unclear to what degree this sensitivity relates to the species' genetic structure. Here, we explored the relationship between the toxic sensitivity and genetic structure of the amphipod species Gammarus pulex (Linnaeus, 1758) along an organic micropollutant gradient in the Holtemme River in central Germany. We determined the river's site-specific micropollutant patterns and analyzed the genetic structure of G. pulex using nuclear and mitochondrial genetic markers. Furthermore, we examined the exposure sensitivities and bioaccumulation of the commonly detected insecticide imidacloprid in G. pulex from different sites. Our results show that throughout the Holtemme River, G. pulex forms a well-connected and homogeneous population with no observable pollution-related differences in the genetic structure. However, G. pulex from polluted sites responded more sensitively to imidacloprid; survival times for half of the amphipods were up to 54% shorter, the percentage of immobile individuals increased up to 65%, and the modeled imidacloprid depuration rate was lower in comparison to amphipods from non-polluted sites. Altogether, these results suggest that the level of sensitivity of G. pulex amphipods to micropollutants in the river depends on the degree of pollution: amphipods may thrive in food-rich but polluted habitats; yet, their sensitivity is increased when chronically exposed to organic micropollutants.

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.

Predicting copper toxicity in zebrafish larvae under complex water chemistry conditions by using a toxicokinetic-toxicodynamic model

Multiple water chemistry parameters influence metal toxicity in natural waters and accurate quantification of those influences may accelerate the development of site-specific water quality criteria (WQC) and further execute metal risk assessment for better protection of aquatic biota. Here, we investigated the effects of water chemistry parameters on copper (Cu) toxicity of larval zebrafish (Danio rerio) and then incorporated the effects of key parameters in a Toxicokinetic and Toxicodynamic (TK-TD) model. Further, the proposed TK-TD model was used to predict Cu toxicity in laboratory artificial waters as well as natural water samples. The predictive performance of the TK-TD model was evaluated in comparison to the biotic ligand model (BLM). The results showed that increasing Ca, Mg, pH, and fulvic acid (FA) levels significantly mitigated Cu toxicity in larvae, while K and Na levels had no significant effect on Cu toxicity. A predictive TK-TD model based on these data described 91 % of Cu accumulation and 87 % of survival of larvae exposed to Cu under 0, 2.5, 5, 10 mg/L FA. Compared with BLM, TK-TD model predicted better Cu accumulation and toxicity for an independent dataset in low DOC concentration (<10.95 mg L^-1) of 9 sites in Haihe river (Tianjin, China) media during 96 h exposure. The BLM under-predicted the acute Cu toxicity to larvae when compared with observed values. In high DOC concentration (13.12-17.78 mg L^-1) among three field sites, BLM and TK-TD model both under-predicted the acute Cu toxicity to larvae when compared with observed values. Our research provides a TK-TD approach for predicting Cu toxicity under complex water chemistry conditions and deriving Cu-WQC in different scenarios where there exist limits for using the BLM.

Effect Modeling Quantifies the Difference Between the Toxicity of Average Pesticide Concentrations and Time-Variable Exposures from Water Quality Monitoring

Synthetic chemicals are frequently detected in water bodies, and their concentrations vary over time. Water monitoring programs typically employ either a sequence of grab samples or continuous sampling, followed by chemical analysis. Continuous time-proportional sampling yields the time-weighted average concentration, which is taken as proxy for the real, time-variable exposure. However, we do not know how much the toxicity of the average concentration differs from the toxicity of the corresponding fluctuating exposure profile. We used toxicokinetic-toxicodynamic models (invertebrates, fish) and population growth models (algae, duckweed) to calculate the margin of safety in moving time windows across measured aquatic concentration time series (7 pesticides) in 5 streams. A longer sampling period (14 d) for time-proportional sampling leads to more deviations from the real chemical stress than shorter sampling durations (3 d). The associated error is a factor of 4 or less in the margin of safety value toward underestimating and an error of factor 9 toward overestimating chemical stress in the most toxic time windows. Under- and overestimations occur with approximate equal frequency and are very small compared with the overall variation, which ranged from 0.027 to 2.4 × 10¹⁰ (margin of safety values). We conclude that continuous, time-proportional sampling for a period of 3 and 14 d for acute and chronic assessment, respectively, yields sufficiently accurate average concentrations to assess ecotoxicological effects. Environ Toxicol Chem 2020;39:2158-2168. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Improving Risk Assessment by Predicting the Survival of Field Gammarids Exposed to Dynamic Pesticide Mixtures

Exposure assessment of pesticides has substantially improved over time, with methods that now include a combination of advanced analytical techniques and fate/transport models to evaluate their spatiotemporal distribution. However, the current regulatory environmental risk assessment considers thresholds from laboratory studies completed under standardized conditions that do not reflect environmental dynamics. Using the General Unified Threshold model for Survival (GUTS) model framework, we predicted the impact of time-varying pesticide exposures on the survival of gammarids in a small agricultural stream. The LP₅₀ values were used as an additional metric for assessing risks (defined in GUTS as a multiplication factor applied to the concentration time series to induce 50% mortality by the end of exposure). Although real-case exposures to individual pesticides were predicted to produce little to no impact on survival, the LP₅₀ values indicate acute (LP₅₀ ≤ 100) and/or chronic (LP₅₀ ≤ 10) toxicities for azoxystrobin, chlorpyrifos, diazinon, and imidacloprid, while risk to propiconazole exposure was considered very low (LP₅₀ ≫ 100). Finally, the model was extended to reflect mixture toxicity via concentration addition. It predicted risks under acute and chronic exposures to organophosphates and neonicotinoids. Given that gammarids are simultaneously exposed to multiple chemicals and other stressors throughout their lifetime, a decline in survival probabilities due to chemical stress can likely influence their overall fitness. We recognize that some assumptions require validation, but our work included a level of realism that can assist risk managers when evaluating the cumulative consequences of chemical exposure.

Linking Morphology, Toxicokinetic, and Toxicodynamic Traits of Aquatic Invertebrates to Pyrethroid Sensitivity

Pyrethroid insecticides are known to be highly toxic to most aquatic nontarget organisms, but little is known about the mechanisms causing some species to be highly sensitive while others are hardly affected by the pyrethroids. The aim of the present study was to measure the sensitivity (EC₅₀-values) of 10 aquatic invertebrates toward a 24 h pulse of the pyrethroid cypermethrin and subsequently test if the difference in sensitivity could be explained by measured morphological and physiological traits and modeled toxicokinetic (TK) and toxicodynamic (TD) parameters. Large differences were observed for the measured uptake and elimination kinetics, with bioconcentration factors (BCFs) ranging from 53 to 2337 at the end of the exposure. Similarly, large differences were observed for the TDs, and EC₅₀-values after 168 h varied 120-fold. Modeling the whole organism cypermethrin concentrations indicated compartmentation into a sorbed fraction and two internal fractions: a bioavailable and non-bioavailable internal fraction. Strong correlations between surface/volume area and the TK parameters (sorption and uptake rate constants and the resulting BCF) were found, but none of the TK parameters correlated with sensitivity. The only parameter consistently correlating with sensitivity across all species was the killing rate constant of the GUTS-RED-SD model (the reduced general unified threshold models of survival assuming stochastic death), indicating that sensitivity toward cypermethrin is more related to the TD parameters than to TK parameters.

Different decreasing rates of chemical threshold concentrations can be explained by their toxicokinetic and toxicodynamic characteristics

To protect ecosystems, threshold concentrations (e.g., HC₅) for chemicals are often derived using the toxicity data obtained at fixed times. Since the toxicity (e.g., LC₅₀) usually decreases with exposure time, the threshold concentrations are expected to be time-dependent, giving rise to the uncertainty in the chemical environmental criteria. Here, using the LC₅₀ data with at least 3 different exposure durations (24, 48 and 96 h) for compounds, we explored the time evolutions of HC₅ across 20 chemicals. Results showed that all chemical's HC₅ decreased with time, but their decreasing rates of HC₅ (k) are significantly different: for some chemicals the k are lower than 0.001 (e.g., methoxychlor and dieldrin), while for some chemicals the k are higher than 0.05 (e.g., PCP and aldicarb). Furthermore, we found that k is negatively related to the bioconcentration factors (BCF), and positively related to the damage recovery rates (k_R). Our work demonstrated that time is an important source of the ecological threshold uncertainty, and this uncertainty is associated with chemical-specific toxicokinetic and toxicodynamic characteristics. We recommend that to effectively protect the ecological communities, higher assessment factor should be adopted in deriving the acute environmental criteria for these chemicals with high BCF and low k_R, fluoranthene and diazinon.

Comparison of the General Threshold Model of Survival and Dose-Response Models in Simulating the Acute Toxicity of Metals to Danio rerio

We exposed zebrafish (Danio rerio) to different concentrations of lead and cadmium, and monitored them for survival at 24, 48, 72, and 96 h. Metal toxicity was predicted and compared using the dose-response and general threshold survival models in terms of required data sets, fit performance, and applicability. Environ Toxicol Chem 2019;38:2169-2177. © 2019 SETAC.

Predicting the survival of zebrafish larvae exposed to fluctuating pulses of lead and cadmium

Aquatic organisms are often exposed to time-varied concentrations of contaminants due to pulsed inputs in natural water. Traditional toxicology experiments are usually carried out in a constant exposure pattern, which is inconsistent with the actual environment. In this study, a refined toxicokinetic-toxicodynamic (TK-TD) model was used to study the toxic effects of Pb and Cd on zebrafish larvae under three pulse exposures with 2, 4, and 6 h, respectively. The parameter sensitivity analysis showed that J_{M, max} had the greatest impact on the output of the model. Cd or Pb pulse exposure resulted in less death than constant exposure at the same time-weighted average (TWA) concentrations. Survival fraction in larvae under 6 h interval between two pulses of Pb or Cd was larger than that under 2 h and 4 h interval. Toxicity under constant exposure of Cd or Pb was greater than that under 2, 4, and 6 h interval pulse exposure because the cumulative Cd or Pb concentration in the body under constant exposure was greater than that under pulse exposure. The results also showed that the stochastic death (SD) model was more suitable than the individual tolerance (IT) model for predicting the survival fraction of larvae under pulse exposure to Pb and Cd, which was indicated by higher R² (0.670-0.940) in SD model than that (0.588-0.861) in IT model. Our model provides approaches for laboratory toxicity testing and modeling approaches for addressing the toxicity of heavy metal pulsed exposure.

Exploring inter-species sensitivity to a model hydrocarbon, 2-Methylnaphtalene, using a process-based model

We compared inter-species sensitivity to a model narcotic compound, 2-Methylnaphthalene, to test if taxonomical relatedness, feeding guilds, and trophic level govern species sensitivities on species distributed in different regions. We fitted a toxicokinetic-toxicodynamic model to survival patterns over time for 26 species using new and raw data from the literature. Species sensitivity distributions provided little insight into understanding patterns in inter-species sensitivity. The range of no-effect concentrations (NEC) obtained for 26 species showed little variation (mean 0.0081 mM; SD 0.009). Results suggest that the NEC alone does not explain the complexity of the species tolerances. The dominant rate constant and the derived time to observe an effect (t₀), a function of concentration, might provide the means for depicting patterns in sensitivity and better ecotoxicological testing. When comparing the t₀ functions, we observed that Arctic species have shorter time frames to start showing effects. Mollusks and second trophic level species took longer to build up a lethal body burden than the rest. Coupling our results with fate and transport models would allow forecasting narcotic compounds toxicity in time and thus improve risk assessment.

Memory effect of arsenic-induced cellular response and its influences on toxicity of titanium dioxide nanoparticle

Toxicity of arsenic (As) has been widely characterized. However, few studies focus on whether cell responses induced by As at nontoxic concentration could be inherited and further change cell tolerance to another pollutant. In this study, human A549 and HeLa cells were exposed to As at nontoxic concentrations for 10 or 15 passages, then the cells were recovered in the cell medium without As. At 25th passage, residual As in both type of cells was completely removed through the recovery process. And no abnormity in cell viability was identified in both type of cells between control and As-treated groups. Above results indicated that As exposure-recovery treatment had limited influence on phenotype of the cells. However, gene expression profiles determined by high-throughput sequencing showed that As exposure-recovery treatment induced similar expression modification of genes related to inflammation, oxidative stress and epigenetic modulation in the A549 and HeLa cells after recovery of 10 or 15 passages, indicating that As-induced cellular responses have been partially memorized at transcriptional level. The memory effect might play key roles in increased tolerance of the A549 and HeLa cells to adverse effects (cell viability, intracellular reactive oxygen species (ROS) generation and plasma membrane damage) induced by titanium dioxide nanoparticles (as representative pollutant). This study shed new lights on toxic effects induced by As at nontoxic concentration, which is useful for risk assessment of combined effects of As and other pollutants.

Short-term to long-term extrapolation of lethal effects of an herbicide on the marine mysid shrimp Americamysis Bahia by use of the General Unified Threshold Model of Survival (GUTS)

Risk assessments for plant protection products and their active ingredients that are based on standard laboratory tests performed under constant exposure conditions may result in an overestimation of risks because exposure in the environment is often characterized by a few short peaks. Here, the General Unified Threshold Model of Survival (GUTS) was used to conduct a refined risk assessment for the herbicide tembotrione and its effects on the marine invertebrate Americamysis bahia, for which the standard chronic effect assessment failed. The GUTS model was first calibrated with time-to-effect and concentration-response data from 2 independent acute experiments with A. bahia. Model parameters for both toxicodynamic assumptions of stochastic death (SD) and individual tolerance (IT) were estimated with the reduced GUTS model (GUTS-RED) using the scaled internal concentration as a dose metric. Both the calibrated GUTS-RED-SD and GUTS-RED-IT models described survival dynamics well. Model validation using datasets of 2 independent chronic tests yielded robust predictions of long-term toxicity of tembotrione on A. bahia, with GUTS-RED-IT being more reliable than GUTS-RED-SD. The validated model was subsequently used to predict survival from time-variable exposure profiles, as derived from the FOrum for Co-ordination of pesticide fate models and their USe (FOCUS). Because ecotoxicological independence of peaks had not been empirically verified, the link between exposure and effects was assessed with complete exposure profiles. Effect thresholds resulting from different peak exposure concentrations and durations were determined with GUTS and directly compared with the exposure concentrations from the FOCUS surface water scenarios. The derived values were higher than the predicted FOCUS critical concentrations. Additionally, comparing the areas under the curve (AUCs) derived with GUTS for multiple peak exposure profiles to those from FOCUS revealed significant additional safety margins, demonstrating that only unrealistically high exposure concentrations would produce significant effects. In conclusion, no unacceptable effects of tembotrione on aquatic invertebrates under realistic environmental exposure conditions are expected. Integr Environ Assess Manag 2019;15:29-39. © 2018 SETAC.

Calibration and validation of toxicokinetic-toxicodynamic models for three neonicotinoids and some aquatic macroinvertebrates

Exposure patterns in ecotoxicological experiments often do not match the exposure profiles for which a risk assessment needs to be performed. This limitation can be overcome by using toxicokinetic-toxicodynamic (TKTD) models for the prediction of effects under time-variable exposure. For the use of TKTD models in the environmental risk assessment of chemicals, it is required to calibrate and validate the model for specific compound-species combinations. In this study, the survival of macroinvertebrates after exposure to the neonicotinoid insecticide was modelled using TKTD models from the General Unified Threshold models of Survival (GUTS) framework. The models were calibrated on existing survival data from acute or chronic tests under static exposure regime. Validation experiments were performed for two sets of species-compound combinations: one set focussed on multiple species sensitivity to a single compound: imidacloprid, and the other set on the effects of multiple compounds for a single species, i.e., the three neonicotinoid compounds imidacloprid, thiacloprid and thiamethoxam, on the survival of the mayfly Cloeon dipterum. The calibrated models were used to predict survival over time, including uncertainty ranges, for the different time-variable exposure profiles used in the validation experiments. From the comparison between observed and predicted survival, it appeared that the accuracy of the model predictions was acceptable for four of five tested species in the multiple species data set. For compounds such as neonicotinoids, which are known to have the potential to show increased toxicity under prolonged exposure, the calibration and validation of TKTD models for survival needs to be performed ideally by considering calibration data from both acute and chronic tests.

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.

Scientific Opinion on the state of the science on pesticide risk assessment for amphibians and reptiles

Following a request from EFSA, the Panel on Plant Protection Products and their Residues developed an opinion on the science to support the potential development of a risk assessment scheme of plant protection products for amphibians and reptiles. The coverage of the risk to amphibians and reptiles by current risk assessments for other vertebrate groups was investigated. Available test methods and exposure models were reviewed with regard to their applicability to amphibians and reptiles. Proposals were made for specific protection goals aiming to protect important ecosystem services and taking into consideration the regulatory framework and existing protection goals for other vertebrates. Uncertainties, knowledge gaps and research needs were highlighted.

Scientific Opinion on the state of the science on pesticide risk assessment for amphibians and reptiles

Following a request from EFSA, the Panel on Plant Protection Products and their Residues developed an opinion on the science to support the potential development of a risk assessment scheme of plant protection products for amphibians and reptiles. The coverage of the risk to amphibians and reptiles by current risk assessments for other vertebrate groups was investigated. Available test methods and exposure models were reviewed with regard to their applicability to amphibians and reptiles. Proposals were made for specific protection goals aiming to protect important ecosystem services and taking into consideration the regulatory framework and existing protection goals for other vertebrates. Uncertainties, knowledge gaps and research needs were highlighted.

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.

Sequential exposure to low levels of pesticides and temperature stress increase toxicological sensitivity of crustaceans

Frequent pesticide-related impacts on ecosystems at concentrations considered environmentally safe indicate that the current risk assessment framework for registration of pesticides is not protective enough. Causes may include difficulties in assessing the effects of sequential pesticide pulses and their interaction with environmental stressors. By contrast to such realistic scenarios, risk assessment for registration of pesticides is typically based on tests of a single exposure period under benign laboratory conditions. Here, we investigated the toxicological sensitivity of Gammarus pulex, an ecologically relevant crustacean, from uncontaminated control streams and pesticide-contaminated agricultural streams by exposing them to pesticide contamination in the laboratory. Individuals from contaminated streams were 2.7-fold more sensitive to pesticide exposure than individuals from the reference streams. We revealed that this increase in sensitivity was the result of a synergistic interaction of sequential pesticide exposure and temperature stress. Such multiple stressor scenarios are typical for agricultural streams. We conclude that the interactive effects of sequential toxicant exposure and additional environmental stressors need to be considered in a realistic risk assessment framework.

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

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

Simulation to aid in interpreting biological relevance and setting of population-level protection goals for risk assessment of pesticides

Specific protection goals (SPGs) comprise an explicit expression of the environmental components that need protection and the maximum impacts that can be tolerated. SPGs are set by risk managers and are typically based on protecting populations or functions. However, the measurable endpoints available to risk managers, at least for vertebrates, are typically laboratory tests. We demonstrate, using the example of eggshell thinning in skylarks, how simulation can be used to place laboratory endpoints in context of population-level effects as an aid to setting the SPGs. We develop explanatory scenarios investigating the impact of different assumptions of eggshell thinning on skylark population size, density and distribution in 10 Danish landscapes, chosen to represent the range of typical Danish agricultural conditions. Landscape and timing of application of the pesticide were found to be the most critical factors to consider in the impact assessment. Consequently, a regulatory scenario of monoculture spring barley with an early spray treatment eliciting the eggshell thinning effect was applied using concentrations eliciting effects of zero to 100% in steps of 5%. Setting the SPGs requires balancing scientific, social and political realities. However, the provision of clear and detailed options such as those from comprehensive simulation results can inform the decision process by improving transparency and by putting the more abstract testing data into the context of real-world impacts.

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.

Robust Fit of Toxicokinetic-Toxicodynamic Models Using Prior Knowledge Contained in the Design of Survival Toxicity Tests

Toxicokinetics-toxicodynamic (TKTD) models have emerged as a powerful means to describe survival as a function of time and concentration in ecotoxicology. They are especially powerful to extrapolate survival observed under constant exposure conditions to survival predicted under realistic fluctuating exposure conditions. But despite their obvious benefits, these models have not yet been adopted as a standard to analyze data of survival toxicity tests. Instead simple dose-response models are still often used although they only exploit data observed at the end of the experiment. We believe a reason precluding a wider adoption of TKTD models is that available software still requires strong expertise in model fitting. In this work, we propose a fully automated fitting procedure that extracts prior knowledge on parameters of the model from the design of the toxicity test (tested concentrations and observation times). We evaluated our procedure on three experimental and 300 simulated data sets and showed that it provides robust fits of the model, both in the frequentist and the Bayesian framework, with a better robustness of the Bayesian approach for the sparsest data sets.

Toxic Mixtures in Time-The Sequence Makes the Poison

"The dose makes the poison". This principle assumes that once a chemical is cleared out of the organism (toxicokinetic recovery), it no longer has any effect. However, it overlooks the other process of re-establishing homeostasis, toxicodynamic recovery, which can be fast or slow depending on the chemical. Therefore, when organisms are exposed to two toxicants in sequence, the toxicity can differ if their order is reversed. We test this hypothesis with the freshwater crustacean Gammarus pulex and four toxicants that act on different targets (diazinon, propiconazole, 4,6-dinitro-o-cresol, 4-nitrobenzyl chloride). We found clearly different toxicity when the exposure order of two toxicants was reversed, while maintaining the same dose. Slow toxicodynamic recovery caused carry-over toxicity in subsequent exposures, thereby resulting in a sequence effect-but only when toxicodynamic recovery was slow relative to the interval between exposures. This suggests that carry-over toxicity is a useful proxy for organism fitness and that risk assessment methods should be revised as they currently could underestimate risk. We provide the first evidence that carry-over toxicity occurs among chemicals acting on different targets and when exposure is several days apart. It is therefore not only the dose that makes the poison but also the exposure sequence.

Revealing the complex effects of salinity on copper toxicity in an estuarine clam Potamocorbula laevis with a toxicokinetic-toxicodynamic model

The effects of salinity on metal toxicity are complex: not only affecting metal bioaccumulation, but also altering the physiology and sensitivity of organisms. In this study, we used a toxicokinetic-toxicodynamic (TK-TD) model to separate and quantify the dual effects of salinity on copper (Cu) toxicity in a euryhaline clam Potamocorbula laevis. The toxicokinetics of Cu was determined using the stable isotope ⁶⁵Cu as a tracer at concentrations (10-500 μg L^-1) realistic to contaminated environments and at salinities ranging from 5 to 30. At low Cu concentrations (ca. 10 μg L^-1), Cu bioaccumulation decreased monotonically with salinity, and the uptake rate constant (k_u, 0.546 L g^-1 h^-1 to 0.213 L g^-1 h^-1) fitted well with an empirical equation, k_u = 1/(1.35 + 0.116·Salinity), by treating salinity as a pseudo-competitor. The median lethal concentrations (LC₅₀s) of Cu were 269, 224, and 192 μg L^-1 at salinity 5, 15, and 30, respectively. At high Cu concentrations (ca. 500 μg L^-1), elevating salinity were much less effective in decreasing Cu bioaccumulation; whereas Cu toxicity increased with salinity. The increased toxicity could be explained by the increases in Cu killing rates (k_ks), which were estimated to be 0.44-2.08 mg μg^-1 h^-1 and were presumably due to the osmotic stress caused by the deviation from the optimal salinity of the clams. The other toxicodynamic parameter, internal threshold concentration (C_IT), ranged from 79 to 133 μg^-1 g^-1 and showed no clear trend with salinity.

Toward refined environmental scenarios for ecological risk assessment of down-the-drain chemicals in freshwater environments

Current regulatory practice for chemical risk assessment suffers from the lack of realism in conventional frameworks. Despite significant advances in exposure and ecological effect modeling, the implementation of novel approaches as high-tier options for prospective regulatory risk assessment remains limited, particularly among general chemicals such as down-the-drain ingredients. While reviewing the current state of the art in environmental exposure and ecological effect modeling, we propose a scenario-based framework that enables a better integration of exposure and effect assessments in a tiered approach. Global- to catchment-scale spatially explicit exposure models can be used to identify areas of higher exposure and to generate ecologically relevant exposure information for input into effect models. Numerous examples of mechanistic ecological effect models demonstrate that it is technically feasible to extrapolate from individual-level effects to effects at higher levels of biological organization and from laboratory to environmental conditions. However, the data required to parameterize effect models that can embrace the complexity of ecosystems are large and require a targeted approach. Experimental efforts should, therefore, focus on vulnerable species and/or traits and ecological conditions of relevance. We outline key research needs to address the challenges that currently hinder the practical application of advanced model-based approaches to risk assessment of down-the-drain chemicals. Integr Environ Assess Manag 2017;13:233-248. © 2016 SETAC.

From the exposome to mechanistic understanding of chemical-induced adverse effects

The exposome encompasses an individual's exposure to exogenous chemicals, as well as endogenous chemicals that are produced or altered in response to external stressors. While the exposome concept has been established for human health, its principles can be extended to include broader ecological issues. The assessment of exposure is tightly interlinked with hazard assessment. Here, we explore if mechanistic understanding of the causal links between exposure and adverse effects on human health and the environment can be improved by integrating the exposome approach with the adverse outcome pathway (AOP) concept that structures and organizes the sequence of biological events from an initial molecular interaction of a chemical with a biological target to an adverse outcome. Complementing exposome research with the AOP concept may facilitate a mechanistic understanding of stress-induced adverse effects, examine the relative contributions from various components of the exposome, determine the primary risk drivers in complex mixtures, and promote an integrative assessment of chemical risks for both human and environmental health.

Modelling survival: exposure pattern, species sensitivity and uncertainty

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

Computationally Efficient Implementation of a Novel Algorithm for the General Unified Threshold Model of Survival (GUTS)

The General Unified Threshold model of Survival (GUTS) provides a consistent mathematical framework for survival analysis. However, the calibration of GUTS models is computationally challenging. We present a novel algorithm and its fast implementation in our R package, GUTS, that help to overcome these challenges. We show a step-by-step application example consisting of model calibration and uncertainty estimation as well as making probabilistic predictions and validating the model with new data. Using self-defined wrapper functions, we show how to produce informative text printouts and plots without effort, for the inexperienced as well as the advanced user. The complete ready-to-run script is available as supplemental material. We expect that our software facilitates novel re-analysis of existing survival data as well as asking new research questions in a wide range of sciences. In particular the ability to quickly quantify stressor thresholds in conjunction with dynamic compensating processes, and their uncertainty, is an improvement that complements current survival analysis methods.