Comparing Sensitivity of Different Bee Species to Pesticides: A TKTD modeling approach.

Risk assessment for bees is mainly based on data for honey bees; however, risk assessment is intended to protect all bee species. This raises the question of whether data for honey bees are a good proxy for other bee species. This issue is not new and has resulted in several publications in which the sensitivity of bee species is compared based on the values of the 48-h median lethal dose (LD50) from acute test results. When this approach is used, observed differences in sensitivity may result both from differences in kinetics and from inherent differences in species sensitivity. In addition, the physiology of the bee, like its overall size, the size of the honey stomach (for acute oral tests), and the physical appearance (for acute contact tests) also influences the sensitivity of the bee. The recently introduced Toxicokinetic-Toxicodynamic (TKTD) model that was developed for the interpretation of honey bee tests (Bee General Uniform Threshold Model for Survival [BeeGUTS]) could integrate the results of acute oral tests, acute contact tests, and chronic tests within one consistent framework. We show that the BeeGUTS model can be calibrated and validated for other bee species and also that the honey bee is among the more sensitive bee species. In addition, we found that differences in sensitivity between species are smaller than previously published comparisons based on 48-h LD50 values. The time-dependency of the LD50 and the specifics of the bee physiology are the main causes of the wider variation found in the published literature. Environ Toxicol Chem 2024;00:1-11. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Toxicokinetic-Toxicodynamic Model to Assess Thermal Stress.

Temperature is a crucial environmental factor affecting the distribution and performance of ectothermic organisms. This study introduces a new temperature damage model to interpret their thermal stress. Inspired by the ecotoxicological damage model in the General Unified Threshold model for Survival (GUTS) framework, the temperature damage model assumes that damage depends on the balance between temperature-dependent accumulation and constant repair. Mortality due to temperature stress is driven by the damage level exceeding a threshold. Model calibration showed a good agreement with the measured survival of Gammarus pulex exposed to different constant temperatures. Further, model simulations, including constant temperatures, daily temperature fluctuations, and heatwaves, demonstrated the model's ability to predict temperature effects for various environmental scenarios. With this, the present study contributes to the mechanistic understanding of temperature as a single stressor while facilitating the incorporation of temperature as an additional stressor alongside chemicals in mechanistic multistressor effect models.

BeeGUTS-A Toxicokinetic-Toxicodynamic Model for the Interpretation and Integration of Acute and Chronic Honey Bee Tests.

Understanding the survival of honey bees after pesticide exposure is key for environmental risk assessment. Currently, effects on adult honey bees are assessed by Organisation for Economic Co-operation and Development standardized guidelines, such as the acute and chronic oral exposure and acute contact exposure tests. The three different tests are interpreted individually, without consideration that the same compound is investigated in the same species, which should allow for an integrative assessment. In the present study we developed, calibrated, and validated a toxicokinetic-toxicodynamic model with 17 existing data sets on acute and chronic effects for honey bees. The model is based on the generalized unified threshold model for survival (GUTS), which is able to integrate the different exposure regimes, taking into account the physiology of the honey bee: the BeeGUTS model. The model is able to accurately describe the effects over time for all three exposure routes combined within one consistent framework. The model can also be used as a validity check for toxicity values used in honey bee risk assessment and to conduct effect assessments for real-life exposure scenarios. This new integrative approach, moving from single-point estimates of toxicity and exposure to a holistic link between exposure and effect, will allow for a higher confidence of honey bee toxicity assessment in the future. Environ Toxicol Chem 2022;41:2193-2201. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Significant decline of Daphnia magna population biomass due to microplastic exposure.

Even though microplastics are intensively studied, the focus of the research is mainly on relatively short term effects at high doses. Therefore there is a need to shift the focus toward more realistic, longer-term endpoints. Studies with a range of chemicals have shown that the response of populations often differs from studies in which a single organism is exposed in an individual container (as often described within standard ecotox screening assays). Here we investigate the impact of primary microplastics (1-5 µm in size) on a population of Daphnia magna. We first allowed a stable population of D. magna to develop over 29 d, after which the populations were exposed to microplastics for three weeks (concentrations ranging from 102 to 105 particles mL-1 and a control). We found a significant impact of microplastics on the total population of D. magna, with a reduction in the amount of adult daphnids. Importantly, when expressed as total biomass, exposure to 105 microplastics mL-1 resulted in a 21% reduction in total biomass compared to control. These results indicate that exposure to microplastics can result in significant adverse effects on the population of D. magna, including a reduction in the number of individuals as well as total biomass. Given the importance of D. magna in freshwater food webs, both as a grazer as well as a food source, this can potentially impact the functioning of the ecosystem.

Acute toxicity of organic pesticides to Daphnia magna is unchanged by co-exposure to polystyrene microplastics.

Daphnia magna were exposed to two pesticides in the presence or absence of microplastics (300 000 particles ml-1 1 µm polystyrene spheres) and to microplastics alone. The pesticides were dimethoate, an organophosphate insecticide with a low log Kow, and deltamethrin, a pyrethroid insecticide with a high log Kow. Daphnia were exposed to a nominal concentration range of 0.15, 0.31, 0.63, 1.25, 2.5, 5 mg l-1 dimethoate and 0.016, 0.08, 0.4, 2, 5 and 10 µg l-1 deltamethrin. Exposure to polystyrene microplastics alone showed no effects on Daphnia magna survival and mobility over a 72 h exposure. In the dimethoate exposures, mobility and survival were both affected from a concentration of 1.25 mg l-1, with effects were seen on mobility from 28 h and survival from 48 h, with greater effects seen with increasing concentration and exposure time. In deltamethrin exposures, survival was affected from a concentration of 0.4 µg l-1 and mobility from a concentration of 0.08 µg l-1. Effects of deltamethrin on mobility were seen from 5 h and on survival from 28 h, with greater effects on survival and mobility seen with increasing concentration and exposure time. Contrary to expectations, pesticide toxicity to Daphnia magna was not affected by the presence of microplastics, regardless of chemical binding affinity (log Kow). This therefore suggests that polystyrene microplastics are unlikely to act as a significant sink, nor as a vector for increased uptake of pesticides by aquatic organisms. CAPSULE: Polystyrene microplastics are unlikely to act as vector for increased uptake of pesticides by aquatic organisms.

Acute sensitivity of three Cladoceran species to different types of microplastics in combination with thermal stress.

Microplastics (<5 mm, MP) are ubiquitously distributed in the environment, causing increasing concern regarding their potential toxicity to organisms. To date, most research has focussed on the impacts of MPs on marine and estuarine organisms, with fewer studies focussing on the effects of microplastics on freshwater ecosystems, especially under different environmental conditions. In the present study, the sensitivity of two temperate Cladoceran species, Daphnia magna and Daphnia pulex, and a smaller tropical species Ceriodaphnia dubia, to primary microplastics (PMP) and secondary (weathered) microplastics (SMP) was assessed. A prolonged acute toxicity assay (up to 72 or 96 h) was performed at 18°, 22°, and 26 °C, to determine the influence of temperature as an additional stressor and survival data were analysed using toxicokinetic-toxicodynamic (TK-TD) model. Acute sensitivity of D. magna and D. pulex to both PMP and SMP increased sharply with temperature, whereas that of C. dubia remained relatively stable across temperatures. C. dubia was the most sensitive species at 18 °C, followed by D. pulex and D. magna, which were of comparable sensitivity. However, this ranking was reversed at 26 °C as could be seen from the No Effect Concentration (NEC) estimates of the TK-TD model. In addition, SMP and PMP had a similar effect on D. magna and D. pulex, but PMP was more toxic to C. dubia. Effects on survival were strongly time-dependent and became substantially more severe after the standard 48 h test period. Our results indicate that sensitivity to microplastics may differ between species for different types of microplastics, and could be drastically influenced by temperature albeit at high exposure concentrations.

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.

Comparing bee species responses to chemical mixtures: Common response patterns?

Pollinators in agricultural landscapes can be exposed to mixtures of pesticides and environmental pollutants. Existing mixture toxicity modelling approaches, such as the models of concentration addition and independent action and the mechanistic DEBtox framework have been previously shown as valuable tools for understanding and ultimately predicting joint toxicity. Here we apply these mixture models to investigate the potential to interpret the effects of semi-chronic binary mixture exposure for three bee species: Apis mellifera, Bombus terrestris and Osmia bicornis within potentiation and mixture toxicity experiments. In the potentiation studies, the effect of the insecticide dimethoate with added propiconazole fungicide and neonicotinoid insecticide clothianidin with added tau-fluvalinate pyrethroid acaricide showed no difference in toxicity compared to the single chemical alone. Clothianidin toxicity showed a small scale, but temporally conserved increase in exposure conducted in the presence of propiconazole, particularly for B. terrestris and O. bicornis, the latter showing a near three-fold increase in clothianidin toxicity in the presence of propiconazole. In the mixture toxicity studies, the dominant response patterns were of additivity, however, binary mixtures of clothianidin and dimethoate in A. mellifera, B. terrestris and male O. bicornis there was evidence of a predominant antagonistic interaction. Given the ubiquitous nature of exposures to multiple chemicals, there is an urgent need to consider mixture effects in pollinator risk assessments. Our analyses suggest that current models, particularly those that utilise time-series data, such as DEBtox, can be used to identify additivity as the dominant response pattern and also those examples of interactions, even when small-scale, that may need to be taken into account during risk assessment.

Comparative toxicity of pesticides and environmental contaminants in bees: Are honey bees a useful proxy for wild bee species?

Threats to wild and managed insect pollinators in Europe are cause for both ecological and socio-economic concern. Multiple anthropogenic pressures may be exacerbating pollinator declines. One key pressure is exposure to chemicals including pesticides and other contaminants. Historically the honey bee (Apis mellifera spp.) has been used as an 'indicator' species for 'standard' ecotoxicological testing but it has been suggested that it is not always a good proxy for other types of eusocial and solitary bees because of species differences in autecology and sensitivity to various stressors. We developed a common toxicity test system to conduct acute and chronic exposures of up to 240h of similar doses of seven chemicals, targeting different metabolic pathways, on three bee species (Apis mellifera spp., Bombus terrestris and Osmia bicornis). We compared the relative sensitivity between species in terms of potency between the chemicals and the influence of exposure time on toxicity. While there were significant interspecific differences that varied through time, overall the magnitude of these differences (in terms of treatment effect ratios) was generally comparable (<2 fold) although there were some large divergences from this pattern. Our results suggest that A. mellifera spp. could be used as a proxy for other bee species provided a reasonable assessment factor is used to cover interspecific variation. Perhaps more importantly our results show significant and large time dependency of toxicity across all three tested species that greatly exceeds species differences (>25 fold within test). These are rarely considered in standard regulatory testing but may have severe environmental consequences, especially when coupled with the likelihood of differential species exposures in the wild. These insights indicate that further work is required to understand how differences in toxicokinetics vary between species and mixtures of chemicals.

Comparison and evaluation of pesticide monitoring programs using a process-based mixture model.

A number of European countries run large-scale pesticide monitoring schemes in watersheds aimed at identifying and evaluating the presence of pesticide residues in the environment. These schemes provide national and regional scale assessments of pesticide concentrations within the context of environmental quality assessment, aiming to ensure some degree of ecological protection. The present study is aimed at evaluating the joint effects of the pesticide mixtures detected in monitoring programs, using a process-based mixture model that was parameterized for Daphnia magna. In total, over 15 000 samples containing over 1 million individual measurements were evaluated for effects. It was found that there are only a small number of places where one can expect to have effects on daphnids, based on measured concentrations. The most polluted samples would cause extinction of a daphnid population within only 30 h. The results show that effects are mostly triggered by a limited number of pesticide residues at locations with high emissions. It was also shown that the analytical detection limits are basically too high to exclude mixture effects. So, despite all the effort that is put into chemical monitoring programs, it remains a challenge to make statements on whether or not the environment is protected. Recommendations are offered for a different setup of monitoring programs to improve this situation. Environ Toxicol Chem 2016;35:3113-3123. © 2016 SETAC.

Evaluating the Combined Toxicity of Cu and ZnO Nanoparticles: Utility of the Concept of Additivity and a Nested Experimental Design.

Little is understood regarding the effects of mixtures of different metal-based nanoparticles (NPs). Using concentration-addition (CA) and independent-action (IA) models, we evaluated the combined toxicity of Cu and ZnO NPs based on five nested combinations, i.e., Cu(NO3)2-CuNPs, Zn(NO3)2-ZnONPs, Cu(NO3)2-ZnONPs, Zn(NO3)2-CuNPs, and CuNPs-ZnONPs on root elongation of Lactuca sativa L. The CA and IA models performed equally well in estimating the toxicity of mixtures of Cu(NO3)2-CuNPs, Zn(NO3)2-ZnONPs, and Zn(NO3)2-CuNPs, whereas the IA model was significantly better for fitting the data of Cu(NO3)2-ZnONPs and CuNPs-ZnONPs mixtures. Dissolved Cu proved to be the most toxic metal species to lettuce roots in the tests, followed by Cu NPs, dissolved Zn, and ZnO NPs, respectively. An antagonistic effect was observed for ZnO NPs on the toxicity of Cu NPs. This antagonistic effect is expected to be the result of interactions between dissolved Cu and dissolved Zn, particulate Zn and dissolved Zn, particulate Cu and dissolved Zn, and between particulate Zn and dissolved Cu. In general terms, assuming additivity gives a first indication of the combined toxicity with soluble and insoluble metal particles, both being important in driving the toxicity of metal-based NPs to higher plants.

Statistically significant deviations from additivity: What do they mean in assessing toxicity of mixtures?

There is increasing attention from scientists and policy makers to the joint effects of multiple metals on organisms when present in a mixture. Using root elongation of lettuce (Lactuca sativa L.) as a toxicity endpoint, the combined effects of binary mixtures of Cu, Cd, and Ni were studied. The statistical MixTox model was used to search deviations from the reference models i.e. concentration addition (CA) and independent action (IA). The deviations were subsequently interpreted as 'interactions'. A comprehensive experiment was designed to test the reproducibility of the 'interactions'. The results showed that the toxicity of binary metal mixtures was equally well predicted by both reference models. We found statistically significant 'interactions' in four of the five total datasets. However, the patterns of 'interactions' were found to be inconsistent or even contradictory across the different independent experiments. It is recommended that a statistically significant 'interaction', must be treated with care and is not necessarily biologically relevant. Searching a statistically significant interaction can be the starting point for further measurements and modeling to advance the understanding of underlying mechanisms and non-additive interactions occurring inside the organisms.

Sensitivity of animals to chemical compounds links to metabolic rate.

Ecotoxicological studies have shown considerable variation in species sensitivity for chemical compounds, but general patterns in sensitivity are still not known. A better understanding of this sensitivity is important in the context of environmental risk assessment but also in a more general ecological and evolutionary one. We investigated the metabolic rate or more precise the specific somatic maintenance (expressed in J cm(-3) d(-1), at a standardised body temperature of 20 °C) on the sensitivity of a species to chemical poisoning. The sensitivity of a species was expressed in terms of its threshold concentration for survival, the no effect concentrations (NEC, in µmol/L). Somatic maintenance data were based on the 'add-my-pet' database hosted by the VU University of Amsterdam. NECs were derived from the US-EPA ECOTOX database. We focussed on four pesticides; two that need a metabolic activation, Chlorpyrifos and Malathion, and two without metabolic activation, carbofuran and carbaryl. All four pesticides showed a similar response: a strong negative correlation between the specific somatic maintenance and the NEC. We discuss possible explanations, deviations and ecological implications.

Interaction between nickel and cobalt toxicity in Enchytraeus crypticus is due to competitive uptake.

Uptake and toxicity of Ni-Co mixtures in Enchytraeus crypticus were determined after 4 d, 7 d, 10 d, and 14 d exposure. Generally, body concentrations of Ni and Co increased with increasing exposure concentrations. Ni body concentration was significantly reduced in the presence of Co, whereas Ni only marginally affected Co uptake. When expressed as free ion activities, individual toxicity of Ni and Co increased with time, with median lethal concentrations (LC50) decreasing from 78.3 µM and 511 µM at 4 d to 40.4 µM and 393 µM at 14 d, respectively. When expressed as body concentrations, LC50BodyNi remained constant with time whereas LC50BodyCo increased during the first 7 d but remained stable afterwards. As identified by the MIXTOX model, interactions between Ni and Co were mainly antagonistic when based on free ion activities, however, no interaction was observed when based on body concentrations. A process-based model, incorporating exposure time to analyze the mechanisms underlying the dynamic mixture toxicity confirmed the differences in toxicokinetics of the 2 metals. The author's findings suggest that body concentrations, which incorporate bioaccumulation processes, are time-independent and can act as a more constant indicator of metal toxicity. The observed antagonism was mainly caused by competition between Co and Ni for binding sites and subsequent inhibition of Ni uptake. This competitive interaction occurred at the uptake level (toxicokinetics), but not at the target level (toxicodynamics).

Time is of the essence.

An organism is a dynamic system, and its life history results from underlying processes in time. The effects of biological and chemical stressors on this system therefore also change temporally. In the present short communication, we emphasize the importance of including time as a factor in stress ecology and ecotoxicology and argue that current standard test protocols may benefit considerably from this, improving data interpretation and thus also risk assessment and risk management.

A biology-based approach for mixture toxicity of multiple endpoints over the life cycle.

Typical approaches for analyzing mixture ecotoxicity data only provide a description of the data; they cannot explain observed interactions, nor explain why mixture effects can change in time and differ between endpoints. To improve our understanding of mixture toxicity we need to explore biology-based models. In this paper, we present an integrated approach to deal with the toxic effects of mixtures on growth, reproduction and survival, over the life cycle. Toxicokinetics is addressed with a one-compartment model, accounting for effects of growth. Each component of the mixture has its own toxicokinetics model, but all compounds share the effect of body size on uptake kinetics. The toxicodynamic component of the method is formed by an implementation of dynamic energy budget theory; a set of simple rules for metabolic organization that ensures conservation of mass and energy. Toxicant effects are treated as a disruption of regular metabolic processes such as an increase in maintenance costs. The various metabolic processes interact, which means that mixtures of compounds with certain mechanisms of action have to produce a response surface that deviates from standard models (such as 'concentration addition'). Only by separating these physiological interactions from the chemical interactions between mixture components can we hope to achieve generality and a better understanding of mixture effects. For example, a biology-based approach allows for educated extrapolations to other mixtures, other species, and other exposure situations. We illustrate our method with the interpretation of partial life-cycle data for two polycyclic aromatic hydrocarbons in Daphnia magna.

A review of DEB theory in assessing toxic effects of mixtures.

In this manuscript we review the use of mechanistic models to interpret effects of mixtures of compounds within the framework of the Dynamic Energy Budget (DEB) theory. Within this approach the effect of a mixture is built up from the effects of the individual components making up the mixture. Understanding effects of mixtures is essential as it is impossible to assess effects of all possible mixtures experimentally. In contrast to the more classical way of interpreting effects of mixtures with concentration addition or effect addition models, DEB theory offers a single consistent framework to understand effects of mixtures on growth, reproduction and survival in an integrated, way. It systematically incorporates exposure time and biology of the organisms, including the natural links between the processes of feeding, maintenance, growth, development and reproduction. We also give directions for an experimental setup to interpret the results within the DEB framework. The DEB framework was successfully applied to assess effects of complex mixtures on survival and binary mixtures on sub-lethal endpoints. It gives the possibility to explain observed interactions by the underlying biological mechanisms or pinpoint interactions. We expect this approach to help in identifying key mechanisms and enable to focus further research in cooperation with modelers and experimentalists to improve our understanding of the mechanisms underlying mixture toxicity.

Model-based experimental design for assessing effects of mixtures of chemicals.

We exposed flour beetles (Tribolium castaneum) to a mixture of four poly aromatic hydrocarbons (PAHs). The experimental setup was chosen such that the emphasis was on assessing partial effects. We interpreted the effects of the mixture by a process-based model, with a threshold concentration for effects on survival. The behavior of the threshold concentration was one of the key features of this research. We showed that the threshold concentration is shared by toxicants with the same mode of action, which gives a mechanistic explanation for the observation that toxic effects in mixtures may occur in concentration ranges where the individual components do not show effects. Our approach gives reliable predictions of partial effects on survival and allows for a reduction of experimental effort in assessing effects of mixtures, extrapolations to other mixtures, other points in time, or in a wider perspective to other organisms.

Understanding toxicity as processes in time.

Studies in ecotoxicology usually focus on a single end point (typically mortality, growth, or reproduction) at a standardized exposure time. The exposure time is chosen irrespective of the properties of the chemical under scrutiny, but should depend on the organism of choice in combination with the compound(s) of interest. This paper discusses the typical patterns for toxic effects in time that can be observed for the most encountered endpoints growth reproduction and survival. Ignoring the fact that toxicity is a process in time can lead to severe bias in environmental risk assessment. We show that especially EC(x) values for sublethal endpoints can show very distinct patterns in time. We recommend that the test duration for survival as an endpoint should be extended till the incipient LC(50) is observed. Given the fact that toxicity data for single compounds show clear patterns in time, it is to be expected that effects of mixtures will also be strongly dependent on time. The few examples that have been published support this statement.

Chemical contamination and the ecological quality of surface water.

In the assessment of the quality of surface waters, the typical procedure is that the concentration of contaminants in the surface water is monitored and subsequently compared with their respective Maximum Permissible Concentrations (MPCs). If the MPCs are not exceeded the water quality is considered to be safe. But can we be certain that this is true? We compared MPCs to observed and calculated effects of measured contaminants in Dutch surface waters and showed that effects of mixtures can cause a daphnid population to go extinct within 30h of exposure even when MPCs are not exceeded. We conclude that there are shortcomings underlying the concepts of the MPCs. And that the MPCs aim to protect 95% of all species is not met.