The effect of temperature on toxicokinetics and the chronic toxicity of insecticides towards Gammarus pulex

Huang, Anna; Mangold-Döring, Annika; Guan, Huitong; Boerwinkel, Marie-Claire; Belgers, Dick; Focks, Andreas

doi:10.1016/j.scitotenv.2022.158886

Cited by 19 publications

(23 citation statements)

References 49 publications

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“…Elimination processes mediated by enzyme activity (e.g., biotransformation) will likely also show an increase with increasing temperature, at least up to the enzyme’s temperature optima. As reported in Huang and Mangold-Döring et al, the biotransformation of IMI to IMI-ole increased 2.2-fold from 18 to 24 °C, also visible in the TK-T model fits of this study (Supporting Information 01, Figure S2). Unfortunately, the temperature influence on elimination rates appeared to be understudied for aquatic organisms.…”

Section: Discussionsupporting

confidence: 92%

“…Thus, by explicitly accounting for temperature in the TK-T model, it is possible to describe the toxicokinetic processes of IMI and FPF in G. pulex by one parameter set per chemical (Supporting Information 01, Table S2), in contrast to three separate factors parameter sets in the conventional approach previously used. 14 However, the observed temperature influence in the previous study was different between the uptake and the elimination rates (i.e., for IMI, a 2.1-fold difference of k u and a 4.9-fold difference of k e ) and between the two insecticides (with only a 1.3-fold difference for k u and a 3.1-fold difference of k e for FPF). Thus, with the data currently available for the uptake kinetics of FPF, we found no significant scaling with temperature (also see the reasoning in the Results section) and therefore treated this rate to be constant in the TK-T approach.…”

Section: ■ Materials and Methodsmentioning

confidence: 76%

“…For comparison, we can consult the results of the previous analysis of the measured survival data . The LC 10 and LC 50 values obtained from the concentration–response curve analysis based on a log-logistic regression decreased with increasing temperature for both compounds, suggesting increased toxicity of both compounds with increasing temperature in the range of 7–11 °C, in line with the analysis in this study.…”

Section: Discussionmentioning

confidence: 99%

“…We applied the full version of the model (GUTS-FULL), which is calibrated on both survival data and internal concentrations. These data were obtained from TK and toxicity experiments previously published …”

Section: Materials and Methodsmentioning

confidence: 99%

“…The resulting models were calibrated to data from the previously published TK experiments (conducted at 7, 18, and 24 °C) and toxicity experiments (conducted at 7, 11, and 15 °C) with G. pulex exposed to IMI and FPF . Briefly, both experiments were conducted with field caught G.…”

Section: Materials and Methodsmentioning

confidence: 99%

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Explicit Consideration of Temperature Improves Predictions of Toxicokinetic–Toxicodynamic Models for Flupyradifurone and Imidacloprid in Gammarus pulex

Mangold-Döring

Huang

Nes

et al. 2022

Environ. Sci. Technol.

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In the face of global climate change, where temperature fluctuations and the frequency of extreme weather events are increasing, it is needed to evaluate the impact of temperature on the ecological risk assessment of chemicals. Current state-of-the-art mechanistic effect models, such as toxicokinetic–toxicodynamic (TK–TD) models, often do not explicitly consider temperature as a modulating factor. This study implemented the effect of temperature in a widely used modeling framework, the General Unified Threshold model for Survival (GUTS). We tested the model using data from toxicokinetic and toxicity experiments with Gammarus pulex exposed to the insecticides imidacloprid and flupyradifurone. The experiments revealed increased TK rates with increasing temperature and increased toxicity under chronic exposures. Using the widely used Arrhenius equation, we could include the temperature influence into the modeling. By further testing of different model approaches, differences in the temperature scaling of TK and TD model parameters could be identified, urging further investigations of the underlying mechanisms. Finally, our results show that predictions of TK–TD models improve if we include the toxicity modulating effect of temperature explicitly.

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Section: Discussionsupporting

confidence: 92%

Section: ■ Materials and Methodsmentioning

confidence: 76%

Section: Discussionmentioning

confidence: 99%

Section: Materials and Methodsmentioning

confidence: 99%

Section: Materials and Methodsmentioning

confidence: 99%

See 3 more Smart Citations

Explicit Consideration of Temperature Improves Predictions of Toxicokinetic–Toxicodynamic Models for Flupyradifurone and Imidacloprid in Gammarus pulex

Mangold-Döring

Huang

Nes

et al. 2022

Environ. Sci. Technol.

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A Toxicokinetic–Toxicodynamic Modeling Workflow Assessing the Quality of Input Mortality Data

Bauer,

Singer,

Gao

et al. 2023

Enviro Toxic and Chemistry

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Abstract:Toxicokinetic‐toxicodynamic (TKTD) models simulate organismal uptake and elimination of a substance (TK) and its effects on the organism (TD). The Reduced General Unified Threshold model of Survival (GUTS‐RED) is a TKTD modelling framework that is well established for aquatic risk assessment to simulate effects on survival. TKTD models are applied in three steps: parameterization based on experimental data (calibration), comparing predictions to independent data (validation) and prediction of endpoints under environmental scenarios. Despite a clear understanding of GUTS‐RED predictions’ sensitivity to the model parameters, the influence of the input data on the quality of GUTS‐RED calibration and validation is not systematically explored. We analyzed performance of GUTS‐RED calibration and validation based on a unique, comprehensive dataset, covering different types of substances, exposure patterns and aquatic animal species taxa that are regularly used for risk assessment of plant protection products. We developed a software code to automatically calibrate and validate GUTS‐RED against survival measurements from 59 toxicity tests and calculate selected model evaluation metrics. To assess whether specific survival data sets were better suited for calibration or validation, we applied a design where all possible combinations of studies for the same species‐substance combination are used for calibration and validation. We found that uncertainty of calibrated parameters was lower when the full range of effects (i.e. from high survival to high mortality) was covered by input data. Increasing the number of toxicity studies used for calibration, further decreased parameter uncertainty. Including data from both acute and chronic studies as well as studies under pulsed and constant exposure in model calibrations improved model predictions on different types of validation data. Using our results we derive a workflow, including recommendations for the sequence of modelling steps from the selection of input data to a final judgement on the suitability of GUTS‐RED for the dataset.

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Integrating climate model projections into environmental risk assessment: A probabilistic modeling approach

Moe,

Brix,

Landis

et al. 2024

Integr Envir Assess & Manag

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The Society of Environmental Toxicology and Chemistry (SETAC) convened a Pellston workshop in 2022 to examine how information on climate change could be better incorporated into the ecological risk assessment (ERA) process for chemicals as well as other environmental stressors. A major impetus for this workshop is that climate change can affect components of ecological risks in multiple direct and indirect ways, including the use patterns and environmental exposure pathways of chemical stressors such as pesticides, the toxicity of chemicals in receiving environments, and the vulnerability of species of concern related to habitat quality and use. This paper explores a modeling approach for integrating climate model projections into the assessment of near‐ and long‐term ecological risks, developed in collaboration with climate scientists. State‐of‐the‐art global climate modeling and downscaling techniques may enable climate projections at scales appropriate for the study area. It is, however, also important to realize the limitations of individual global climate models and make use of climate model ensembles represented by statistical properties. Here, we present a probabilistic modeling approach aiming to combine projected climatic variables as well as the associated uncertainties from climate model ensembles in conjunction with ERA pathways. We draw upon three examples of ERA that utilized Bayesian networks for this purpose and that also represent methodological advancements for better prediction of future risks to ecosystems. We envision that the modeling approach developed from this international collaboration will contribute to better assessment and management of risks from chemical stressors in a changing climate.

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The effect of temperature on toxicokinetics and the chronic toxicity of insecticides towards Gammarus pulex

Cited by 19 publications

References 49 publications

Explicit Consideration of Temperature Improves Predictions of Toxicokinetic–Toxicodynamic Models for Flupyradifurone and Imidacloprid in Gammarus pulex

Explicit Consideration of Temperature Improves Predictions of Toxicokinetic–Toxicodynamic Models for Flupyradifurone and Imidacloprid in Gammarus pulex

A Toxicokinetic–Toxicodynamic Modeling Workflow Assessing the Quality of Input Mortality Data

Integrating climate model projections into environmental risk assessment: A probabilistic modeling approach

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