Time‐Variable Exposure Experiments in Conjunction with Higher Tier Population and Effect Modeling to Assess the Risk of Chlorotoluron to Green Algae

Weber, Denis; Weyman, Gabriel S.; Fruhmann, Thomas; Gagniarre, Marion; Minten, Barbara; Memmert, U.

doi:10.1002/etc.4544

Cited by 3 publications

(10 citation statements)

References 42 publications

(61 reference statements)

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“…Validation of the full Simple Algae Model Extended model using original data from Weber et al (2012, 2019). Top panels give the model predictions relative to data points derived from a flow‐through experiment.…”

Section: Resultsmentioning

confidence: 99%

“…The full SAM-X model was implemented in R, following Weber et al (2012Weber et al ( , 2019. The model consists of four ordinary differential equations (ODEs).…”

Section: Full Model Implementationmentioning

confidence: 99%

“…The validation data used in the present study for chlorotoluron and isoproturon are available in Weber et al (2012Weber et al ( , 2019, respectively. Both of these validation data sets were generated in flow-through chemostat systems with constant light and temperature conditions.…”

Section: Experimental Validation Datamentioning

confidence: 99%

“…Both of these validation data sets were generated in flow-through chemostat systems with constant light and temperature conditions. Full details are available in Weber et al (2012Weber et al ( , 2019. In selecting between the full and the simplified model for validation, we must consider the growth conditions in the experiment.…”

Section: Experimental Validation Datamentioning

confidence: 99%

“…Therefore, the model contains no TK module; and the parameters EC50 and slope at EC50 correspond to those from the standard growth inhibition study, and no model calibration is initially required. Instead, the generic physiological parameters of the algae species can be (Weber, 2019) and isoproturon (Weber et al, 2012) used together with the EC50 and slope at EC50 from the standard growth inhibition study.…”

Section: Model Parameterizationmentioning

confidence: 99%

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A Framework for Algae Modeling in Regulatory Risk Assessment

Rendal

Witt

Preuß

et al. 2023

Enviro Toxic and Chemistry

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The use of toxicokinetic-toxicodynamic (TKTD) modeling in regulatory risk assessment of plant protection products is increasingly popular, especially since the 2018 European Food Safety Authority (EFSA) opinion on TKTD modeling announced that several established models are ready for use in risk assessment. With careful adherence to the guidelines laid out by EFSA, we present a stepwise approach to validation and use of the Simple Algae Model Extended (SAM-X) for regulatory submission in Tier 2C. We demonstrate how the use of moving time windows across time-variable exposure profiles can generate thousands of virtual laboratory mimic simulations that seamlessly predict the effects of time-variable exposures across a full exposure profile while maintaining the laboratory conditions of the standard Organisation for Economic Co-operation and Development (OECD) growth inhibition test. Thus, every virtual laboratory test has a duration of 72 h, with OECD medium and constant light and temperature conditions. The only deviation from the standard test setup is the replacement of constant exposure conditions for time-variable concentrations. The present study demonstrates that for simulation of 72-h toxicity tests, the nutrient dynamics in the SAM-X model are not required, and we propose the alternative use of a simplified model version. For risk assessment, in accordance with the EFSA guidelines we use a median exposure profile of 10 as a threshold, meaning that if a time window within the exposure profile causes 50% growth inhibition when magnified by a factor of 10, the threshold will have been exceeded. We present a simplified example for chlorotoluron and isoproturon. The present case study brings to life our proposed framework for TKTD modeling of algae to establish whether a given exposure can be considered to be of low risk.

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Section: Resultsmentioning

confidence: 99%

“…The full SAM-X model was implemented in R, following Weber et al (2012Weber et al ( , 2019. The model consists of four ordinary differential equations (ODEs).…”

Section: Full Model Implementationmentioning

confidence: 99%

Section: Experimental Validation Datamentioning

confidence: 99%

Section: Experimental Validation Datamentioning

confidence: 99%

Section: Model Parameterizationmentioning

confidence: 99%

See 3 more Smart Citations

A Framework for Algae Modeling in Regulatory Risk Assessment

Rendal

Witt

Preuß

et al. 2023

Enviro Toxic and Chemistry

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A critical review of effect modeling for ecological risk assessment of plant protection products

Larras

Charles

Chaumot

et al. 2022

Environ Sci Pollut Res

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A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can hâve ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modelling approaches enabling the assessment of PPP effects (inc.luding biopesticides) on the biota. Six categories of models were inventoried: QSAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, and address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem ser vices protection). Among them, mechanistic models are increasingly recognized by EFSA for P P P regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multi-generational effects, multiple biotic and abiotic stressors. ..). This review also underlines a lack of model testing by rneans of fleld data and of sensitivity and uncertainty analyses. Accurate and robust modelling of PPP effects and other stressors on living organisms, from their application in the ffeld to their functional consé quences on the ecosystems at different scales of time and space, would help going towards a more sustainable management of the environment. K e y w o r d s: Ecotoxicological m odels, ecological m odels, risk assessm ent, environm ent, ecotoxicity, m ulti-stressors, E u ro p ea n rég u latio n Review of models for ERA of plant protection products

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Large monitoring datasets reveal high probabilities for intermittent occurrences of pesticides in European running waters

Herrmann,

Bub,

Wolfram

et al. 2023

Environ Sci Eur

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Many studies have investigated short-term peak concentrations of pesticides in surface waters resulting from agricultural uses. However, we lack information to what extent pesticides reoccur over medium (> 4 days) and longer time periods (> 10 days). We use here large-scale pesticide monitoring data from across Europe (~ 15 mil. measurements, i.e., quantified concentrations in water at > 17,000 sites for 474 pesticide compounds) to evaluate the degree to which pesticides were not only detected once, but in sequences of a compound repeatedly quantified in the same area (0.015 km2) within 4–30 days. Reoccurrence was observed at ~ 18% of sites for > 76% of compounds, ~ 40% of which not a priori considered to chronically expose aquatic ecosystems. We calculated a probability of reoccurrence (POR) over medium-term (4–7 days) and long-term (8–30 days) time periods for ~ 360 pesticides. Relative PORs (ratio between long-term and medium-term POR) revealed three occurrence patterns: ephemeral, intermittent and permanent. While fungicides dominated intermittently occurring substances, aligning with application strategies and physico-chemical properties, neonicotinoids and legacy pesticides were among substances permanently occurring. The results of this study shed new light on previously underestimated longer-term occurrence of many pesticides in aquatic environments (35% of investigated substances occurring intermittently or permanently were previously not considered to pollute the aquatic environment chronically), entailing new challenges for chronic risk assessments and the evaluation of pesticide effects on aquatic biodiversity.

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Time‐Variable Exposure Experiments in Conjunction with Higher Tier Population and Effect Modeling to Assess the Risk of Chlorotoluron to Green Algae

Cited by 3 publications

References 42 publications

A Framework for Algae Modeling in Regulatory Risk Assessment

A Framework for Algae Modeling in Regulatory Risk Assessment

A critical review of effect modeling for ecological risk assessment of plant protection products

Large monitoring datasets reveal high probabilities for intermittent occurrences of pesticides in European running waters

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