Prediction of Daphnid Survival after in Situ Exposure to Complex Mixtures

Baas, Jan; Willems, J.; Jager, Tjalling; Kraak, Michiel H.S.; Vandenbrouck, Tine; Kooijman, S.A.L.M.

doi:10.1021/es901083v

Cited by 16 publications

(16 citation statements)

References 40 publications

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“…The insecticides typically target nerve function, even if the target is not mediated by the same molecular initiating event (e.g., acetyl cholinesterase binding, nicotinic receptor binding, or sodium channel binding). We used this approach before an exceedance of 1 for the NEC mix proved to be an excellent proxy for predicting daphnid survival after exposure to complex mixtures . This general approach is in line with other research with both the concentration addition and independent action models to predict mixture effects for different pesticides , although with some tendency toward moderate synergistic effects in binary mixtures.…”

Section: Discussionsupporting

confidence: 66%

“…The model proved able to make reliable predictions on both survival (if the mixture threshold was below 1) and mortality (if the mixture threshold exceeded 1) of exposed organisms. The more frequently used concentration addition and independent action models could not make reliable predictions on both survival and mortality in this real‐life situation . The problem is that these models are conceptually inappropriate to be used in an approach like this.…”

Section: Methodsmentioning

confidence: 99%

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

Baas

Vijver²,

Rambohul

et al. 2016

Enviro Toxic and Chemistry

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. 2016. Comparison and evaluation of pesticide monitoring programs using a process-based mixture model. Environmental Toxicology and Chemistry, 35 (12). 3113-3123. 10.1002/etc.3492 Contact CEH NORA team at noraceh@ceh.ac.ukThe NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner.This article is protected by copyright. All rights reserved Accepted PreprintThis article is protected by copyright. All rights reserved Abstract: 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. This study is aimed at evaluating the joint effects of the pesticide mixtures detected in monitoring programs, using a process based mixture modelthat was parameterised 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 we 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 hrs. The results show that effects are mostly triggered by a limited nr 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 programmes it remains a challenge to make statements on whether or not the environment is protected. The paper ends with recommendations for a different setup of monitoring programs to improve on this. This article is protected by copyright. All rights reserved

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Section: Discussionsupporting

confidence: 66%

Section: Methodsmentioning

confidence: 99%

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

Baas

Vijver²,

Rambohul

et al. 2016

Enviro Toxic and Chemistry

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“…modeling the effect of binary metal mixtures on survival of the soil arthropod F. candida (Baas et al, 2007) and modeling the effect of a mixture of 14 PAHs on the survival of the fish Pimephales promelas (Baas et al, 2009a). The model was also used to predict the effect of surface waters contaminated with over 90 chemicals on the survival of D. magna (Baas et al, 2009b). In 34 out of 37 cases (92%), daphnid survival was predicted correctly.…”

Section: Mechanistic Mixture Studiesmentioning

confidence: 99%

Tools and perspectives for assessing chemical mixtures and multiple stressors

2013

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The present paper summarizes the most important insights and findings of the EU NoMiracle project with a focus on (1) risk assessment of chemical mixtures, (2) combinations of chemical and natural stressors, and (3) the receptor-oriented approach in cumulative risk assessment. The project aimed at integration of methods for human and ecological risk assessment. A mechanistically based model, considering uptake and toxicity as a processes in time, has demonstrated considerable potential for predicting mixture effects in ecotoxicology, but requires the measurement of toxicity endpoints at different moments in time. Within a novel framework for risk assessment of chemical mixtures, the importance of environmental factors on toxicokinetic processes is highlighted. A new paradigm for applying personal characteristics that determine individual exposure and sensitivity in human risk assessment is suggested. The results are discussed in the light of recent developments in risk assessment of mixtures and multiple stressors.

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“…(8) Risk assessment of mixtures in time is important as different compounds can interact and contribute to mixture toxicity even if they occur days(22) or weeks apart. (15) TKTD models for mixtures of chemicals are available, 15,59 but their relationship to standard models for toxicity of mixtures with simultaneous, constant exposure is not well established. (60) TKTD models for temporal mixtures can explain phenomena such as the sequence effect,(15) which is caused by carry-over toxicity, however the large number of model parameters needed to assess the temporal mixtures of chemicals on a catchment scale are not available yet.…”

Section: Resultsmentioning

confidence: 99%

Environmental Risk Assessment of Fluctuating Diazinon Concentrations in an Urban and Agricultural Catchment Using Toxicokinetic–Toxicodynamic Modeling

Ashauer

Wittmer

Stamm

et al. 2011

Environ. Sci. Technol.

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Temporally resolved environmental risk assessment of fluctuating concentrations of micropollutants is presented. We separated the prediction of toxicity over time from the extrapolation from one to many species and from acute to sublethal effects. A toxicokinetic–toxicodynamic (TKTD) model predicted toxicity caused by fluctuating concentrations of diazinon, measured by time-resolved sampling over 108 days from three locations in a stream network, representing urban, agricultural and mixed land use. We calculated extrapolation factors to quantify variation in toxicity among species and effect types based on available toxicity data, while correcting for different test durations with the TKTD model. Sampling from the distribution of extrapolation factors and prediction of time-resolved toxicity with the TKTD model facilitated subsequent calculation of the risk of undesired toxic events. Approximately one-fifth of aquatic organisms were at risk and fluctuating concentrations were more toxic than their averages. Contribution of urban and agricultural sources of diazinon to the overall risk varied. Thus using fixed concentrations as water quality criteria appears overly simplistic because it ignores the temporal dimension of toxicity. However, the improved prediction of toxicity for fluctuating concentrations may be small compared to uncertainty due to limited diversity of toxicity data to base the extrapolation factors on.

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Prediction of Daphnid Survival after in Situ Exposure to Complex Mixtures

Cited by 16 publications

References 40 publications

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

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

Tools and perspectives for assessing chemical mixtures and multiple stressors

Environmental Risk Assessment of Fluctuating Diazinon Concentrations in an Urban and Agricultural Catchment Using Toxicokinetic–Toxicodynamic Modeling

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