Modelling survival: exposure pattern, species sensitivity and uncertainty

Research output: Contribution to journalJournal articleResearchpeer-review

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Modelling survival : exposure pattern, species sensitivity and uncertainty. / Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I.; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B.; Van den Brink, Paul J.; Veltman, Karin; Vogel, Sören; Zimmer, Elke I.; Preuss, Thomas G.

In: Scientific Reports, Vol. 6, 29178, 2016.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Ashauer, R, Albert, C, Augustine, S, Cedergreen, N, Charles, S, Ducrot, V, Focks, A, Gabsi, F, Gergs, A, Goussen, B, Jager, T, Kramer, NI, Nyman, A-M, Poulsen, V, Reichenberger, S, Schäfer, RB, Van den Brink, PJ, Veltman, K, Vogel, S, Zimmer, EI & Preuss, TG 2016, 'Modelling survival: exposure pattern, species sensitivity and uncertainty', Scientific Reports, vol. 6, 29178. https://doi.org/10.1038/srep29178

APA

Ashauer, R., Albert, C., Augustine, S., Cedergreen, N., Charles, S., Ducrot, V., Focks, A., Gabsi, F., Gergs, A., Goussen, B., Jager, T., Kramer, N. I., Nyman, A-M., Poulsen, V., Reichenberger, S., Schäfer, R. B., Van den Brink, P. J., Veltman, K., Vogel, S., ... Preuss, T. G. (2016). Modelling survival: exposure pattern, species sensitivity and uncertainty. Scientific Reports, 6, [29178]. https://doi.org/10.1038/srep29178

Vancouver

Ashauer R, Albert C, Augustine S, Cedergreen N, Charles S, Ducrot V et al. Modelling survival: exposure pattern, species sensitivity and uncertainty. Scientific Reports. 2016;6. 29178. https://doi.org/10.1038/srep29178

Author

Ashauer, Roman ; Albert, Carlo ; Augustine, Starrlight ; Cedergreen, Nina ; Charles, Sandrine ; Ducrot, Virginie ; Focks, Andreas ; Gabsi, Faten ; Gergs, André ; Goussen, Benoit ; Jager, Tjalling ; Kramer, Nynke I. ; Nyman, Anna-Maija ; Poulsen, Veronique ; Reichenberger, Stefan ; Schäfer, Ralf B. ; Van den Brink, Paul J. ; Veltman, Karin ; Vogel, Sören ; Zimmer, Elke I. ; Preuss, Thomas G. / Modelling survival : exposure pattern, species sensitivity and uncertainty. In: Scientific Reports. 2016 ; Vol. 6.

Bibtex

@article{3ef0e87bf3764bd0b32b4f677552dd60,
title = "Modelling survival: exposure pattern, species sensitivity and uncertainty",
abstract = "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.",
keywords = "Journal Article",
author = "Roman Ashauer and Carlo Albert and Starrlight Augustine and Nina Cedergreen and Sandrine Charles and Virginie Ducrot and Andreas Focks and Faten Gabsi and Andr{\'e} Gergs and Benoit Goussen and Tjalling Jager and Kramer, {Nynke I.} and Anna-Maija Nyman and Veronique Poulsen and Stefan Reichenberger and Sch{\"a}fer, {Ralf B.} and {Van den Brink}, {Paul J.} and Karin Veltman and S{\"o}ren Vogel and Zimmer, {Elke I.} and Preuss, {Thomas G.}",
year = "2016",
doi = "10.1038/srep29178",
language = "English",
volume = "6",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "nature publishing group",

}

RIS

TY - JOUR

T1 - Modelling survival

T2 - exposure pattern, species sensitivity and uncertainty

AU - Ashauer, Roman

AU - Albert, Carlo

AU - Augustine, Starrlight

AU - Cedergreen, Nina

AU - Charles, Sandrine

AU - Ducrot, Virginie

AU - Focks, Andreas

AU - Gabsi, Faten

AU - Gergs, André

AU - Goussen, Benoit

AU - Jager, Tjalling

AU - Kramer, Nynke I.

AU - Nyman, Anna-Maija

AU - Poulsen, Veronique

AU - Reichenberger, Stefan

AU - Schäfer, Ralf B.

AU - Van den Brink, Paul J.

AU - Veltman, Karin

AU - Vogel, Sören

AU - Zimmer, Elke I.

AU - Preuss, Thomas G.

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - Journal Article

U2 - 10.1038/srep29178

DO - 10.1038/srep29178

M3 - Journal article

C2 - 27381500

VL - 6

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

M1 - 29178

ER -

ID: 169106903