Modelling survival: exposure pattern, species sensitivity and uncertainty.

Roman Ashauer,Andreas Focks,Virginie Ducrot,Sören Vogel,Nina Cedergreen,Elke I Zimmer,Ralf B Schäfer,Paul J Van Den Brink,Starrlight Augustine,Faten Gabsi,Tjalling Jager,Nynke I Kramer,André Gergs,Carlo Albert,Karin Veltman,Stefan Reichenberger,Sandrine Charles,Anna Nyman ,Benoît Goussen ,Véronique Poulsen ,Thomas G Preuß

doi:10.1038/srep29178

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.

Highlights

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetictoxicodynamic models and estimates survival with explicitly defined assumptions
TK-TD models quantify the time-course of internal concentrations of chemicals, which is defined by uptake and elimination rates of chemicals, as well as the processes leading to toxic effects, which include damage accrual and recovery, as well as the death mechanisms explained below
How well do the implementations General Unified Threshold model of Survival (GUTS)-SD and GUTS -IT, calibrated on data from short-term toxicity experiments and constant exposure forecast effects of longer-term pulsed exposures? The likelihood values indicate a better fit to the calibration data for GUTS- SD (Table S14 in SI), but the majority of survival predictions are in better agreement with the data for GUTS-IT (Table S15 in SI)

Summary

Introduction

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetictoxicodynamic models and estimates survival with explicitly defined assumptions. The General Unified Threshold model of Survival[3] (GUTS) provides a theoretical framework for deriving consistent model equations for different choices and assumptions about stressor quantification, compensatory processes and the nature of the death process. Survival datasets used in ecotoxicology generally do not contain enough information to estimate all parameters of the GUTS proper model with sufficient precision. This is because a large number of individuals is required to provide strong information on probabilistic events and because the choices of concentrations and exposure durations matter[23]. It is not clear which experimental designs can identify both death mechanisms and to what degree of precision

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