Modelling survival under chemical stress
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Modelling survival under chemical stress

A comprehensive guide to the GUTS framework

About the Book

Stressors, such as toxicants, can cause mortality among organisms. Interestingly, not all individuals will die at the same time in the same exposure treatment, and the number of deaths will change with exposure time. The pattern of mortality will also depend on the exposure profile (e.g., constant versus pulsed exposure), and can be modified by the addition of other stresses (e.g., mixture toxicity). Making sense of these complex issues requires mechanism-based models, known as toxicokinetic-toxicodynamic (TKTD) models. For mortality, almost all published TKTD models can now be viewed as members of an over-arching framework, that we have christened GUTS: the General Unified Threshold model of Survival. GUTS has been published in the scientific literature in 2011, but a publication is obviously not the place to provide a detailed description of the model or to provide guidance on how to apply the model in practical situations. As the GUTS framework is now gaining broader interest in the scientific, regulatory and industry communities, it is time for a more in-depth treatise.

This book presents the background and history of GUTS, the concepts applied and the underlying assumptions, as well as the mathematical details (in a separate chapter). Furthermore, three worked out case studies are provided, demonstrating how the model can be used in practice. Further chapters deal with potential applications in a regulatory context, ring testing of various software implementations, and more (see the table of contents). We expect to provide regular updates of the book to include novel developments in this field (and to correct errors).

The supporting web page for this book is at There, you can also find a log file with version information and known errors. The first version of this book was released on 18 January 2018.

About the Authors

Tjalling Jager
Tjalling Jager

Mechanistic modelling is still an under-utilised tool in ecotoxicology and stress ecology. It is my passion to promote these models through (applied) scientific projects, providing software solutions, teaching in courses, presentations at conferences, and through writing e-books. The models that I specialise in are so-called toxicokinetic-toxicodynamic (TKTD) models; in particular, models for survival (the GUTS framework) and sublethal effects (based on Dynamic Energy Budget - DEB - theory). These models are based on a rigorous simplification of biological complexity, and have the power to explain (and predict) life-history traits of organisms (e.g., growth, reproduction and survival) over time. Especially when considering exposure to stressors, such dynamic models are indispensable to make sense of the data.

I hold an MSc and PhD in Biology, and have been a professional modeller since 1992, working almost exclusively on DEB- and GUTS-based TKTD modelling since 2002. Currently, I run my own private company 'DEBtox Research', offering my expertise to clients from industry, contract laboratories, and universities.

More information about Tjalling at DEBtox Research

More information about DEB(tox) and GUTS models

Roman Ashauer
Roman Ashauer

What makes man-made chemicals dangerous to the environment? Which species are most vulnerable? How can we improve risk assessment of chemicals? To answer these questions I combine field and laboratory experiments with theory and computation. The models that I specialise in are so-called toxicokinetic-toxicodynamic models and I have been working in this field since 2004.

I hold a PhD in Environmental Science and until 2018 I worked as Associate Professor in the Environment Department at the University of York (UK) as well as Director of Toxicodynamics Ltd. Since 2019 I work as Eco-modelling lead at Syngenta Crop Protection AG, Switzerland. You can find out more at

Table of Contents


  1. 1. Introduction
  2. 2. Description of GUTS
  3. 3. Mathematical treatment
  4. 4. Case study: dieldrin in guppies
  5. 5. Case study: propiconazole in amphipods
  6. 6. Case study: flupyradifurone in midges
  7. 7. Use cases
  8. 8. Model evaluation
  9. 9. Outlook



Appendix A: Ring test

Appendix B: Model extensions

Appendix C: Typical identifiability problems and limit cases

Appendix D: Sampling from parameter space

Appendix E: Relationship to Haber's rule

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