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Predicting the synergy of multiple stress effects
Toxicants and other, non-chemical environmental stressors contribute to the global biodiversity crisis. Examples include the loss of bees and the reduction of aquatic biodiversity. Although non-compliance with regulations might be contributing, the widespread existence of these impacts suggests that...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5017025/ https://www.ncbi.nlm.nih.gov/pubmed/27609131 http://dx.doi.org/10.1038/srep32965 |
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author | Liess, Matthias Foit, Kaarina Knillmann, Saskia Schäfer, Ralf B. Liess, Hans-Dieter |
author_facet | Liess, Matthias Foit, Kaarina Knillmann, Saskia Schäfer, Ralf B. Liess, Hans-Dieter |
author_sort | Liess, Matthias |
collection | PubMed |
description | Toxicants and other, non-chemical environmental stressors contribute to the global biodiversity crisis. Examples include the loss of bees and the reduction of aquatic biodiversity. Although non-compliance with regulations might be contributing, the widespread existence of these impacts suggests that for example the current approach of pesticide risk assessment fails to protect biodiversity when multiple stressors concurrently affect organisms. To quantify such multiple stress effects, we analysed all applicable aquatic studies and found that the presence of environmental stressors increases individual sensitivity to toxicants (pesticides, trace metals) by a factor of up to 100. To predict this dependence, we developed the “Stress Addition Model” (SAM). With the SAM, we assume that each individual has a general stress capacity towards all types of specific stress that should not be exhausted. Experimental stress levels are transferred into general stress levels of the SAM using the stress-related mortality as a common link. These general stress levels of independent stressors are additive, with the sum determining the total stress exerted on a population. With this approach, we provide a tool that quantitatively predicts the highly synergistic direct effects of independent stressor combinations. |
format | Online Article Text |
id | pubmed-5017025 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-50170252016-09-12 Predicting the synergy of multiple stress effects Liess, Matthias Foit, Kaarina Knillmann, Saskia Schäfer, Ralf B. Liess, Hans-Dieter Sci Rep Article Toxicants and other, non-chemical environmental stressors contribute to the global biodiversity crisis. Examples include the loss of bees and the reduction of aquatic biodiversity. Although non-compliance with regulations might be contributing, the widespread existence of these impacts suggests that for example the current approach of pesticide risk assessment fails to protect biodiversity when multiple stressors concurrently affect organisms. To quantify such multiple stress effects, we analysed all applicable aquatic studies and found that the presence of environmental stressors increases individual sensitivity to toxicants (pesticides, trace metals) by a factor of up to 100. To predict this dependence, we developed the “Stress Addition Model” (SAM). With the SAM, we assume that each individual has a general stress capacity towards all types of specific stress that should not be exhausted. Experimental stress levels are transferred into general stress levels of the SAM using the stress-related mortality as a common link. These general stress levels of independent stressors are additive, with the sum determining the total stress exerted on a population. With this approach, we provide a tool that quantitatively predicts the highly synergistic direct effects of independent stressor combinations. Nature Publishing Group 2016-09-09 /pmc/articles/PMC5017025/ /pubmed/27609131 http://dx.doi.org/10.1038/srep32965 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Liess, Matthias Foit, Kaarina Knillmann, Saskia Schäfer, Ralf B. Liess, Hans-Dieter Predicting the synergy of multiple stress effects |
title | Predicting the synergy of multiple stress effects |
title_full | Predicting the synergy of multiple stress effects |
title_fullStr | Predicting the synergy of multiple stress effects |
title_full_unstemmed | Predicting the synergy of multiple stress effects |
title_short | Predicting the synergy of multiple stress effects |
title_sort | predicting the synergy of multiple stress effects |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5017025/ https://www.ncbi.nlm.nih.gov/pubmed/27609131 http://dx.doi.org/10.1038/srep32965 |
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