Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Zeitschriften |
| DOI | 10.1038/s41598-019-51645-4 |
Lizenz  |
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| Titel (primär) | Predicting low-concentration effects of pesticides |
| Autor | Liess, M.; Henz, S.; Knillmann, S. |
| Quelle | Scientific Reports |
| Erscheinungsjahr | 2019 |
| Department | OEKOTOX |
| Band/Volume | 9 |
| Seite von | art. 15248 |
| Sprache | englisch |
| Supplements | https://static-content.springer.com/esm/art%3A10.1038%2Fs41598-019-51645-4/MediaObjects/41598_2019_51645_MOESM1_ESM.pdf https://static-content.springer.com/esm/art%3A10.1038%2Fs41598-019-51645-4/MediaObjects/41598_2019_51645_MOESM2_ESM.txt |
| Abstract | We present a model to identify the effects of low toxicant concentrations. Due to inadequate models, such effects have so far often been misinterpreted as random variability. Instead, a tri-phasic relationship describes the effects of a toxicant when a broad range of concentrations is assessed: i) at high concentrations where substantial mortality occurs (LC50), we confirmed the traditional sigmoidal response curve (ii) at low concentrations about 10 times below the LC50, we identified higher survival than previously modelled, and (iii) at ultra-low concentrations starting at around 100 times below the LC50, higher mortality than previously modelled. This suggests that individuals benefit from low toxicant stress. Accordingly, we postulate that in the absence of external toxicant stress individuals are affected by an internal “System Stress” (SyS) and that SyS is reduced with increasing strength of toxicant stress. We show that the observed tri-phasic concentration-effect relationship can be modelled on the basis of this approach. Here we revealed that toxicant-related effects (LC5) occurred at remarkably low concentrations, 3 to 4 orders of magnitude below those concentrations inducing strong effects (LC50). Thus, the ECx-SyS model presented allows us to attribute ultra-low toxicant concentrations to their effects on individuals. This information will contribute to performing a more realistic environmental and human risk assessment. |
| dauerhafte UFZ-Verlinkung | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=22563 |
| Liess, M., Henz, S., Knillmann, S. (2019): Predicting low-concentration effects of pesticides Sci. Rep. 9 , art. 15248 10.1038/s41598-019-51645-4 |
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