Abstract:To make more realistic predictions about the current and future effects of pesticides, we need to better understand physiological mechanisms associated with the widespread higher toxicity of many pesticides under increasing mean temperatures and daily temperature fluctuations (DTFs). One overlooked, yet insightful, mechanism are bioenergetic responses as these provide information about the balance between energy gains and costs. Therefore, we studied how the bioenergetic responses to the insecticide chlorpyrif… Show more
“…Assays were done on one pooled set of five larvae per jar, and the jar means of the three to four technical replicates were used in the statistical analyses (exact sample sizes per treatment combination are given in Figure A,B and SI Figure S4 in Appendix S6). All assays were based on spectrophotometry as described in Delnat et al and Verheyen and Stoks . The detailed assay protocols can be found in SI Appendix S4.…”
The exposure order may strongly affect
the impact of stressors,
yet is largely ignored for the frequently occurring combinations of
toxicants with natural stressors. We tested how exposure order shaped
the interactive effects of serial exposure to the pesticide chlorpyrifos
and to a heat spike in the larvae of the mosquito Culex pipiens. Notably, the chlorpyrifos-induced mortality was much more magnified
by the heat spike and a synergism was already detected at the low
concentration when exposure to chlorpyrifos followed the heat spike.
This suggests that the preceding heat spike weakened the larvae as
reflected in their lower net energy budget, moreover the chlorpyrifos-induced
inhibition of its target enzyme (acetylcholinesterase) was only magnified
by the heat spike when it was the first stressor. Also the chlorpyrifos-induced
reduction in heat tolerance was stronger when the pesticide pulse
followed the heat spike, and was buffered by the heat spike when this
was the second stressor. Our results provide the first evidence that
the exposure order can strongly change the magnifying effect of an
important climate change factor on the toxicity of a pesticide. This
highlights the importance of exposure order in ecological risk assessment
of toxicants under realistic combinations with natural stressors.
“…Assays were done on one pooled set of five larvae per jar, and the jar means of the three to four technical replicates were used in the statistical analyses (exact sample sizes per treatment combination are given in Figure A,B and SI Figure S4 in Appendix S6). All assays were based on spectrophotometry as described in Delnat et al and Verheyen and Stoks . The detailed assay protocols can be found in SI Appendix S4.…”
The exposure order may strongly affect
the impact of stressors,
yet is largely ignored for the frequently occurring combinations of
toxicants with natural stressors. We tested how exposure order shaped
the interactive effects of serial exposure to the pesticide chlorpyrifos
and to a heat spike in the larvae of the mosquito Culex pipiens. Notably, the chlorpyrifos-induced mortality was much more magnified
by the heat spike and a synergism was already detected at the low
concentration when exposure to chlorpyrifos followed the heat spike.
This suggests that the preceding heat spike weakened the larvae as
reflected in their lower net energy budget, moreover the chlorpyrifos-induced
inhibition of its target enzyme (acetylcholinesterase) was only magnified
by the heat spike when it was the first stressor. Also the chlorpyrifos-induced
reduction in heat tolerance was stronger when the pesticide pulse
followed the heat spike, and was buffered by the heat spike when this
was the second stressor. Our results provide the first evidence that
the exposure order can strongly change the magnifying effect of an
important climate change factor on the toxicity of a pesticide. This
highlights the importance of exposure order in ecological risk assessment
of toxicants under realistic combinations with natural stressors.
“…The cellular energy allocation (CEA) measures a net cellular energy budget of the organisms at a cellular level of biological organization, by quantifying the available energy reserves and energy consumption in tissues (Erk et al, 2011). Presently, the CEA has been widely used as a biomarker reflected the metabolic processes of an organism under stressful conditions (Verheyen and Stoks, 2020;Gandar et al, 2017;Kühnhold et al, 2017). In terms of the available energy reserves, only exposure to OW led to an increase in total lipid content and a decrease in glycogen content in the muscles of T. niloticus.…”
Section: Effects Of Oa And/or Ow On Energy Metabolism Of T Niloticusmentioning
“…With such a bio-energetic approach, the higher toxicity of many pesticides under increasing mean temperatures and daily temperature fluctuations could be associated with a reduced cellular energy allocation [40]. Nevertheless, the question remains as to how these sublethal responses can be integrated to predict individual mortality in natural conditions, the most integral-and hence pivotal-endpoint when assessing the fitness of individuals and higher levels of biological organization.…”
Background
Toxicants often occur simultaneously. Some combinations show synergistic combined effects that go far beyond what is predicted with current effect models. Up until now, only the combined additive effects of similar acting chemicals have been assessed accurately, whereas the combined effects of dissimilar acting chemicals have been greatly underestimated in many cases.
Results
Here, we use the individual tri-phasic concentration–response relationship of two toxicants with different modes of action to model their combined synergistic effect on Daphnia magna. The novel stress addition approach (SA) predicted the combined effects (LC50) of different esfenvalerate and prochloraz combinations with an uncertainty factor of 2.8 at most, while the traditional effect addition (EA) and concentration addition (CA) approaches underestimated the combined effect by a factor of up to 150 and 660, respectively. Data of the single substance concentration–response relationships and on their combined effects enable to determine the degree of synergism. For the evaluation of the combined toxicant effect, we provide the approach as R package and as Indicate model (http://www.systemecology.eu/indicate/).
Conclusion
Adding stressors arithmetically, considering non-monotonic cause–effect relationships, is a decisive component in predicting the combined effects of multiple stressors within test systems. However, the extent of the synergistic effects that multiple stressors exert on populations within the ecosystem context is still highly controversial. Various processes are relevant at the ecosystem level, which are not considered in laboratory studies. However, the present work serves as a building block for understanding the effects of multiple stressors in the field.
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