Insecticide alters the evolution of glyphosate resistance in Ipomoea purpurea
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Abstract
The evolution of plant resistance naturally occurs in complex, multifaceted environments that consist of multiple simultaneous stressors. Understanding how shifting environmental contexts may shape resistance evolution requires empirical studies that consider the combined effects of interacting stressors on fitness and selection. Here, we examined how exposure to an insecticide impacts the evolution of resistance to the herbicide glyphosate in Ipomoea purpurea (common morning glory). Through a factorial field experiment, we manipulated glyphosate and an insecticide to estimate selection on glyphosate and herbivory resistance. We found that glyphosate acted as the primary agent of selection, favoring higher levels of glyphosate resistance. In the presence of glyphosate alone, positive correlational selection favored a combination of higher glyphosate and herbivory resistance, supporting prior work that suggested these traits may be linked. Importantly, insecticide exposure modified both glyphosate resistance and the strength of selection acting upon the trait by increasing resistance and weakening selection. Together, our results indicate that the evolution of herbicide resistance is context-dependent and that secondary stressors like insecticide can alter the evolutionary trajectories of plant defense.
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We also identified a fitness peak for high levels of both glyphosate and herbivory resistance (i.e., correlational selection: γ = 0.06, F1 = 5.10, p = 0.030; Figure 4; Table S6),
It is exciting to see a non-linear relationship (epistasis) between these two environmental stressors. To help with interpreting this figure, I suggest that the figure 4 legend include the analysis being done a bit further: explaining what it means for a number to be more or less negative, naming the type of analysis in the first sentence, as done for figure 5, and explaining the meaning of the axis values.
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There was evidence for potential positive selection for glyphosate resistance
I noticed that for some scatter plots there is a clear correlation shown with a solid line (a), and for others there is no clear correlation and no linear regression shown in the figure (all herbivory resistance scatters, as well as (b). I think it would make sense to follow suit with (c) and (d) and not show dashed 'potential' selection when the p-values do not support a correlation, and the scatter plots don't have a visible correlation.
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Figure 2.
Do shriveled and yellow leaves get counted when randomly sampling leaves for herbivory damage? I'm assuming these leaves are not counted, and this is what is meant by in the methods 'excluded ambiguous damage'.
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We found that spinosad application significantly reduced herbivory (untreated: 0.53%, treated: 0.15%; F1 = 174.06, p < 0.001; Figure 2a, Table S1).
I am struggling with the Y-axis '% herbivory per leaf'. Firstly, I am confused about the range. It seems to go from around -2% to 3% damage. However, in the methods, damage values are explained as being the percentage of the leaf surface damaged by herbivory, averaged across four leaves). How can there be negative herbivory damage? Also, perhaps the Y axis title should be something like '% leaf area damaged'
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In line with our previous work, we elected to be conservative with our herbivory damage estimates and excluded ambiguous damage that could be attributed to glyphosate from our estimates (Zhang & Baucom, 2024).
I'm curious what leaf damage due to glyphosate versus leaf damage do to herbivores looks like. It would be nice to see what each of these looks like in a figure, maybe as a supplement. For both, leaf damage is used as an important measure of the effects of stressors on the health/fitness of the plant. This section would benefit from a citation to point to the previous work referenced here that shows this software can exclude one damage from the other.
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