Beneficial effects of solar <scp>UV</scp>‐B radiation on soybean yield mediated by reduced insect herbivory under field conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ultraviolet-B radiation (UV-B: 280-315 nm) has damaging effects on cellular components and macromolecules. In plants, natural levels of UV-B can reduce leaf area expansion and growth, which can lead to reduced productivity and yield. UV-B can also have important effects on herbivorous insects. Owing to the successful implementation of the Montreal Protocol, current models predict that clear-sky levels of UV-B radiation will decline during this century in response to ozone recovery. However, because of climate change and changes in land use practices, future trends in UV doses are difficult to predict. In the experiments reported here, we used an exclusion approach to study the effects of solar UV-B radiation on soybean crops, which are extensively grown in many areas of the world that may be affected by future variations in UV-B radiation. In a first experiment, performed under normal management practices (which included chemical pest control), we found that natural levels of UV-B radiation reduced soybean yield. In a second experiment, where no pesticides were applied, we found that solar UV-B significantly reduced insect herbivory and, surprisingly, caused a concomitant increase in crop yield. Our data support the idea that UV-B effects on agroecosystems are the result of complex interactions involving multiple trophic levels. A better understanding of the mechanisms that mediate the anti-herbivore effect of UV-B radiation may be used to design crop varieties with improved adaptation to the cropping systems that are likely to prevail in the coming decades in response to agricultural intensification.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it