Trade‐offs between the shade‐avoidance response and plant resistance to herbivores? Tests with mutant <i> Cucumis sativus</i>
Bibliographic record
Abstract
Summary Plants exhibit adaptations to many stresses, including light competition and herbivory. The expression of these traits may interact negatively, potentially instigating a trade‐off. We employed a combination of genetically altered Cucumis sativus varieties and phenotypic manipulations to test for trade‐offs in field experiments. The different genetic lines of C. sativus were altered in their phytochrome‐mediated shade responses and the production of terpenoid defence compounds. Cucumber plants constitutively expressing the shade‐avoidance response had 93% more herbivory by specialist beetles compared with wild types. The long‐hypocotyl mutants also produced leaves with fewer trichomes, greater toughness and a higher carbon to nitrogen ratio (C : N) than wild types. Plants lacking defensive cucurbitacins had 23% longer internodes than the cucurbitacin‐producing line. We then manipulated the plant phenotype by artificially imposing neighbours’ shade on plants with and without cucurbitacins. As expected, plants responded to shade by growing longer hypocotyls and first internodes, but few trade‐offs were found between plant line and shade treatment and, although herbivory levels were very low, there was a trend towards reduced damage on shaded plants. The use of genetically altered plant lines provided strong evidence for the trade‐off hypothesis, while phenotypic manipulations did not support the hypothesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".