Induced twining in Convolvulaceae climbing plants in response to leaf damage
Bibliographic record
Abstract
Plant responses to herbivory include slow changes in growth patterns and biomass distribution. A recent study, however, showed that a convolvulaceous vine began twining sooner around a stake after 25% of the plant was defoliated (damaged). We evaluated whether this induced response is widespread within the Convolvulaceae, and made preliminary studies of its underlying mechanisms. Leaf damage was applied to seven twining vine species from the genera Convolvulus, Calystegia, and Ipomoea. We compared the twining rate (proportion of plants successfully climbing at a given time), growth rate, and twining geometry in the control and in damaged plants. We further evaluated the consequences of jasmonic acid application on the twining rate of Ipomoea purpurea (L.) Roth. Five out of the seven species tested showed an enhanced twining rate after leaf damage. Growth rate did not differ between damaged and undamaged plants in any species. The angle of ascent of the twining stem was lower in damaged plants during the first gyres. Jasmonic acid increased twining rate in I. purpurea, as did leaf damage. The induced twining was not due to increased growth, but to changes in the climbing process, and further mechanistic approaches should consider the jasmonate pathway. Induced twining may be common in the Convolvulaceae, and its occurrence in other families should be tested.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".