Effects of the Spatial Pattern of Leaf Damage on Growth and Reproduction: Whole Plants
Bibliographic record
Abstract
Because of differences in their foraging patterns, different herbivores are likely to have different effects on plant fitness. We compared the effects of two contrasting patterns of leaf damage on the growth and reproduction of the wild gourd Cucurbita pepo ssp. texana. Plants were assigned to one of four damage treatments: (1) concentrated (15% damage on every third leaf); (2) dispersed (5% on each leaf); (3) high intensity (15% on each leaf); and (4) control (undamaged). We measured the growth rate of the main vegetative axis of the plants, internode length, the proportions of staminate and pistillate nodes, the proportions of staminate and pistillate buds that reached anthesis, the proportion of pistillate flowers that produced fruit, pollen production and pollen grain size, fruit production, fruit size, number of seeds per fruit, and seed size. Only one trait was significantly affected by the spatial pattern of damage: pollen production per flower increased under the concentrated but not the dispersed damage treatment. Fruit production showed a marginal decrease in the dispersed but not in the concentrated treatment. Very few traits were affected by foliar damage, regardless of the spatial pattern of distribution, suggesting that these plants have a high tolerance to simulated herbivory.
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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".