Feeding the enemy: loss of nectar and nectaries to herbivores reduces tepal damage and increases pollinator attraction in <i>Iris bulleyana</i>
Bibliographic record
Abstract
Floral nectar usually functions as a pollinator reward, yet it may also attract herbivores. However, the effects of herbivore consumption of nectar or nectaries on pollination have rarely been tested. We investigated Iris bulleyana , an alpine plant that has showy tepals and abundant nectar, in the Hengduan Mountains of SW China. In this region, flowers are visited mainly by pollen-collecting pollinators and nectarivorous herbivores. We tested the hypothesis that, in I. bulleyana , sacrificing nectar and nectaries to herbivores protects tepals and thus enhances pollinator attraction. We compared rates of pollination and herbivory on different floral tissues in plants with flowers protected from nectar and nectary consumption with rates in unprotected control plants. We found that nectar and nectaries suffered more herbivore damage than did tepals in natural conditions. However, the amount of tepal damage was significantly greater in the flowers with protected nectaries than in the controls; this resulted in significant differences in pollinator visitation rates. These results provide the first evidence that floral nectar and nectaries may be ‘sacrificed’ to herbivores, leading to reduced damage to other floral tissues that are more important for reproduction.
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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".