Indirect effects of herbivory on plant–pollinator interactions in invasive <i>Lythrum salicaria</i>
Bibliographic record
Abstract
PREMISE OF THE STUDY: Herbivory can affect a plant's fitness in a variety of ways, including modifying the biotic interactions of the plant. In particular, when herbivory influences floral display, we hypothesize that pollinator visitation will be altered accordingly. Here we studied the indirect effects of feeding by two beetles, Neogalerucella calmariensis and N. pusilla, released as a biological control, on plant-pollinator interactions and fitness in the invasive plant, purple loosestrife (Lythrum salicaria). METHODS: Two herbivory treatments (ambient and simulated) were applied to plants in a naturally occurring population of purple loosestrife. During flowering, traits of plants in the treatment and control groups were recorded. Data on pollinator visitation behavior was then collected after intense larval herbivory had ended. KEY RESULTS: Plants exposed to herbivory treatments produced more flowers and inflorescences but flowered significantly later than those in the control group. Moreover, we found a significant, positive association of herbivory with the number of flowers probed by bumblebees and with the number of times a foraging pollinator moved among inflorescences on a single plant. No differences in female fitness (fruit or seed production) were detected. CONCLUSIONS: We conclude that herbivore-mediated differences in floral display traits impacted pollinator visitation behavior. However, as we discuss, differences in pollinator visitation did not translate into detectable differences in female reproductive success. We postulate that herbivory could influence other unmeasured aspects of fitness, such as seed quality or the number of seeds sired.
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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".