Interspecific competition and tolerance to defoliation in four grassland species
Bibliographic record
Abstract
Herbivory and competition are known to influence plant performance. Recent investigations showed that tolerance is an important strategy for plant survival under herbivory, but few have examined its interaction with plant competition. We evaluated in a greenhouse experiment if plant tolerance to defoliation is related to species presence in a grazed habitat and how plant tolerance to herbivory changes in a competitive environment. Regrowth capacity of four grassland species, Trifolium repens L., Rumex acetosella L., Vicia sativa L. subsp. nigra (L.) Ehrh., and Senecio jacobaea L., was evaluated as the capacity to compensate for 75% of aboveground biomass removed. Target plants were also grown in competition with Festuca rubra L. subsp. rubra, and different clipping treatments were applied. Plant biomass (above- and below-ground) was measured after 5 months. Rumex acetosella, T. repens, and S. jacobaea were able to compensate fully when grown alone. In competition, only R. acetosella was still able to regrow. In no case did clipping the competitor improve target plant performance (i.e., no beneficial effect from competitor release). These results highlight the importance of considering plant competition when studying plant responses to herbivory.Key words: herbivory, regrowth, competitor release, biomass compensation.
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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 | 0.001 | 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".