Are clonal traits and their response to defoliation good predictors of grazing resistance?
Bibliographic record
Abstract
Grazing resistance in plants, which can be defined as the ability to grow and reproduce under grazed conditions, is either associated to defoliation avoidance or tolerance. Clonal traits are often neglected when studying functional responses to grazing, despite frequent occurrence in grassland vegetation. We investigated whether clonal traits and response to defoliation were associated to increased grazing resistance. First, grazing resistance was estimated for eight clonal species using abundance patterns in a long-term field study. We then analysed its correlation with traits in undisturbed conditions and responses to defoliation in a garden experiment. A few traits were correlated to grazing resistance, though only one was a clonal trait (belowground clonal biomass). Grazing resistance was negatively correlated to shoot height and belowground clonal biomass and positively correlated to inflorescence biomass, suggesting that tall rhizomatous species investing little in sexual reproduction were at a disadvantage under grazed conditions. Both shoot height and belowground clonal biomass were negatively affected by defoliation but their decrease was significantly less for species that expressed the greatest grazing resistance in the field. Our findings show that incorporating clonal traits slightly improved predictions about field grazing resistance in the eight investigated species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".