Influence of nutrient availability on the mechanisms of tolerance to herbivory in an annual grass, <i>Avena barbata</i> (Poaceae)
Bibliographic record
Abstract
Tolerance, or the capacity of a genotype to survive and reproduce following herbivore damage, varies widely across the plant kingdom. One proximate cause of this variation is resource availability, which can influence tolerance through mechanisms such as growth rate and photosynthesis. We examined the effect of high and low soil nutrient levels on the relationship between tolerance and two of its underlying mechanisms, biomass regrowth and photosynthetic upregulation, among genotypes of the Mediterranean annual grass Avena barbata. Although defoliated plants did not reach the same biomass as controls, biomass regrowth was higher at high nutrients. However, increased seed abortion at high nutrients caused tolerance to be the same in both nutrient treatments. Increased seed abortion also uncoupled biomass regrowth from tolerance at high nutrients. We found no evidence for photosynthetic upregulation in defoliated compared to control plants in either nutrient treatment. However, tolerance was positively correlated with predefoliation photosynthetic efficiency at high nutrients. Thus, constitutive photosynthetic efficiency may be a better predictor of tolerance than photosynthetic responses following herbivory in A. barbata. More generally, our results highlight the possibility that the mechanisms of tolerance can differ across resource environments even if tolerance is the same.
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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 | 0.001 | 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 | 0.001 |
| 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".