Intraclonal variation in defence substances and palatability: a study on <i>Carex</i> and lemmings
Bibliographic record
Abstract
Clonal sedges consist of integrated ramets at different development stages. Many of these sedges are important food for herbivores, yet differences in herbivore preferences and defence allocation between ramet development stages have not previously been evaluated. In this study we investigated intraclonal ramet variation in level of plant defence and nutrient compounds and intraclonal ramet preferences by lemmings ( Lemmus trimucronatus ) in field samples of a rhizomatous sedge ( Carex stans ). Plant defence was measured as the level of proteinase inhibitor activity (PIA) and the ratio of PIA to soluble plant proteins (SPP), whereas plant nutrients were measured as the level of soluble plant sugars (SPS) and SPP. Flowering ramets generally had a higher content of defence compared to vegetative ramets, which is consistent with the optimal defence theory predicting that defence compounds are allocated to the ramet stage of the highest fitness value. Compared to vegetative ramets, the flowering ramets had a lower content of SPP and a higher content of SPS. The lemmings showed preference differences between the ramet development stages, and to a large extent the ramet content of defence compounds and nutrient compounds covaried with these preferences in the predicted way. This study shows that defence allocation between ramet development stages of the clonal sedge Carex conforms to predictions of the optimal defence theory.
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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".