Spring temperatures affect senescence and N uptake in autumn and N storage for winter in Rhynchospora alba (Cyperaceae)
Bibliographic record
Abstract
Environmental and physiological factors underlying variation in timing of autumn senescence are not well known. We investigated how the time of the onset of the growth in spring affects senescence and its functional consequences for nitrogen (N) uptake in autumn and storage of N for the winter, in a species that each year develops its bulbils for storage and overwintering anew. Rhynchospora alba was grown outdoors with two treatments, identical except for a 3 week difference in the start of growth in May. Leaf and root growth and senescence, and N uptake were recorded from August to November. By August, late-starting plants had caught up in size and total N content, but had smaller bulbils. They had a higher δ 13C, indicating a higher stomatal conductance during growth. Leaf and root senescence were delayed, extending 15N tracer uptake by 4 weeks. Nevertheless, after senescence, plants with an early start had 55% more N in their overwintering bulbils, due to earlier and more efficient remobilization. We conclude that timing of senescence in R. alba is a result of an interplay between the status of winter storage and cold temperatures, constrained by a trade-off between prolonged nutrient uptake and efficient remobilization of nutrients.
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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".