Physiological responses of <i>Abies faxoniana</i> seedlings to different non-growing-season temperatures as revealed by reciprocal transplantations at two contrasting altitudes
Bibliographic record
Abstract
Detailed information on plants’ responses to varying temperature conditions will be useful when assessing the potential effects of climate change. We conducted reciprocal transplantations in Abies faxoniana Rehd. et Wils. to detect responses of seedlings to different winter (non-growing-season) temperatures in the Wanglang National Nature Reserve, China. Winter temperature variation might alter nitrogen allocation between 1-year-old leaves and branchlets. In leaves, coupling acclimation between photosynthesis potential (evident in pigment content and composition and carbon isotope composition (δ13C)) and adversity tolerance (detectable in peroxidase activity, malondialdehyde content, and nonstructural carbohydrate composition) to winter temperature variation was documented, whereas in branchlets, warming winter did not result in a δ13C-discriminative respiration process at tissue level. Although the experiment included only a short winter period, warming winter was found to pose a negative influence (decreased storage and increased leaf thickness) on A. faxoniana seedlings of subalpine forest understory. As both genetic adaptation and phenotypic plasticity could be responsible for such physiological variation, a detailed altitudinal investigation and a long-term experiment on A. faxoniana seedlings are needed to properly assess their responses to climate change.
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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 | 0.001 |
| 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".