Biomass, carbohydrate, and leakage conductance in buds of six ornamental tree species subjected to a "false spring" in Northeast China
Bibliographic record
Abstract
Information is highly scarce about the possible effect of a late spring frost on physiological response of buds in ornamental trees. In this study, spring temperature of Changchun at Northeast China was recorded to identify the characteristics of a false spring by detecting extraordinary warming and sudden freeze in early April of 2017. Buds of six local ornamental tree species were investigated for their dynamics in biomass, non-structural carbohydrates, frost resistance on days of 7, 14, 21, and 28 April 2017. According to a comparison with spring temperature records historically from 2007 to 2016, a false spring was determined. Black pine (Pinus tabuliformis var. mukdensis) had greater bud biomass than apricot (Prunus sibirica L.). Peach (Prunus persica L. var. persica f. rubro-plena Schneid.) reserved greater non-structural carbohydrate content in post-chilling buds than black pine, and apricot and willow (Salix babylonica L.) had greater soluble sugars and starch contents in buds, respectively. Cumulative number of days with temperature below 12°C had a negative relationship with relative conductance in sorbus (Sorbus pohuashanensis [Hance] Hedl.). Chokecherry (Padus virginiana 'Canada Red') had greatest bud starch content on 21 April. Overall, a late spring frost imposed interruption on carbohydrate metabolism rather than direct damage on buds of ornamental trees before late April. Advanced warming induced more pronounced negative impact of a false spring than the sudden decline of minimum temperature.
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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) | 0.000 | 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 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".