Is It Cold Enough? Effects of Artificial and Natural Chilling on Budbreak and Frost Hardiness in <scp> <i>Acer saccharum</i> </scp> (Marsh.)
Bibliographic record
Abstract
ABSTRACT A crucial part of the phenological cycle in temperate and boreal trees is the exposure to chilling temperatures releasing endodormancy, which allows the trees to react to external signals and resume growth in spring. We compared the effect of artificial and natural chilling on endodormancy break and frost hardiness of sugar maple ( Acer saccharum ) seedlings. Samples were either placed in growing chambers under artificial chilling conditions (4°C) or outdoors (natural temperatures, including < 0°C) in Chicoutimi, Canada. During dormancy, we performed regular transfers to forcing conditions, quantified frost hardiness (LT 50 ) at the time of transfer and observed the time to budbreak (TBB). We measured chilling accumulation with classic models considering only temperatures above 0°C (Chilling Hours, Utah Model, and Dynamic Model) and with a modified model accounting for all temperatures between −10°C and 7.2°C. Samples in artificial chilling showed earlier deacclimation and initiated budbreak in late April, indicating that 4°C can both fulfill the chilling requirement and initiate ontogenetic development. Samples under natural chilling showed later deacclimation, correlating with a longer TBB. Endodormancy break point was only identified in artificial conditions, after 2715 to 3075 h at 4°C. The chilling model accounting for freezing temperatures outperformed classic chilling models. Seedling provenance did not have a significant effect. Our results indicate that including freezing temperatures can improve chilling calculations in cold climates or boreal species, where temperatures remain below 0°C during most of the winter. Moreover, measuring frost hardiness during chilling‐forcing experiments can clarify how acclimation and deacclimation influence dormancy dynamics.
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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".