Chilling and forcing proceed in parallel to regulate spring leaf unfolding in temperate trees
Bibliographic record
Abstract
Abstract Aim Temperature is the main driver of growth reactivation in plants of extratropical regions. Accumulations of chilling and forcing units during dormancy co‐regulate spring phenology. Here, we aimed to answer whether chilling and forcing proceed in parallel or sequentially to regulate spring phenology in temperate trees. Location Europe. Time Period 1951–2016. Major Taxa Studied Nine temperate woody species. Methods Using long‐term and large‐scale records of in situ leaf unfolding dates of temperate tree species at more than 2300 sites, we analysed the rolling partial correlations between leaf unfolding dates and chilling and forcing in winter and spring using a weekly smoothing window. Through process‐based modelling, we further identified the start of forcing accumulation and the end of chilling accumulation using the Unified model and compared the model efficiency of the Parallel and the Sequential models. Results We observed negative responses of leaf unfolding dates to accumulations of both chilling and forcing units for most of winter and spring across successional types of species (early‐ and late‐successional taxa), elevations and periods. Using the Unified model, we also found overlapping windows for chilling and forcing accumulations. Moreover, the Parallel model performed better than the Sequential model. These findings suggested that chilling and forcing requirements may be fulfilled simultaneously in temperate trees. Main Conclusions Our study not only provides a guideline for identifying the effective periods of chilling and forcing, but also a general and robust perspective that accumulations of chilling and forcing act in parallel to regulate spring leaf unfolding in temperate trees, promoting more precise and reasonable predictions of temperature‐driven phenological shifts under future 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".