Exploring the control of diurnal cycles on chilling and forcing accumulation in tree bud dormancy release
Bibliographic record
Abstract
Cold temperatures (known as ‘chilling’) are perceived by tree buds in winter and are responsible for dormancy release after species-specific exposure times, which marks the start of the buds' sensitivity to warmer temperatures (known as ‘forcing’). Temperate trees are also sensitive to changing daylength, but it remains unresolved whether the accumulation of chilling and forcing is related to the diurnal cycle. This study explores whether trees "count" chilling based on night/day cycles rather than purely through temperature accumulation or exposition, and whether forcing temperatures are more effective during daylight.We harvested twigs from four temperate tree species with contrasting chilling and forcing requirements for dormancy release in late November 2024 , i.e. before they would experience significant periods of cold. Twig cuttings were then placed into transparent boxes filled with water and kept in climate chambers at 2°C/4°C (night/day) under three diurnal cycles: 12h/12h, 6h/6h (2 cycles per day), and 4h/4h (3 cycles per day) for one month (short chilling) or two months (long chilling). After these six treatments, all cuttings were transferred to forcing conditions with 12h daylight under two temperature regimes: 10°C/25°C and 15°C/20°C, i.e. with the same mean temperature but warmer or colder temperature during daytime. The timing and success of bud break were visually monitored twice a week.The experiment is ongoing. We hypothesize that chilling accumulation is influenced by diurnal cycles, with faster dormancy release for twigs exposed to shorter diurnal cycles. Additionally, we anticipate that daytime temperatures play a more significant role in forcing accumulation, leading to faster budburst in the 10°C/25°C treatment compared to the 15°C/20°C, especially for species known to be photoperiodic sensitive such as European beech. Our study will provide insights into how trees perceive and respond to temperature in relation to daylight, which is crucial for understanding and predicting phenological responses accurately in the context of 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 | 0.000 |
| 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".