Chilling and forcing temperatures interact to predict the onset of wood formation in Northern Hemisphere conifers
Why this work is in the frame
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Bibliographic record
Abstract
The phenology of wood formation is a critical process to consider for predicting how trees from the temperate and boreal zones may react to climate change. Compared to leaf phenology, however, the determinism of wood phenology is still poorly known. Here, we compared for the first time three alternative ecophysiological model classes (threshold models, heat-sum models and chilling-influenced heat-sum models) and an empirical model in their ability to predict the starting date of xylem cell enlargement in spring, for four major Northern Hemisphere conifers (Larix decidua, Pinus sylvestris, Picea abies and Picea mariana). We fitted models with Bayesian inference to wood phenological data collected for 220 site-years over Europe and Canada. The chilling-influenced heat-sum model received most support for all the four studied species, predicting validation data with a 7.7-day error, which is within one day of the observed data resolution. We conclude that both chilling and forcing temperatures determine the onset of wood formation in Northern Hemisphere conifers. Importantly, the chilling-influenced heat-sum model showed virtually no spatial bias whichever the species, despite the large environmental gradients considered. This suggests that the spring onset of wood formation is far less affected by local adaptation than by environmentally driven plasticity. In a context of climate change, we therefore expect rising winter-spring temperature to exert ambivalent effects on the spring onset of wood formation, tending to hasten it through the accumulation of forcing temperature, but imposing a higher forcing temperature requirement through the lower accumulation of chilling.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it