Variation in bud phenology, frost tolerance and non-structural carbohydrates among white spruce seed sources on climate-contrasted test sites: implications for assisted migration
Bibliographic record
Abstract
ABSTRACT To assess the potential impacts of climate change on white spruce local adaptation, six seed sources were evaluated seven years after plantation on two test sites with contrasting growing conditions and latitude in Quebec. Bud set, frost tolerance and analysis of non-structural carbohydrates (NSC) content showed important effects of test sites, seed sources, and their interactions on bud set phenology and growth. The average bud set initiation occurred one week later in the southern site compared to the northern site, whereas the late stage of bud set was similar between sites. Significant differences were observed between seed sources for some phenological stages. Frost tolerance was significantly lower in the southern site and below -12 °C for all seed sources sampled at the beginning of October. The trend in fructose and glucose content was opposite between sites in September. It decreased from September to October in the southern site and increased in the northern site, while sucrose content showed an opposite pattern, with the southwestern seed source harboring the lowest sucrose content. NSC content was also correlated to frost tolerance. Our study highlighted the crucial role of NSC in cold hardiness to early fall frosts and local adaptation. Implications for assisted migration are discussed.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".