Assessment of assisted migration effects on spring bud flush in white spruce (<i>Picea glauca</i>[Moench] Voss) seedlings
Bibliographic record
Abstract
In a changing climate, delaying the time of bud flush may be advantageous to boreal forest species to reduce the risk of spring frost damage. In this study, we examined the potential effect of assisted migration of tree seed on time to bud flush for white spruce. Flushing times of seedlings from 23 white spruce provenances from Ontario were observed under varying temperature conditions simulated in controlled environment chambers. Results indicated that time to bud flush varied considerably among provenances. Although higher temperatures significantly promoted bud flushing for all provenances, provenance-by-temperature interactions were negligible, indicating stable performance of white spruce provenances for this adaptive trait. Spatial patterns of variation among provenances in bud flushing were not consistent with patterns found in range-wide provenance tests. Assisted migration of tree seed across relatively short distances is unlikely to delay bud flushing time in white spruce. Some southern populations may flush earlier at more northerly sites, which would exacerbate spring frost risk. Tree improvement may be an effective approach to utilize amongand withinprovenance variation to enhance this fitness trait for better climatic adaptation.
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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) | 0.000 | 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 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".