Plasticity plays a dominant role in regulating the phenological variations of sugar maple populations in Canada
Bibliographic record
Abstract
Global changes affect the growing conditions of terrestrial ecosystems, causing a mismatch between plant phenology and local climates in Northern regions. Due to their long lifespan and irregular regeneration periods, trees cannot respond quickly enough to climate variability through long-term genetic adaptation. In this study, we explored the phenological plasticity and genetic variation among populations of bud burst in sugar maple (Acer saccharum Marsh.) seedlings from 30 Canadian provenances with contrasting climates planted in two common gardens near and at the northern limit of the species’ range. We tested the hypothesis that phenotypic plasticity and genetic variation among populations affect bud phenology. We expect that phenotypic plasticity is more important in regulating bud phenology due to the high variability in short-term weather events characterizing this part of North America. Bud development and leafing occurred in April–May, with complete bud burst lasting between 21 and 29 days. On average, bud swelling differed by 12 days between common gardens. Both factors site (common gardens) and provenance significantly affected bud burst, demonstrating phenological plasticity and genetic variation of sugar maple, respectively. A significant interaction between site and provenance was also found. Overall, the site (11.8–90.3%) contributed more than provenance (0–3.1%) to the variance in timings of bud burst, indicating a dominant role of plasticity in regulating spring phenology. Our study demonstrated the concurring effects of genetic variation and phenological plasticity of sugar maple and revealed the dominant role of the latter factor. The high plasticity observed in sugar maple has a crucial role in the phenological adaptation of maple and the survival of its local populations in a context of changing climate.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".