Timing of seed germination correlated with temperature-based environmental conditions during seed development in conifers
Bibliographic record
Abstract
Abstract Ecological (climatic and geographic) variation in early life-history transitions is a vital determinant of the adaptive evolution of timing of seed germination. This study aimed to investigate the correlation between timing of seed germination and environmental conditions during seed development. We examined seed germination timing of 15 coniferous seed lots of lodgepole pine, ‘interior’ spruce and western hemlock collected from natural stands in British Columbia (BC), Canada, under manipulated [stratification, thermo-priming (15 or 20°C) and their combinations] and non-manipulated (control) conditions. Timing of seed germination showed strong and positive correlation with the temperature-based environmental condition during seed development. This pattern persisted across species and seed lots within species, substantiating the historic importance of environmental conditions during seed development and maturation to life-history traits. Moreover, the strategy of phenotypic plasticity affecting timing of seed germination was observed across the applied germination treatments. These results provide insight into the germination niche as affected by global warming, indicating that conifers' seed dormancy in BC (north of 54°N) tends to increase and the changes associated with early spring warm-up are expected to accelerate seedling emergence, as shortened winters would have a minimal effect on dormancy decay.
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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".