Secondary dormancy, temperature, and burial depth regulate seedbank dynamics in canola
Bibliographic record
Abstract
In western Canada, seasonal seedling recruitment has been reported in weedy canola populations, and seed persistence has been linked to the secondary seed dormancy potential of a genotype. Temperature influences secondary seed dormancy induction in this species. In these experiments we (1) investigated the influence of temperature and osmotic potential on secondary seed dormancy induction in canola, (2) related these to seedbank dynamics and seedling recruitment of two canola genotypes with different seed dormancy potentials in the field, and (3) investigated the influence of residue, burial depth, and soil type on seedbank dynamics and seedling recruitment in the field. In the laboratory, rates of seed dormancy induction were positively correlated to increasing temperatures and water stress. The role of temperature was approximately threefold more important to seed dormancy development than was osmotic potential within the tested ranges of these variables. In the field, seasonal seedbank dynamics of canola buried at 10 cm were strongly influenced by a genotype's inherent potential for secondary dormancy. An increase in the ungerminable portion of the seedbank was observed in the high-dormancy genotype as soil temperatures increased during spring. This did not occur in the low-dormancy genotype, resulting in sixfold less seed persistence in this genotype by midsummer, by which time, the total remaining seedbank was ungerminable in both genotypes. At the 1-cm burial depth, most of the seedbank was depleted by midsummer of the year after seedbank establishment because of high seedbank mortality in all treatments. Thus, the seasonal recruitment behavior in canola was primarily a function of seed death in the shallow seedbank and a shift to an ungerminable state in the deep seedbank.
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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 | 0.000 | 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".