Seed germination response to temperature for a range of international populations of <i><scp>C</scp>onyza canadensis</i>
Bibliographic record
Abstract
Summary Conyza canadensis is a surface‐germinating ruderal facultative winter annual with recruitment that is highly susceptible to changes in microsite conditions. A key adaptive characteristic for a facultative winter annual species, like C. canadensis, is germination response to temperature. The objective of this study was to determine the germination response to temperature for C. canadensis seed sourced from regions around the world with differing climates and, by doing so, gain insight into the role that seed germination biology plays in the adaptiveness and weediness of facultative winter annual weeds. Seed was sourced from populations in Málaga, Spain, Hertfordshire, UK, Shiraz, Iran and southern Ontario, Canada, and grown out in a common garden under controlled conditions to produce seed for this study. These seeds were then subjected to temperatures from 6.5 to 20°C at 1.5°C increments using a thermogradient plate. Cumulative daily germination counts for 30 days were recorded. Results indicated that temperature and source location had a significant effect on germination response. Estimated base germination temperature ranges were significantly different among the populations [Ontario (8–9.5°C), Iran (9.5–11°C), Spain (12.5–14°C), UK (11–12.5°C)], as were accumulated growing degree days (GDDs; d°C) required to reach 50% germination. For three of the four populations, estimated base germination temperature range values were below those previously reported in the literature. These differences are most likely rapid evolutionary adaptations to local climate and highlight the potential C. canadensis has to be problematic as a native and invasive species.
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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) | 0.001 | 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".