Effects of Seedling Emergence Timing on the Population Dynamics of Horseweed (<i>Conyza canadensis</i>var.<i>canadensis</i>)
Why this work is in the frame
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Bibliographic record
Abstract
Horseweed is a surface-germinating ruderal facultative winter annual. The ruderal nature is a key adaptive characteristic that implicates emergence timing as an important recruitment factor. Experiments were established at three sites in southern Ontario, Canada, from 2009 to 2012 to determine the possible effect of emergence timing of horseweed on plant number, fecundity, and flowering timing. Emerged seedlings were tagged in 0.25-m 2 plots in five 2-wk cohorts in the fall and spring of each experimental season. Each plot was followed though until the plants contained within each plot completed their life cycle. Generally, spring-emerging plants were found to flower earlier than fall-emerging plants, but with fall emergence there were higher plant densities in August each season compared with spring emergence. Overall, there was no difference in fecundity between spring- or fall-emerging cohorts, but when cohorts were parsed beyond just spring or fall emergence, we found that plants emerging in early fall and early spring were more fecund and flowered earlier than plants emerging in late fall and late spring. Disturbance (tilled versus not-tilled) significantly affected emergence levels but not emergence timing. The differences in performance among emergence cohorts are likely due to spatial or temporal density-dependent growth advantages. These results show that spring-emerging cohorts of horseweed, especially early spring–emerging cohorts, should not be discounted when considering the weediness of this species, and this may hold true for other facultative winter annual weeds as well.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it