Burial Environment Drives Seed Mortality of Kochia (Bassia scoparia), Wild Oat (Avena fatua), and Volunteer Canola (Brassica napus) Irrespective of Crop Species
Bibliographic record
Abstract
Models of weed population demography are critical to understanding the long-term viability of management strategies. The driving factors of weed seedbank persistence are often underrepresented in demographic models due to the cumbersome nature of seedbank research. Simplification of weed seedbank dynamics may induce substantial error in model simulations. A soil bioassay was conducted to determine whether growth of different crop species, including wheat (Triticum aestivum L.), canola (Brassica napus L.), and field pea (Pisum sativum L.), differentially impact seed mortality of kochia [Bassia scoparia (L.) A.J. Scott], wild oat (Avena fatua L.), and volunteer canola in seven burial environments in western Canada. Weed seed survival after the 7 week burial period varied widely among burial environments (from 8% to 88% when averaged among weed and crop species), whereas growth of the different crop species had negligible impact on seedbank persistence. Among environments, wild oat seed survived the greatest (79%), followed by kochia (20%), and volunteer canola (6%). Weed seed survival was associated with soil physical properties (texture) and seed microsite characteristics (temperature), but not crop species or soil chemical properties. Overall, these data support the need for greater integration of soil and environmental parameters into models of weed population demography.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".