Weeds in field margins: a spatially explicit simulation analysis of Canada thistle population dynamics
Bibliographic record
Abstract
Field margin weeds may contribute to the invasion and persistence of weeds in arable fields. Experimental studies of this hypothesis, however, have been inconclusive. We examined the role of field margin weed populations with a spatially explicit simulation model of Canada thistle population dynamics. We measured the contribution of field margin populations to weed pressure in the field across a wide range of parameter values and compared the weed control value of efforts applied to the field margin to that of similar efforts applied to the field. Under most combinations of parameter values, field margin weeds contributed little to weed pressure in the field, suggesting that controlling field margin weeds may often be of little value. Two conditions appeared to be necessary for field margin weeds to influence weed population dynamics within the field: the presence of unoccupied weed habitat, which increased the importance of dispersal to population growth, and high dispersal rates of field margin weeds relative to field weeds, which increased the relative contribution of field margin weeds to dispersal.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".