Seed and microsite limitations to emergence of four annual weed species
Bibliographic record
Abstract
The emergence of annual species depends on the number of seeds present and the biotic and abiotic conditions directly surrounding those seeds (the microsite). A field experiment was conducted to study the relative importance of seed presence vs. microsite conditions in determining the emergence of four annual species. Green foxtail, wild mustard, wild oat, and canola were seeded at 200, 400, and 1,200 seeds m−2in separate plots in a coarse, loamy, mixed Typic Haplocryoll and a fine, mixed Typic Haplocryoll soil. Five microsite modification treatments (control, irrigation, soil compaction, soil compaction plus irrigation, and no crop) were applied to all weed seed density treatments for each weed species. All plots were seeded to spring wheat. Irrigation or soil compaction increased percent emergence of wild oat. Green foxtail emergence tended to increase with soil compaction in 2001 but not in 2002. Wild mustard and canola emergence were largely unaffected by microsite modification treatments. Weed emergence increased with increasing seed density for all species, but the proportion of the total number of seeds emerging decreased with increasing seed density for all species. We suggest that the emergence of the four weed species in this experiment was both seed and microsite limited. Increasing the number of seeds in the soil increased the probability of seeds landing within an appropriate microsite. For these four species, therefore, weed spread and weed patch formation may be determined both by seed production and dispersal and by variability in soil microsite conditions. Results suggest that weed management practices should limit seed dispersal of all species and discourage weed emergence of hard-to-control species during critical establishment periods.
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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 | 0.001 |
| 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) | 0.001 | 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".