Floristic diversity, size, and vertical distribution of the weed seedbank in ridge and conventional tillage systems
Bibliographic record
Abstract
The floristic diversity and the vertical distribution of the weed seedbank were studied in ridge tillage (RT) and conventional tillage (CT) systems in clay and clay loam soils. Viable seedbank populations were monitored during 3 yr using germination in a greenhouse. Ridge-tilled fields had a larger soil seedbank (2,992 seeds m−2) than moldboard-plowed fields (1,481 seeds m−2) in the top 15 cm. This result can be explained by the larger perennial seedbank of RT fields at both the 0- to 5-cm and 5- to 15-cm depths. Annual dicot seeds were more abundant in clay soils than in clay loams at the two soil depths. Annual grass seeds were more abundant under CT than under RT in clay soils at the two sampled depths. In clay loams, the density of annual grass seeds in RT fields was six times greater than in CT fields in the top 5 cm of soil and two times greater at the 5- to 15-cm depth. The vertical distribution of total seeds in soil did not differ between tillage systems. The top 5 cm of the 15-cm soil core contained 35 and 46% of all weed seed in CT and RT systems, respectively. However, the CT system had the highest concentration of annual dicot seeds 5 to 15 cm deep, whereas in the RT system, the same depth contained the highest concentration of perennial seeds. These results confirm that tillage systems and soil types can regulate seedbanks. Weed management programs must take this information into account.
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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) | 0.000 | 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 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".