Effects of weed and erosion control on communities of soil mites (Oribatida and Gamasina) in short-rotation willow plantings in central New York
Bibliographic record
Abstract
Several pre-emergent herbicides (azafenidin, oxyfluorfen, and imazaquin–pendimethalin mixture), used for weed control during the establishment of short-rotation willow plantings, were tested for their impact on population density, species richness, and community structure of predaceous (Gamasina) and saprophagous and (or) mycophagous (Oribatida) soil mites. The experimental control was hand-weeded (no herbicide). Two site preparation treatments were used: conventional (disked) and erosion controlled (no-till with cover crop of winter rye). The influence of herbicide application on non-target organisms (soil mites) cannot be generalized, with groups being differentially affected. Overall, Oribatida were most affected by herbicides. Among specific herbicides, azafenidin and oxyfluorfen had a negative effect on density and species richness of soil mites. The response of Oribatida and Gamasina to herbicides was species-specific. Two species of Oribatida ( Sellnickochthonius immaculatus (Forsslund) and Liochthonius lapponicus (Trägårdh)) declined significantly in all herbicide-treated plots. The cover crop residue had positive effect on both Oribatida and Gamasina; the negative effect of herbicides on Oribatida was greatly mitigated by cover crop. Herbicides appear to reduce mite diversity and alter community structure, but they do not always affect abundance. We speculate that the sensitivity of Oribatida to herbicides can reflect the indirect impacts of herbicides on soil microflora.
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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 | 0.000 | 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".