Forest floor microarthropod abundance and oribatid mite (Acari: Oribatida) composition following partial and clear-cut harvesting in the mixedwood boreal forest
Bibliographic record
Abstract
The effects of partial and clear-cut harvesting on abundance and community composition of forest floor microarthropods and oribatid mites were investigated in conifer and deciduous stands of the mixedwood boreal forest. Soil samples from clearcuts, strip-cut corridors in a partial cut, green-tree retention patches in a partial cut, and uncut control sites were collected 2.5 years after harvest and microarthropods were extracted, enumerated, and identified. Densities of microarthropod suborders were lower in the strip-cut corridors of the deciduous stands and significantly lower in the suborder Oribatida (oribatid mites). Changes in microarthropod community composition, decreased relative abundance of prostigmatid mites, and increased relative abundance of mesostigmatid mites were observed in corridor and clear-cut treatments. Lowered abundances and changes in community composition are likely due to compaction of the forest floor during harvesting. Selected oribatid mite species showed significantly lower abundances in clearcuts than in uncut sites, but diversity indices for oribatid mites were generally not significantly different between uncut sites and clearcuts. Changes in oribatid mite communities following harvesting were thus more quantitative (absolute abundance) than qualitative (diversity, composition), and as a result, use of oribatid mites as biological indicators of disturbance is limited because of the lack of changes in species composition.
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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) | 0.000 | 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".