Diversity and Distribution of Oribatid Mites (Acari: Oribatida) Associated with Arboreal and Terrestrial Habitats in Interior Cedar-Hemlock Forests, British Columbia, Canada
Bibliographic record
Abstract
We assessed oribatid mite abundance, species richness and community composition in arboreal and terrestrial habitats associated with 12 western redcedar trees in the Interior Cedar-Hemlock biogeoclimactic zone of British Columbia, Canada. We extracted microarthropods from 36 canopy litter samples, 36 epiphytic lichen samples from three different lichen functional groups, and 36 soil core samples of the forest floor litter layer. Oribatid mites dominated microarthropod assemblages in all habitats. Total microarthropod and oribatid mite abundances were significantly greater in forest floors and foliose (leaf-like) lichens compared to canopy litter accumulations, and alectorioid (hair-like) and cyanolichen (lobed) groups. Sixty-one species of oribatid mites were identified from the study area. The ten species collected from canopy litter and 14 species collected from epiphytic lichens shared five species in common, whereas only three of the 45 species collected from the forest floor also were found within the canopy system. Principal components analysis and discriminant function analysis differentiated three distinct assemblages of oribatid mites corresponding to the canopy litter accumulations, epiphytic lichens and forest floor habitats. Low abundance of oribatid mites in canopy litter accumulations is attributed to low microhabitat structural complexity, low food resources and low desiccation resistance in these habitats compared to canopy lichen habitats and the forest floor. Epiphytic lichens are the dominant habitat for arboreal oribatid mites in the ICH forest zone, and contribute to the overall biodiversity of the forest system by containing distinct oribatid mite assemblages.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".