Are tree trunks habitats or highways? A comparison of oribatid mite assemblages from hoop‐pine bark and litter
Bibliographic record
Abstract
Abstract Oribatid mites (Acari: Oribatida) are among the most diverse and abundant inhabitants of forest soil and litter, but also have species‐rich assemblages on bark and in the canopies of trees. It is unclear whether the trunk of a tree acts simply as a ‘highway’ for movement of mites into and out of the canopy, or whether the trunk has a distinctive acarofauna. We compare oribatid assemblages from the trunk bark of hoop pine (Araucaria cunninghamii) with those from litter collected beneath the same trees. A 1.0 by 0.5 m area of bark was sampled from three trees at each of five sites using a knockdown insecticide. A 1‐L sample of leaf litter was collected as close as possible to the base of each sampled tree. Mites were extracted using Tullgren funnels, identified to genus and morphospecies, and counted. Assemblages were almost 100% distinct, with only one oribatid morphospecies (Pseudotocepheus sp.) collected from both litter and bark. Litter had a higher taxon richness than bark in total and per sample, but oribatids made up a greater percentage of the acarofauna in the bark samples. We had expected that the more consistent physical substrate of bark would be reflected in greater similarity of oribatid faunas on trunks than in litter; however, the opposite proved to be the case. We conclude that hoop‐pine trunks are habitats rather than highways for oribatid mites. Based on the observed higher turnover among bark faunas, tree trunks may represent habitat islands whose colonisation by particular oribatid species is more stochastic than that of the more continuous ‘sea’ of litter.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".