Tree hollows can affect epiphyte species composition
Bibliographic record
Abstract
Abstract Tree hollows often harbor animals and microorganisms, thereby storing nutritive resources derived from their biological activities. The outflows from tree hollows can create unique microenvironments, which may affect communities of epiphytic organisms on trunk surfaces below the hollows. In this study, we tested whether the species richness and composition of epiphytic bryophytes (liverworts and mosses) and lichens differ above and below tree hollows of Aria japonica and Cercidiphyllum japonicum in a Japanese temperate forest. The species richness of epiphytic bryophytes and lichens did not differ above and below hollows; however, the species composition of bryophytes differed significantly above and below hollows. Indicator species analyses showed that the moss species Anomodon tristis and the liverwort species Porella vernicosa were significantly more common below than above hollows, while the liverwort species Radula japonica and four lichen species, including Leptogium cyanescens , occurred more frequently above than below hollows. Our results highlight that tree hollows can produce unique microenvironments on trunk surfaces that potentially contribute to the maintenance of epiphytic diversity on a local scale.
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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 | 0.001 |
| 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".