? Dr W. Junk Publishers, Dordrecht Printed in the Netherlands
Bibliographic record
Abstract
Multivariate methods were used to examine epiphytic species composition on the lower trunk of Acer mac rophyllum at five sites in south-coastal British Columbia, Canada. Differences in species composition and abundance between sites were attributed mainly to variation in relative humidity and light conditions. Bark chemistry differences accounted for only a small portion of the observed variation in epiphytic composition between sites. Within sites, compositional variation was examined over 0.5-5 m from ground level on the upper, vertical, and lower trunk surfaces of leaning trees. Compositional variation of the epiphytic vegetation with height and inclination tended to be more strongly developed at drier sites. Furthermore, at all sites com positional variation tended to be greater on upper (wetter) than on lower (drier) surfaces. Particular epiphytic species tended to occur in similar locations on the trunk surface at different sites, suggesting that some microhabitat specialization has occurred. Observed distributional shifts of epiphytic species appeared to be greatest among sites differing widely in prevailing microenvironmental conditions.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.599 | 0.487 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".