Stand openness predicts hair lichen (Bryoria) abundance in the lower canopy, with implications for the conservation of Canada’s critically imperiled Deep-Snow Mountain Caribou (Rangifer tarandus caribou)
Bibliographic record
Abstract
Tree-dwelling hair lichens in the genus Bryoria provide crucial late-winter forage for Deep-Snow Mountain Caribou (DSC), an imperiled ungulate endemic to south-central British Columbia, Canada. Because DSC survival requires continuous access to heavy hair lichen loadings, conservation efforts can benefit from an improved understanding of the factors that contribute to such loadings. Here we quantify the relation of Bryoria abundance to stand spacing by testing an “Angle-To-Canopy-Skyline” (ATCS) protocol as a measure of stand openness and a proxy for ventilation. Fieldwork conducted in 60-year-old conifer forests on a 250-m conical volcano within the range of DSC yielded three principal findings: (1) Bryoria abundance strongly increases with increasing stand openness; (2) Pinus contorta supports much heavier Bryoria loadings than other local host trees; and (3) ATCS is a powerful predictor of arboreal hair lichen abundance in general across a wide range of environmental settings, but does not predict the abundance of foliose lichens. We suggest that canopy openness, at least within the range of DSC, complements stand age as a key factor in the development of heavy Bryoria loadings, consistent with the hypothesis that Bryoria benefits from rapid drying after rain. The possibility that anomalously high Bryoria abundance on Pinus may hold promise for accelerated DSC habitat restoration following clearcut logging is explored but rejected.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".