Arboreal forage lichens in partial cuts – a synthesis of research results from British Columbia, Canada
Bibliographic record
Abstract
The mountain ecotype of the woodland caribou (Rangifer tarandus caribou) is highly dependent on the arboreal hair lichens Bryoria spp. and Alectoria sarmentosa during winter. In parts of British Columbia, partial-cutting silvicultural systems have been used in an effort to provide continuously usable winter habitat for mountain caribou, while allowing some timber removal. We reviewed available information about the changes in hair lichens after partial cutting in Engelmann spruce (Picea engelmannii) – subalpine fir (Abies lasiocarpa) forests of British Columbian and Idaho. Generally, abundance of Bryoria spp. in the lower canopy of individual residual trees increases with increased exposure after partial cutting, until the new regeneration begins to shelter the lower canopy of the residuals. Heavy basal area removal, however, results in low lichen availability at the stand level for many years. Abundance of Bryoria on the regeneration is low, and appears to be limited largely by the structure of the young trees, not by lichen dispersal, although dispersal capability may be limiting in Alectoria. Both distributional and physiological data suggest that Bryoria is intolerant of prolonged wetting, and that increased ventilation, rather than increased light, accounts for enhanced Bryoria abundance in the partial cuts. Alectoria sarmentosa reaches its physiological optimum in the lower canopy of unharvested stands; its growth rates are somewhat reduced in the more exposed environment of partial cuts. Both genera are capable of rapid growth: over a 7-year period, individual thalli of A. sarmentosa and Bryoria spp. (excluding those with a net biomass loss due to fragmentation) in an unlogged stand more than tripled their biomass. Calculated growth rates, as well as dispersal potential, are influenced by fragmentation. Bryoria produces more abundant, but smaller, fragments than Alectoria, and fragmentation in both genera increases in partial cuts. In subalpine mountain caribou habitat, partial-cutting prescriptions that enhance exposure of residual trees while keeping basal area removal low will maintain forage best. Regeneration management should focus on maintaining ventilation in the lower canopy of the residual stand.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.018 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".