Can partial-cut harvesting be used to extend the availability of terrestrial forage lichens in late-seral pine-lichen woodlands? Evidence from the Lewes Marsh (southern Yukon) silvicultural systems trial
Bibliographic record
Abstract
In northern British Columbia and southern Yukon woodland, caribou forage extensively on terrestrial lichens, predominately mat-forming Cladina species in late-successional pine-lichen woodlands. Many of these stands are now reaching a point in their development where lichen abundance declines as feather-moss mats increase. We evaluated the response of forest floor plant communities in pine-lichen woodlands from the southern Yukon Lewes Marsh partial-cutting trial 8 years after harvesting. Photoplot results documented a major decline (>60% ± 5.6% SE) in the mean surface area of existing large clumps of C. mitis in control (unharvested) treatments, whereas the mean surface area of large C. mitis clumps declined by 28% (±15% SE) in the one-third basal-area removal and showed an increase of 13.5% (±25% SE) in the two-thirds basal-area removal. Line intercept transects documented no changes in overall stand-level lichen abundance between pre-harvest (2012) and post-harvest (2021) measurements, while feather-moss mats and dwarf shrubs showed declines and increases, respectively, in partial-cutting harvest plots. Stand thinning may provide a bridging strategy to extend the period of forage lichen availability in late-seral pine-lichen woodlands, an important consideration in landscapes where increasing severity and frequency of fires are changing the seral-state distribution of caribou habitat.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".