Short-term impacts of partial cutting on lichen retention and canopy microclimate in an Engelmann spruce subalpine fir forest in north-central British Columbia
Bibliographic record
Abstract
The retention of canopy lichens (Alectoria, Bryoria, and foliose) in group selection (GS) and single-tree selection (STS) partial cuts (30% removal) was studied within a subalpine sprucefir forest (Picea englemannii Parry ex Engelm. Abies lasiocarpa (Hook.) Nutt.) in north-central British Columbia. Baseline canopy lichen loading (preharvest and immediate postharvest) was compared with lichen loading 2 years after harvesting, using both ground- and canopy-based sampling techniques. Additionally, canopy microclimate was compared between GS and adjacent stand areas with no harvest treatment (NT). Partial cutting did not have a significant effect on lichen loading in residual trees, although a trend of declining lichen abundance was observed in each of the GS, STS, and NT areas. Partitioning of lichen abundance data showed significant postharvest declines for upper canopy STS Bryoria and smaller, but significant, changes in foliose lichen abundance in the NT and STS areas. No significant changes in canopy microclimate were observed between treatments, with the exception of south-facing aspects in GS trees, which showed reduced duration of lichen hydration. Taken together, these factors suggest that although the placement of Bryoria in residual trees may shift towards lower canopy exposures, partial-cut harvest treatments can maintain short-term lichen loading and associated ecosystem values (e.g., caribou forage) in subalpine sprucefir stands.
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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 | 0.001 |
| 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".