Resilience of bryophyte communities in regenerating matrix forests after logging in temperate rainforests of coastal British ColumbiaThis paper is one of a selection of papers published as part of the special Schofield Gedenkschrift.
Bibliographic record
Abstract
The resilience (measured as changes in functional group representation and species composition) of bryophyte communities found in the younger-aged (“matrix”) forests surrounding old-growth remnants was examined in two different forest types, warmer, drier (Nimpkish) versus cooler, wetter (Sayward), on Vancouver Island, British Columbia. Bryophytes were sampled within 10 m × 2 m belt transects (species composition only) and using 10 cm × 30 cm microplots (composition and abundance) in two age classes of matrix forest, clearcuts (age 7–20 years), and second-growth (age 25–49 years) as well as in remnant old-growth forest stands (age >300 years). The cover of all bryophytes was diminished and more patchily distributed in younger-aged stands; however, the richness and frequency of bryophyte functional groups showed different responses in the two younger age class forests. Disturbance-associated species exhibited both higher richness and frequency in clearcut plots and higher richness in second-growth plots. In comparison, the richness of species associated with old-growth was largely unchanged in younger-aged forests compared with old-growth forests; however, the frequency of occurrence of species associated with old-growth was significantly reduced in younger-aged forests. The cooler, wetter forests exhibited greater resilience, as the difference in species composition between second-growth and old-growth stands was less than that between second-growth and old-growth stands in the warmer, drier forests. The greater difference in second-growth species composition in the warmer, drier forests was attributed mainly to the persistence of disturbance-associated species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".