Short-term effects of timber harvest and forest edges on ground-layer mosses and liverworts
Bibliographic record
Abstract
Limited information exists on the effects of forest management practices on bryophytes, despite their importance to forest ecosystems. We examined short-term responses of ground-layer bryophytes to logging disturbance and creation of edges in mature Pseudotsuga forests of western Washington (USA). The abundance and richness of species were measured in four 1-ha forest aggregates (patches of intact forest) and in surrounding logged areas before and after structural retention harvests. One year after treatment, species richness, total cover, and frequency of most moss and liverwort taxa declined within harvest areas. Within forest aggregates, mosses did not show significant edge effects; however, richness and abundance of liverworts declined with proximity to the aggregate edge. Our results suggest that, over short time frames, 1-ha-sized aggregates are sufficient to maintain most common mosses through structural retention harvests but are not large enough to prevent declines or losses of liverworts. Thus, current standards for structural retention, which allow for aggregates as small as 0.2 ha, may be inadequate to retain the diversity and abundance of species found in mature, undisturbed forests.Key words: bryophyte, edge effects, forest borders, forest management, logging effects, structural retention harvest.
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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 | 0.000 | 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".