Effects of variable canopy retention harvest on epixylic bryophytes in boreal black spruce – feathermoss forests<sup>1</sup>This article is one of a selection of papers from the International Symposium on Dynamics and Ecological Services of Deadwood in Forest Ecosystems.
Bibliographic record
Abstract
Modification of forest attributes and structural components like downed wood (DW) during forest harvest can lead to local species loss. Epixylic bryophytes have been proposed as good indicators of such changes. Unharvested control, variable canopy retention, and single pass harvest represent a gradient in forest harvest impact and can be used to test the response of epixylic bryophytes to different levels of environmental change. The objective of this study was to see if variable canopy retention attenuates environmental change associated with harvesting, consequently maintaining an epixylic community more similar to unharvested stands than single pass harvesting. Environmental conditions and DW characteristics were sampled on 225 DW pieces distributed in 45 permanent plots. Results showed that treatment affected epixylic richness through its impact on canopy openness and DW diameter and decomposition class. Fewer species were found in more open habitats and more species were found on bigger and more decomposed DW. Most epixylic species were more commonly found on the forest floor than on the DW. In conclusion, variable canopy retention harvest offered microclimatic conditions and DW availability and quality more suitable for epixylic species than single pass harvest, which was less suitable for epixylic 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 | 0.000 |
| 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".