Responses of boreal epiphytic bryophytes to different levels of partial canopy harvestThis paper is one of a selection of papers published as part of the special Schofield Gedenkschrift.
Bibliographic record
Abstract
Epiphytic mosses and liverworts contribute substantially to the bryophyte diversity of circumpolar boreal forests but are susceptible to altered growing conditions after forest harvesting. Management practices that retain some trees after harvest may enhance epiphyte survival; however, the effectiveness of this emerging method needs to be assessed. We examined the survival, composition, and nearest neighbour relationships of epiphytic bryophytes on trembling aspen ( Populus tremuloides Michx.) across a range (10%–100%) of dispersed green-tree retention 5 years after harvest in boreal mixed-wood forest. Growth of the forest floor moss Hylocomium splendens (Hedw.) Schimp. in B.S.G. was used as an indicator of changes in moisture availability for epiphytes following harvesting. Epiphyte richness and abundance increased with canopy retention and were positively correlated with local abundance of coniferous trees. Positive associations among neighbouring species in intact forest demonstrated that interspecies relationships form naturally. However, there was a shift in species composition after harvesting and fewer interspecific associations with declining retention. These trends were accompanied by reduced Hylocomium splendens growth, which implies that moisture may be an important driver of epiphyte response. Although different levels of canopy retention were similarly capable of maintaining some epiphytes, the loss of species associated with intact forest will require consideration of alternative management practices for their conservation.
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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".