Factors Influencing Bryophyte Assemblage at Different Scales in the Western Canadian Boreal Forest
Bibliographic record
Abstract
This study examined bryophyte community composition in relation to microsite and microenvironmental variation at different scales in three conifer-dominated stands in the boreal forest of Alberta, Canada. We documented bryophyte assemblage on specific microsite types (physiognomic forms providing substrates for moss colonization: logs, stumps, tree bases, undisturbed patches of forest floor, disturbed patches of forest floor), and at coarser scales: mesosites (625 m2 plots within stands), and stands (10 ha). Patterns of variation in bryophyte composition arising from the microsite sampling were clearly related to microsite type and, for woody substrates, to microsite quality (decay class; hardwood vs. softwood). Microenvironment (moisture, pH, temperature, light) also had some influence on bryophyte composition of woody microsite types. Forest floor moisture, pH, and light were related to bryophyte composition of undisturbed patches of forest floor while forest floor moisture and temperature were significant correlates for disturbed forest floor. At the coarser-scale, surface moisture and forest floor moisture were related to bryophyte assemblage of mesosites; this was partially reflective of differences among stands. We conclude that bryophyte species composition in these forests is related to a hierarchy of factors including fine scale variation in the type and quality of available microsites along with microenvironmental variation at different scales. Management efforts to preserve bryophyte biodiversity will need to incorporate this complexity.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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".