Forest age and management effects on epiphytic bryophyte communities in Adirondack northern hardwood forests, New York, U.S.A.
Bibliographic record
Abstract
The objective of this study was to assess the influence of substrate heterogeneity on epiphytic bryophyte communities in northern hardwood forests of varying disturbance histories. Specifically, we compared bryophyte abundance (m2·ha1) and community composition among partially cut; maturing, 90- to 100-year-old, even-aged; and old-growth northern hardwood stands in Adirondack Park, New York, U.S.A. Total bryophyte cover from 0 to 1.5 m above ground level on trees [Formula: see text]10 cm diameter at breast height (DBH) did not differ among the three stand types. However, bryophyte community composition differed among host tree species and among stand types. Communities in partially cut and maturing stands were dominated by xerophytic bryophytes (Platygyrium repens, Frullania eboracensis, Hypnum pallescens, Brachythecium reflexum, Ulota crispa), while old-growth stands contained a greater representation of calcicoles and mesophytic species (Brachythecium oxycladon, Anomodon rugelii, Porella platyphylloidea, Anomodon attenuatus, Leucodon brachypus, Neckera pennata). This mesophyte-calcicole assemblage occurred in all stand types but was limited by the abundance of large-diameter (>50 cm DBH), thick-barked, hardwood host trees (Acer saccharum Marsh., Tilia americana L., Fraxinus americana L.). This study suggested that epiphytic bryophyte diversity can be sustained and enhanced in managed northern hardwood forests by maintaining host tree species diversity and retaining large or old, thick-barked residual hardwood stems when applying even-aged and uneven-aged silviculture systems.
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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".