Forest structure and site conditions of boreal felt lichen (<i>Erioderma pedicellatum</i>) habitat in Cape Breton, Nova Scotia, Canada
Bibliographic record
Abstract
Boreal felt lichen [Erioderma pedicellatum (Hue) P.M. Jorg. (1972)] occurs on mainland Nova Scotia as well as Cape Breton, growing almost entirely on balsam fir [Abies balsamea (L.) Mill.] in wet coastal forests. A Geographical Information System (GIS) based predictive model for E. pedicellatum habitat in Nova Scotia has facilitated surveys and guided conservation. We used this model to examine the relationship between presence of E. pedicellatum and forest structure (tree DBH, height, age, and crown closure, inter-tree distance, basal area of live and dead trees, and percent cover of shrubs, herbs, Sphagnum spp., and other mosses), and site conditions (topographic position, slope, aspect, and drainage) as well as the presence of lichen indicator species. Erioderma pedicellatum sites had significantly older trees, higher density of live trees, lower crown closure, lower basal area of live Picea mariana (Mill.) Britton, Sterns & Poggenb., lower basal area of live trees, higher basal area of dead trees, higher Sphagnum spp. cover, and lower shrub cover than unoccupied habitat. Erioderma pedicellatum sites were significantly less well drained and occurred on steeper slopes with a north or east aspect. Four macrolichens (Coccocarpia palmicola, Platismatia norvegica, Lobaria scrobiculata, and Sphaerophorus globosus) occurred at a significantly higher frequency at E. pedicellatum sites.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".