Identifying important characteristics for critical habitat of boreal felt lichen (Erioderma pedicellatum) in Newfoundland, Canada
Bibliographic record
Abstract
In conservation management, outlining critical habitat is an important factor to consider when making recommendations on specific actions. Our study adopts a multi-level approach to determine critical habitat characteristics for boreal felt lichen (Erioderma pedicellatum (Hue.) P.M.Jørg.). The boreal felt lichen in the Avalon Forest Ecoregion of Newfoundland nearly exclusively inhabits balsam fir in old-growth forest stands. However, other factors still need to be determined to better understand what constitutes “critical habitat” in this region, i.e., what are the characteristics of the best quality forest stand for boreal felt lichen? We tested multiple working hypotheses at three levels: 1) at the tree-level, we examined tree morphometrics to determine substrate quality within the lichen habitat; 2) at the plot-level we assessed habitat characteristics and variation in landscape characteristics that can be captured within the 5 m plot radius; 3) we also measured habitat variables beyond the 5 m plot radius, these variables included distance from gaps of various types, elevation and distance from deciduous trees. In our study site, we compared 25 plot pairs, where one plot contained at least one boreal felt lichen thallus and the other contained no thalli. Our findings suggest that characteristics at each level are important when determining critical boreal felt lichen habitat. The tree-level models indicate that boreal felt lichen is likely to occur on trees with a small diameter (5–12 cm). The plot-level models show that north facing slopes are an important habitat characteristic. The beyond-plot analysis suggests an association with distance to deciduous trees, however findings were not consistent with the dripzone hypothesis; perhaps proximity to deciduous trees indicates poor habitat quality. The findings of this study will help streamline future survey efforts and guide important criteria in protecting critical habitat.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".