A preliminary investigation of the lichen biota associated with recently deglaciated terrain in southeastern Alaska
Bibliographic record
Abstract
Glaciers worldwide are currently retreating at unprecedented rates, revealing large tracts of newly exposed rock and till. We present the results of a preliminary, qualitative investigation of the lichen diversity of transient habitats near three glaciers in southeastern Alaska: Muir Glacier within Glacier Bay National Park, and Baird and Patterson Glaciers in the Tongass National Forest. This work is noteworthy as it (i) documents previously undescribed lichen species and communities within rapidly changing glacier habitats, (ii) illustrates the importance of cryptogams (lichens, bryophytes, algae, and cyanobacteria) in the primary colonization of recently deglaciated terrain, (iii) sets apart the lichen biota of recently deglaciated terrain in southeastern Alaska from that of other glacial regions worldwide (e.g., the European Alps, Svalbard, and southern South America) and even other parts of Alaska (e.g., Brooks Range), and (iv) emphasizes the importance of more lichen studies that focus on this rapidly changing habitat. The lichen biotas found at different successional stages near these glaciers are described and compared. The role of lichens and other cryptogams in post-glacial vegetation initiation, the threats to the lichen biota, and suggestions for the possible origins of the lichen propagules that colonize these newly exposed surfaces are also discussed.
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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 | 0.001 | 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".