Conservation Issues in the High Arctic and Pole-to-Pole Comparisons
Bibliographic record
Abstract
With the increasing impacts of global change, conservation activities are more important than ever to protect and preserve high latitude environments and their biota. Efforts to date in the Arctic have focused on higher plants and animals; for example, the Red List of threatened Arctic plants is currently limited to vascular species, and no attention has been given to lower plant and microbial communities that are often dominant features of far northern ecosystems. One of the largest northern conservation zones in Canada is Quttinirpaaq National Park, a 37,775 km2 region that extends to the northern coast of Ellesmere Island, Nunavut. Studies over the last two decades at the northern coastline of this park have shown that the land, lake and fjord environments contain diverse microbial assemblages and functions ('environmental microbiomes') and that these are responding strongly to the current trend of accelerated warming at these extreme high latitudes (82-83N), leading to the extinction of certain ecosystem types. In Antarctica, increased (albeit still limited) attention is being given to protection measures for microbial ecosystems (e.g., ASPAs and SCAR codes of conduct for activities and research in terrestrial, geothermal and subglacial aquatic environments) and a similar level of stewardship is needed for analogous High Arctic microbial ecosystems. A Red List of vulnerable microbiomes in High Arctic and Antarctic environments may help inform conservation efforts.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".