The role of the circumarctic forest–tundra ecotone for Arctic biodiversity
Bibliographic record
Abstract
The arctic forest–tundra ecotone (FTE), which links species communities of the boreal forest with those of the arctic tundra, is expected to respond swiftly to climate change with a profound reduction of tundra as the dominating scenario. With its circumarctic expanse and up to several hundred kilometres in width, the zone occupies a large part of the vegetated surface at high latitudes. Relocation and structural changes of the ecotone vegetation will affect not only plant but also animal and other biological diversity. A large number of arctic species are dependent on the FTE in terms of food and habitat during parts of their life cycle or annual migration. In the ‘Arctic Species Trend Index’, developed to provide trends in arctic vertebrates, more than half of the species and data are from the FTE. However, in assessments of arctic biodiversity, only the northernmost tundra-dominated areas of the ecotone are included. This is unfortunate and somewhat problematic since the treed part that serves as a source of seeds for new seedlings and saplings in the tundra-dominated part is excluded. This inconsistency hampers monitoring efficiency and biodiversity conservation efforts. During the International Polar Year, a large international research project on the FTE established numerous sites around the circumpolar north where causes and consequences of vegetation change were analysed. This network of sites and data forms an excellent basis for necessary monitoring of the spatial and temporal complexity of forest encroachment into tundra and its relation to arctic biodiversity.
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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 | 0.001 | 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".