Bibliographic record
Abstract
Hummocks, small earth or peat mounds, are widely distributed in the arctic and develop as a consequence of biomass accumulation and cryoturbation in the active layer. There is general agreement that the type of vegetation covering peat hummocks may alter the accumulation rate of organic material and thus hummock growth and local carbon sink dynamics. Studies on hummock plant community compositions from the arctic are very scarce. Here, I present results of a case study from the arctic tree-line near Churchill, Manitoba (Canada). Vegetation composition, hummock height and soil moisture content were recorded in 40 peat hummocks located along a tree-line gradient from open forest to tundra. Based on a cluster analysis I found three moss-dominated types of hummock vegetation, according to (1) a Tomenthypnum nitens (golden fuzzy fen moss) type on low hummocks, (2) a Hylocomium splendens (stair-step moss) type on medium-sized hummocks, and (3) a Pleurozium schreberi (red-stemmed feathermoss) type on hummocks higher than 60-70 cm. I found hummock height to increase towards the forest interior with decreasing water content of the upper organic layer on the hummock top. This is indicated by a significant change in vegetation composition towards drought resistant moss species on higher hummocks. Furthermore, species richness decreased with increase in hummock height. Based on evidence from historical tree-line invasion the overall results suggest that hummock height increases due to peat accumulation over the course of time resulting in a typical change in plant community composition.
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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 | 0.003 | 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) | 0.002 | 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".