Paleoecological Evidence for Transitions between Contrasting Landforms in a Polygon-Patterned High Arctic Wetland
Bibliographic record
Abstract
The formation of many arctic wetlands is associated with the occurrence of polygon-patterned permafrost. Existing scenarios to describe and explain surface landforms in arctic wetlands (low-center and high-center polygons and polygon ponds) invoke competing hypotheses: a cyclic succession (the thaw-lake hypothesis) or a linear succession (terrestrialization). Both hypotheses infer the predictable development of polygon-patterned wetlands over millennia. However, very few studies have applied paleoecological techniques to reconstruct long-term succession in tundra wetlands and thereby test the validity of existing hypotheses. This paper uses the paleoecological record of diatoms to investigate long-term development of individual polygons in a High Arctic wetland. Two landform processes were examined: (1) the millennial-scale development of a polygon-pond, and (2) the transition from low-center to erosive high-center polygons. Diatom assemblages were quantified from habitats associated with contrasting landforms in the present-day landscape, and used as an analog to reconstruct past transitions between polygon types. On the basis of this evidence, the paleoecological record does not support either of the existing models describing the predictable succession of polygon landforms in an arctic wetland. Our results indicate a need for greater paleoecological understanding, in combination with in situ observations in present-day geomorphology, in order to identify patterns of polygon wetland development and elucidate the long-term drivers of these landform transitions.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".