Subarctic Thermokarst Ponds: Investigating Recent Landscape Evolution and Sediment Dynamics in Thawed Permafrost of Northern Québec (Canada)
Bibliographic record
Abstract
Although widely distributed throughout Arctic and subarctic regions, thermokarst ponds and lakes remain relatively unexplored regarding geomorphological changes in their catchments and their internal properties in relation to climate change over the past decades. This study synthesizes recent landscape evolution and modern sedimentology of limnologically diverse thermokarst ponds near southeastern Hudson Bay, Canada. Spatio-temporal analysis of permafrost mounds, thermokarst ponds, and vegetation surface areas over the past five decades revealed that the recent climate-induced decrease of permafrost-affected areas was not primarily compensated by thermokarst pond development, but rather by a remarkable increase in vegetation cover. These changes appeared to be modulated by topographical and hydrological gradients at the study site, which are associated with east-ward increasing thickness of postglacial marine deposits. At a more contemporary timescale, physico-chemical measurements made on sedimenting materials (sediment traps) and freshly deposited lacustrine sediments of selected thermokarst ponds revealed striking differences both among ponds and between the oxic epilimnion and the oxygen-depleted hypolimnion. These findings underscore the major influence of local landscape properties and oxycline development on pond sedimentology and geochemistry, such as the transport of detritic particles and the concentration of redox-sensitive elements.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".