Thawing of massive ground ice in mega slumps drives increases in stream sediment and solute flux across a range of watershed scales
Bibliographic record
Abstract
Abstract Ice‐cored permafrost landscapes are highly sensitive to disturbance and have the potential to undergo dramatic geomorphic transformations in response to climate change. The acceleration of thermokarst activity in the lower Mackenzie and Peel River watersheds of northwestern Canada has led to the development of large permafrost thaw slumps and caused major impacts to fluvial systems. Individual “mega slumps” have thawed up to 10 6 m 3 of ice‐rich permafrost. The widespread development of these large thaw slumps (up to 40 ha area with headwalls of up to 25 m height) and associated debris flows drive distinct patterns of stream sediment and solute flux that are evident across a range of watershed scales. Suspended sediment and solute concentrations in impacted streams were several orders of magnitude greater than in unaffected streams. In summer, slump impacted streams displayed diurnal fluctuations in water levels and solute and sediment flux driven entirely by ground‐ice thaw. Turbidity in these streams varied diurnally by up to an order of magnitude and followed the patterns of net radiation and ground‐ice ablation in mega slumps. These diurnal patterns were discernible at the 10 3 km 2 catchment scale, and regional disturbance inventories indicate that hundreds of watersheds are already influenced by slumping. The broad scale impacts of accelerated slumping are indicated by a significant increase in solute concentrations in the Peel River (70,000 km 2 ). These observations illustrate the nature and magnitude of hydrogeomorphic changes that can be expected as glaciogenic landscapes underlain by massive ice adjust to a rapidly changing climate.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".