Postglacial Erosional Response of a Permafrost Landscape, Aklavik Range, Arctic Canada
Bibliographic record
Abstract
Rapid warming and permafrost thaw across Arctic landscapes are projected to drastically accelerate local erosion rates and sediment fluxes to downstream systems and the communities that rely on them. However, interpreting this signal of change first requires disentangling the relative contributions of postglacial landscape responses, periglacial processes, and modern warming to observed changes in erosion. To explore this problem, we combine a suite of geochronometers to examine erosion and deposition rates over 102–107 timescales across a periglacial alluvial fan and catchment system on the former margin of the Laurentide Ice Sheet in the Aklavik Range of Northwest Territories, Canada. We use low-temperature thermochronology (apatite fission-track and apatite/zircon (U-Th)/He) to constrain the long-term (~10 Ma) erosion rate of the Aklavik Range at ~0.09 mm/yr. Cosmogenic nuclide (10Be) dating of erratic boulders near the Laurentide glacial limit in the Aklavik Range suggest that the region was last glaciated prior to ~19.6 ka, about 1.1 ka earlier than previously thought. Postglacial fan- and catchment-derived erosion rates (~1-7 mm/year), calculated using mass balance, detrital 10Be concentrations, radiocarbon (14C) geochronology, and optically stimulated luminescence (OSL) dating, exceed background rates by an order of magnitude or more. These results underscore that contributions to observed erosion rates from modern warming must account for persistent postglacial landscape disequilibrium in Arctic ice-marginal settings.
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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 | 0.002 | 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) | 0.001 | 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".