Mineral dust emissions from proglacial valleys of western Canada: Historical and future dynamics
Bibliographic record
Abstract
Abstract Proglacial valleys of the St. Elias Mountains in western Canada are major sources of historical mineral dust emissions, as evidenced through loess records, yet no estimates of contemporary emissions exist for this region. In these landscapes, dust emissions occur at the interface of glaciofluvial and aeolian processes, not only subject to large seasonal‐annual variability but facing major near‐future changes following rapid deglaciation. We present a camera‐derived observational record of dust emission activity in the A'ą̈y Chù (Yukon, Canada; 60.94°N 138.63°W) and adjacent proglacial valleys between 2016 and 2022, immediately following a major glacial drainage reorganisation. In the A'ą̈y Chù valley, we observe between 57 and 99 days of dust activity per year. Using Landsat 5–8 and MODIS retrievals, long‐term variability in water, snow cover and NDVI was constrained from 1984 to 2023. Across four proglacial valleys, we identify 77.6 km 2 of erodible area (58% of watercourse area), prone to frequent transient meltwater inundation, exposure and potential deflation of glacigenic sediments. Significant variability in seasonal surface erodibility exists between valleys, made notable following the migration of sediment stores into adjacent valleys prone to prolonged snow cover. Ongoing glacier recession and warming climates are anticipated to yield a transient increase in erodible area, and likely dust emissions, in the region over the next several decades. The subsequent decline is anticipated with further deglaciation and the continuing paraglacial transition of proglacial landscapes. A conceptual model is presented to this effect. Understanding contemporary dust emission sources, emission activity and near‐future changes in emission dynamics is critical to establish the role regional mineral dust emissions will occupy in local climatic forcing over the coming decades.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".