Permafrost-Related Erosional Effects of Water Level Regulation and Climate Change along the Shorelines of Aishihik and Canyon Lakes, Southwest Yukon
Bibliographic record
Abstract
Lake shoreline erosion is caused by wind-generated waves (mechanical erosion) and, in areas of permafrost, can be compounded by thawing ground ice (thermal erosion). In southwest Yukon, erosion patterns along the shorelines of Aishihik and Canyon Lakes reflect the combined effects of climate change and lake level regulation for hydroelectricity, which began in 1975. An investigation characterizing shoreline erosion and aiming to determine the relative contributions of lake level regulation and climate change was undertaken to support an environmental and socio-economic effects assessment associated with hydroelectric facility relicensing. The investigation involved three phases: (i) compilation and review of pertinent topographic, geological, and hydrological information; (ii) helicopter- and ground-based field reconnaissance; and (iii) mapping of shoreline types, relative severity of erosion and recession from former beaches at select sites. Three types of shorelines were identified based on their distinct responses to lake level regulation and climate change. Type 1 shorelines exhibit a moderate slope of coarse-grained sediment and may contain ice-poor permafrost; they are relatively insensitive to climate change and quickly self-stabilize when exposed to higher lake levels. Type 2 shorelines typically exhibit an abruptly steep embankment of ice-rich, fine-grained sediments; they are vulnerable to recession through long-term retrogressive thaw and slumping in response to climate change and lake level regulation. Type 3 shorelines are typically low-relief and composed of fine-grained, ice-rich sediments; they are most sensitive to higher lake levels due to inundation-induced thaw. Erosion along the Type 2 and Type 3 shorelines of Aishihik and Canyon Lakes appears to be driven primarily by climatic effects, despite an anomalous peak in lake level at the onset of regulation that locally initiated and exacerbated erosion.
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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 | 0.001 |
| 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 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".