Mass wasting and coastal erosion on Yukon Coast and Herschel Island
Bibliographic record
Abstract
Erosion rates along permafrost coastlines are among the fastest in the world, despite the fact that they are only ice free for 3-4 months of the year. Yearly coastal erosion rates of up to 20 m were recorded along ice rich and unconsolidated coasts of the Beaufort and Laptev Sea. Coastal erosion can thus cause rapid land loss and release large amounts sediments, which can alter near-shore ecosystems. Mass-wasting processes such as active-layer detachments, retrogressive thaw slumping and block failures frequently occur along the coasts of Yukon Coastal Plain and Herschel Island. They can significantly impact coastal dynamics and sediment delivery on the shore. \n \nIn our study we use high resolution digital elevation models (DEMs) to observe short term coastal erosion along Yukon Coast and Herschel Island. DEMs were acquired from LIDAR surveys during the AIRMETH campaigns in 2012 and 2013. The DEMs were processed to obtain a horizontal resolution of 1 meter and compared to identify erosion and accumulation events. \n \nOur results show that erosion behaviour is simple and relatively linear at low-elevation coasts (up to 10 m height), where we recorded yearly coastline retreat from 0 to 20 m. Coastal erosion behaviour becomes diverse and slower at higher-elevation coasts, where mass-wasting processes are more active. Among these mass-wasting processes, retrogressive thaw slumping is particularly important. Activated material can be accumulated at the slump outlets or can be transported along the coast by longshore drift. Such material accumulations caused up to 42 m of coastline progradation. Significant accumulation events were identified also due to block failures (up to 20 m of coastline progradation). Although they are generally short-lived features, they can occur frequently and can influence coastline digitalisations. Coastline observations are therefore not indicating the volume loss that is occurring due to mass wasting. We observe discrepancy between planimetric (coastline movement) and volumetric (recorded by DEMs) coastal erosion on Herschel Island. Exploring the relationship between both measures of coastal erosion would enable better estimates of released sediments from the coasts characterised by mass wasting.
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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 | 0.001 |
| 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) | 0.001 | 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".