Contribution of Coastal Retrogressive Thaw Slumps to theNearshore Organic Carbon budget along the Yukon Coast
Bibliographic record
Abstract
Abstract. We describe the evolution of coastal retrogressive thaw slumps (RTSs) between 1952 and 2011 along the Yukon Coast, Canada, and provide the first estimate of the contribution of RTSs to the nearshore organic carbon budget in this area. We 1) monitor the evolution of RTSs during the periods 1952–1972 and 1972–2011; 2) calculate the volume of material eroded and stocks of organic carbon (OC) mobilized through slumping – including soil organic carbon (SOC) and dissolved organic carbon (DOC) – and 3) measure the OC fluxes mobilized through slumping between 1972 and 2011. We identified 15 RTSs using high-resolution satellite imagery from 2011 and geocoded aerial photographs from 1952 and 1972. To estimate the volume of eroded material, we applied a spline interpolation on an airborne LiDAR dataset acquired in July 2013. We inferred the stocks of mobilized SOC and DOC from existing related literature. Our results show a 73 % increase in the number of RTSs between 1952 and 2011. In the study area, RTSs displaced at least 8600 × 103 m3 of material, with 53 % of ice. We estimated that slumping mobilized 81 900 × 103 kg of SOC and 156 × 103 kg of DOC. Since 1972, 17 % of the RTSs 20 have displaced 8.6 × 103 m3/yr of material, with an average OC flux of 82.5 ×103 kg/yr. This flux represents 0.3 % of the OC flux released from coastal retreat; however RTSs have a strong impact on the transformation of OC in the coastal fringe.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".