Changes in Sedimentary Organic Carbon Compositions in the Mackenzie Trough Over Recent Centuries: Insights Into Permafrost Thawing in the Canadian Arctic
Bibliographic record
Abstract
Abstract This study analyzed three sediment cores (ARA08C/02‐2BC, ARA08C/03‐2BC, and ARA04C‐40MUC) from the Mackenzie Trough in the Beaufort Sea, collected in 2013 and 2017. Using bulk sediment properties (carbon and nitrogen contents, stable carbon isotopes, and radiocarbon isotopes) and terrestrial biomarkers (lignin phenols), we examined the impacts of permafrost thaw on sedimentary organic carbon (OC) in the Canadian Beaufort Sea. Our objective was to investigate whether changes in OC sources reflect the environmental changes documented in the region over the past few decades. At the core site of ARA08C/03‐2BC, we observed an increase in soil‐derived OC accumulation rates (ARs) since the early 20th century, with a noticeable rise over the past few decades, while petrogenic OC ARs showed a slight decline. Grain size end‐member (EM) modeling identified three primary EM groups, revealing a general increase in the proportion of coarse grains (sum of EM2 + EM3 end‐members) since the early 1900s, with a marked acceleration in recent decades. These trends align with regional surface temperature increases over the past few decades, suggesting that permafrost thaw has increasingly affected sedimentary OC dynamics in the Canadian Beaufort Sea. Given climate models that predict accelerated warming in the Mackenzie Basin, our findings highlight the critical need for precise quantification of OC fluxes to improve projections of regional carbon budgets and climate dynamics in the Arctic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| 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".