Bridging the Gap: Nearshore zones as key mediators in Arctic land-ocean carbon fluxes
Bibliographic record
Abstract
The Arctic is experiencing rapid warming, leading to prolonged ice-free periods, increased storm activity, and intensified coastal erosion. These changes release organic matter-rich permafrost into the nearshore marine environment, where it either degrades to CO₂ or is transported further for potential burial on the continental shelf. However, only 5% of all sediment samples in the Arctic Ocean have been collected from the nearshore zone (depths shallower than 10 meters), suggesting that this zone has been significantly under-sampled and understudied in the global carbon cycle and along the land-ocean continuum. This study addresses this gap by investigating OC redistribution and transformation in the nearshore zone of the Canadian Beaufort Sea coast.We collected sediment samples from five locations adjacent to eroding permafrost coasts along the Canadian Beaufort Sea coast across two shallow zones: the surf zone (0–2 m depth) and the nearshore zone (2–5 m depth). Additional samples included four shelf sediments (30–55 m depth), a sediment trap (2.2 m depth), and surface water samples. The samples were hydrodynamically fractionated (into low and high density with cutoff of 1.8 g/cm³; and subsequently size-fractionated) and analysed for their carbon (C), nitrogen (N), and δ¹³C content. We compare our results with an earlier study that characterized eroding permafrost coastal material. Our findings indicate that in eroding permafrost, the majority of OC is stored in the LD and HD63 μm fractions, which contribute up to 39±23% and 28±18% of total OC, respectively, while the LD fraction accounts for only 19±24%. In slightly deeper nearshore waters (2–5 m depth), OC distribution shifts, with a larger fraction in HD63 μm (27±26%), and the LD fraction increasing to 28±18%. On the inner shelf, OC distribution undergoes a clear shift, with the HD
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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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".