How turbidity currents dictate organic carbon fluxes across river-fed fjords
Bibliographic record
Abstract
The delivery and burial of terrestrial particulate organic carbon (OC) in marine sediments is important to quantify, because this OC is a food resource for benthic communities, and if buried it may lower the concentrations of atmospheric CO 2 over geologic timescales. Analysis of sediment cores has previously shown that fjords are hotspots for OC burial. Fjords can contain complex networks of submarine channels formed by seafloor sediment flows, called turbidity currents. However, the burial efficiency and distribution of OC by turbidity currents in river-fed fjords had not been investigated previously. Here, we determine OC distribution and burial efficiency across a turbidity current system within a fjord, in Bute Inlet (Canada). We show that 60 ± 10 % of the OC supplied by the two river sources, is buried across the fjord surficial (2 m) sediment. The sand-dominated submarine channel and its terminal lobe contain 63 ± 14 % of the annual terrestrial OC burial in the fjord. In contrast, the muddy overbank and distal flat basin settings contain the remaining 37 ± 14 %. OC in the channel, lobe and overbank exclusively comprises terrestrial OC sourced from rivers. When normalized by the fjord’s surface area, at least three times more terrestrial OC is buried in Bute Inlet, compared to the muddy parts of other fjords previously studied. Although the long-term (>100 year) preservation of this OC is still to be fully understood, turbidity currents in fjords appear to be efficient in storing OC supplied by rivers in their near-surface deposits.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".