Organic Carbon Burial in Global Continental Margin Sediments
Bibliographic record
Abstract
Continental margin sediments are key long-term sinks for atmospheric carbon dioxide (CO₂). Despite their global significance, the magnitude and spatial distribution of organic carbon (OC) burial in this environment remains poorly quantified mainly due to the exceptional heterogeneity of the coastal ocean. Yet, this knowledge is critical not only for closing the global carbon budget but also for guiding policy decisions. Here, we integrate the rapidly growing observational data set with spatial machine learning and inverse as well as forward reaction-transport modelling, capturing the spatial heterogeneity of global continental margins to deliver robust OC flux estimates.We estimate a global continental margin OC burial flux of 441 Tg C yr⁻¹ through the base of the mixed layer, decreasing to 293 Tg C yr⁻¹ at the 1 kyr age horizon (50% is concentrated within the latitudinal band 10°S–30°N. Using the MARgins and CATchments Segmentation framework, tropical regions show the highest OC flux densities and total long-term burial flux globally (5.4 tC km-2 yr⁻¹ and 64 Tg C yr⁻¹). In addition, polar regions and marginal seas also reveal high total long-term burial fluxes (42 Tg C yr⁻1 and 35 Tg C yr⁻¹). In polar regions, high burial is driven by modest OC flux densities over vast areas, while marginal seas exhibit high flux densities but limited spatial extent. Each of the other MARCAT regions contributes less than 15% to global OC burial. We thus find the highest OC burial rates in the Exclusive Economic Zones (EEZs) of Indonesia (27 Tg C yr⁻¹) and Russia (20 Tg C yr⁻¹), followed by the EEZs of the Philipines, Antarctica, the United States, Japan, Papua New Guinea, Canada, New Zealand, Brazil, Yemen, and Mexico (each accounting for 2-5% of global OC burial). The EU EEZs collectively bury approximately as much OC as the Russian EEZ.When combined with global radiocarbon data for organic carbon (OC), our global estimates reveal several hotspots of young, marine-derived OC burial that actively remove contemporary atmospheric CO₂. These regions include tropical margins such as the Sunda Shelf, the Caribbean coastal zones, the western coast of Mexico, and the South China Sea, as well as marginal seas. In contrast, other burial hotspots—such as tropical margins adjacent to large river deltas or the Arctic shelf—predominantly sequester older, pre-aged terrestrial OC and petrogenic OC. While OC burial in these areas has a limited direct impact on contemporary CO₂ levels, it plays a crucial role in the modern carbon cycle by preventing the release of this geological carbon through microbial degradation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".