Underestimated input of terrestrial dissolved organic carbon to the ocean
Bibliographic record
Abstract
The contribution of terrestrial dissolved organic matter (DOM) to the ocean has been an enigma for decades. Tracking terrestrial DOM in the ocean has proven challenging due to factors such as the instability of terrestrial biomarkers, indistinguishable carbon isotopes from biogeochemical fractionation, and similar chemical composition between terrestrial and oceanic DOM. Here we show that the terrestrial contribution to oceanic organic carbon pools is 2 to 3 times higher than previously assumed, highlighting the need to adjust global carbon cycle models. We derive these estimates by bridging high-performance liquid chromatography with ultra-high resolution mass spectrometry to investigate the presence of terrestrial molecules that are transported from rivers to the ocean and estimate their contribution to oceanic DOM. We identified 269 molecular formulae that are likely transported from land to the ocean. These formulae exhibited resistance to biological and photochemical degradation in incubation experiments, and were widely distributed in global rivers, marginal seas and open oceans, suggesting that they are ubiquitous in inland and ocean waters and have a similar source. By relating the abundances of terrestrially derived molecular formulae to dissolved organic carbon concentrations, we estimated that a mean of 21.7 (16.7-25.0)% of oceanic DOM is likely derived from rivers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".