Sulfur isotope fractionation derived from reaction-transport modelling in the Eastern Equatorial Pacific
Bibliographic record
Abstract
Microbial sulfate reduction in subseafloor sediments regulates a significant portion of the marine organic matter burial flux. Over secular timescales, sulfate reduction is the fundamental process connecting the biogeochemical cycles of sulfur, carbon, oxygen and phosphorus. Similar to carbon reduction, sulfate reduction is associated with a strong isotope fractionation process that allows us to track this process through time. It depends on a variety of factors and it has been argued previously that systematic differences between shallow and deep-sea environments might explain secular changes in the marine S-isotope ratio. However, observational data of in situ fractionation from deep-sea areas are scarce. Here we use a reaction-transport model to analyse the S-isotope fractionation during microbial sulfate reduction in the interstitial water of Ocean Drilling Program (ODP) Site 1226 (Leg 201). We find that the upper 100 m below seafloor are best explained with fractionation around −76‰, whereas below this depth the degree of fractionation drops to around −42‰. We propose that this shift is caused by changes in the ratio of the rate of microbial sulfate reduction relative to the rate of abiotic sulfide oxidation. Because large parts of deep oceans are characterized by exceedingly low sulfate reduction rates, this process may be widespread and possibly explain why pyrite S-isotope data suggest that the average S-isotope fractionation is around −50‰, rather than the theoretically predicted value below −70‰. Supplementary material: Supplementary figures and model results are available at https://doi.org/10.6084/m9.figshare.c.5976772 Thematic collection: This article is part of the Sulfur in the Earth system collection available at: https://www.lyellcollection.org/cc/sulfur-in-the-earth-system
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".