Sedimentary pyrite sulfur isotope compositions preserve signatures of the surface microbial mat environment in sediments underlying low‐oxygen cyanobacterial mats
Bibliographic record
Abstract
Abstract The sedimentary pyrite sulfur isotope (δ 34 S) record is an archive of ancient microbial sulfur cycling and environmental conditions. Interpretations of pyrite δ 34 S signatures in sediments deposited in microbial mat ecosystems are based on studies of modern microbial mat porewater sulfide δ 34 S geochemistry. Pyrite δ 34 S values often capture δ 34 S signatures of porewater sulfide at the location of pyrite formation. However, microbial mats are dynamic environments in which biogeochemical cycling shifts vertically on diurnal cycles. Therefore, there is a need to study how the location of pyrite formation impacts pyrite δ 34 S patterns in these dynamic systems. Here, we present diurnal porewater sulfide δ 34 S trends and δ 34 S values of pyrite and iron monosulfides from Middle Island Sinkhole, Lake Huron. The sediment–water interface of this sinkhole hosts a low‐oxygen cyanobacterial mat ecosystem, which serves as a useful location to explore preservation of sedimentary pyrite δ 34 S signatures in early Earth environments. Porewater sulfide δ 34 S values vary by up to ~25‰ throughout the day due to light‐driven changes in surface microbial community activity that propagate downwards, affecting porewater geochemistry as deep as 7.5 cm in the sediment. Progressive consumption of the sulfate reservoir drives δ 34 S variability, instead of variations in average cell‐specific sulfate reduction rates and/or sulfide oxidation at different depths in the sediment. The δ 34 S values of pyrite are similar to porewater sulfide δ 34 S values near the mat surface. We suggest that oxidative sulfur cycling and other microbial activity promote pyrite formation in and immediately adjacent to the microbial mat and that iron geochemistry limits further pyrite formation with depth in the sediment. These results imply that primary δ 34 S signatures of pyrite deposited in organic‐rich, iron‐poor microbial mat environments capture information about microbial sulfur cycling and environmental conditions at the mat surface and are only minimally affected by deeper sedimentary processes during early diagenesis.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".