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Record W3186927700 · doi:10.1111/gbi.12466

Sedimentary pyrite sulfur isotope compositions preserve signatures of the surface microbial mat environment in sediments underlying low‐oxygen cyanobacterial mats

2021· article· en· W3186927700 on OpenAlexaff
Maya Gomes, Judith M. Klatt, Gregory J. Dick, Sharon L. Grim, Kathryn Rico, M. Gutiérrez Medina, Wiebke Ziebis, Lauren Kinsman‐Costello, Nathan D. Sheldon, David A. Fike

Bibliographic record

VenueGeobiology · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeochemistry and Elemental Analysis
Canadian institutionsMcGill University
FundersWashington University in St. LouisNational Oceanic and Atmospheric AdministrationNational Science Foundation
KeywordsPyriteMicrobial matGeologySedimentary rockSulfurSedimentGeochemistryIsotopes of oxygenOxygenAlgal matCyanobacteriaEnvironmental chemistryMineralogyChemistryBacteriaGeomorphologyPaleontologyEcologyAlgae

Abstract

fetched live from OpenAlex

Abstract The sedimentary pyrite sulfur isotope (δ34S) record is an archive of ancient microbial sulfur cycling and environmental conditions. Interpretations of pyrite δ34S signatures in sediments deposited in microbial mat ecosystems are based on studies of modern microbial mat porewater sulfide δ34S geochemistry. Pyrite δ34S values often capture δ34S 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 δ34S patterns in these dynamic systems. Here, we present diurnal porewater sulfide δ34S trends and δ34S 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 δ34S signatures in early Earth environments. Porewater sulfide δ34S 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 δ34S variability, instead of variations in average cell‐specific sulfate reduction rates and/or sulfide oxidation at different depths in the sediment. The δ34S values of pyrite are similar to porewater sulfide δ34S 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 δ34S 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.202
Teacher spread0.191 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2021
Admission routes1
Has abstractyes

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