Fe, Cu and S isotopes as tracers of microbial reduction in the shale-hosted VMS deposits of the Iberian Pyrite Belt
Bibliographic record
Abstract
This study represents an exploration of the geochemistry of sulphide minerals from prominent shale-hosted volcanogenic massive sulphide deposits of the Iberian Pyrite Belt, including Sotiel-Migollas, Tharsis, Neves Corvo and Lousal using the non-traditional heavy stable isotopes of Fe and Cu along with the S light isotope. Sampling encompassed a diverse range of styles of mineralization, including the dominant fine-grained massive sulphides sometimes exhibiting sedimentary layering, carbonate-rich mounds dominated by sulphides-siderite and formed by the superposition of microbial mats in anoxic bottoms, underlying subseafloor feeder structures (stockworks) and disseminated pyrite within the altered host shales. The δ 56 Fe IRMM-014 values of pyrite exhibit a range from −2.62 to +2.58 ‰, while those of pyrrhotite range from −1.93 to −0.40 ‰. Chalcopyrite δ 65 Cu SRM-976 signature varies between −1.11 and + 0.95 ‰, while the measured δ 34 S V-CDT values fluctuate from −45.0 to +9.4 ‰ in pyrite, −6.8 to +2.1 ‰ in pyrrhotite, and − 10.1 to +6.2 ‰ in chalcopyrite. Notably, pyrite grains within massive sulphides consistently exhibit more negative and variable δ 56 Fe and δ 34 S values than those in the hydrothermally altered host shales (apart from Neves Corvo) and stockworks. These findings strongly imply that the exhalative mineralization incorporated substantial amounts of iron derived from the dissimilatory reduction of aqueous Fe +3 , attributable to low-temperature (<100–120 °C) microbial reduction and contemporaneous with biogenic sulphate reduction. Consequently, Fe in pyrite is likely inherited from both the reduced hydrothermal fluids venting on the seafloor and the microbial reduction of oxidized iron dissolved in ambient seawater. While the microbial influence on Cu isotope signatures is less evident, we infer its potential significance. Superimposed hydrothermal refining during the late percolation of hot hydrothermal fluids reveals a non-biogenic kinetic fractionation, with partial overprinting of the early mineralization and neoformation of sulphides depicting isotopically heavy δ 56 Fe, δ 65 Cu, and δ 34 S signatures that are interpreted as of deep derivation.
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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) | 0.000 | 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".