The link between seawater magnesium concentrations and anhydrite formation in the ocean crust
Bibliographic record
Abstract
Subseafloor hydrothermal systems exert a strong control on the chemical composition of the ocean. Likewise, the chemical composition of the ocean impacts the chemical and physical reactions that happen during hydrothermal circulation, although this has been less well considered. We present a 2D model of basalt alteration under hydrothermal conditions, exploring how changes in major seawater ion concentration over geologic time affect anhydrite (CaSO 4 ) formation in the oceanic crust. Anhydrite precipitation plays a key role in influencing the permeability structure of the ocean crust and acts as a sink for sulfur in the global biogeochemical sulfur cycle, one of the major biogeochemical cycles that regulates Earth’s redox state over geologic time. We develop a fully-coupled 2D reactive transport model to simulate the alteration of fresh mid-ocean ridge basalt by circulating seawater. We verify the model by comparing it to measured vent fluid chemistry and associated alteration mineralogy observed in modern drill cores. We then conduct a series of experiments, systematically changing the chemical composition of seawater to evaluate the impact these changes have on alteration and anhydrite formation. Model results support that the largest controls on the amount of anhydrite precipitation in the oceanic crust are sulfate and calcium concentrations in the ocean, and show that magnesium concentrations exert a strong control on the depth and distribution of anhydrite precipitation. The model results suggest that with the chemistry of certain oceans—in particular low magnesium-calcium ratios and higher magnesium and sulfate concentrations—there may have been significantly shallower anhydrite precipitation, with implications for the permeability structure of the crust and therefore extent of hydrothermal alteration. We suggest that the shallowing of the depth of anhydrite precipitation due to higher magnesium concentrations is via the impact of higher seawater magnesium concentrations on clay formation, which also modulates the pH of fluids during hydrothermal circulation. We speculate that, over Earth’s history, changes in the seawater magnesium, sulfate, and calcium concentrations may have influenced the amount and distribution of anhydrite in hydrothermally altered ocean crust, thus affecting crustal permeability structures, with consequences for key global biogeochemical cycles (e.g. sulfur, calcium).
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".