Cyanobacteria-ferrihydrite aggregates, BIF sedimentation and implications for Archaean- Palaeoproterozoic seawater geochemistry
Bibliographic record
Abstract
Abstract Precambrian banded iron formations (BIFs) are iron- and silica-rich (bio)chemical sediments that are widely believed to have been precipitated by microbial oxidation of dissolved Fe(II). The by-product of these metabolisms – insoluble ferric iron – would have settled through the water column, often as aggregates with the cell biomass. While the mineralogy, composition and physical properties of cell-iron mineral aggregates formed by anaerobic Fe(II)-oxidising photoferrotrophic bacteria have been extensively studied, there are limited studies that characterise cyanobacteria-iron mineral aggregates that formed during oxygenic photosynthesis. This gap in knowledge is important because it impacts sedimentation velocities and the Fe(III) to organic carbon (Corg) ratios in the marine sediment pile. Here, we used a recently introduced approach to precisely measure the sedimentation velocity of cyanobacteria-ferrihydrite aggregates and the Fe(III):Corg ratios of the cyanobacteria-ferrihydrite aggregates over a wide range of pH and initial Fe(II) concentrations under predicted Palaeoproterozoic atmospheric conditions. Our results indicate that it was highly unlikely BIFs formed at pH <7 via chemical oxidation due to the insufficient sedimentation velocity, even at the maximum predicted Fe(II) concentration of 1800 μM with excess oxygen. Instead, large Banded Iron Formation (BIF) deposits, such as those associated with the ca. 2.47 Ga Kuruman Formation in South Africa, would only had been deposited at minimum Fe(II) concentrations of 500 μM at pH 7 or 250 μM at pH 8. The Fe:Corg ratios in cyanobacteria-ferrihydrite sediments formed during initially anoxic Fe(II) oxidation experiments represent the maximum values under each condition because we specifically extracted samples after all Fe(II) was oxidised. The Fe(III) to organic carbon ratio was consistently below 4, which is also the ratio required for dissimilatory Fe(III) reduction (DIR). This result indicates that biomass in this case was in excess, which contradicts the low organic carbon content seen in most BIFs. Thus, we suggest that biomass was either physically separated from ferrihydrite aggregates during sedimentation under the influence of ocean currents and waves, or it was degraded prior to DIR. The mineralogical and geochemical evidences of both oxide and carbonate facies from the Kuruman Iron Formation (IF) suggest that ferrihydrite was most likely the precursor along with a significant initial organic carbon input, supporting the proposed cyanobacterially-mediated BIF depositional model and experimental results.
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 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".