Integration of multiple metabolic pathways supports high rates of carbon precipitation in living microbialites
Bibliographic record
Abstract
Microbialites are lithifying microbial mats that form multi-layered structures via biological carbon (C) uptake and carbonate precipitation. Here we relate C uptake and precipitation rates to taxonomic diversity and functional capacity of bacterial communities in supratidal freshwater microbialites. Diel assays and analysis of functional gene capacity reveal that photosynthesis is bolstered by light-independent, biological C uptake mechanisms, including biomineralization and chemoautotrophy. Through integration of these mechanisms, microbialites can capture inorganic C over a 24-hour cycle at a rate of 7-12 g C m-2 24 h-1. Notably, up to 87 % of the C taken up is precipitated as inorganic carbon, capturing 2.4 − 4.3 kg C m-2 year-1. Based on observed porosity and laboratory-based accretion rates, this equates to 13-23 mm of vertical calcium carbonate accumulation per year. Hence, contemporary microbialites provide a highly effective biological mechanism to precipitate dissolved CO2 as geologically stable carbonate mineral deposits. Living microbialites achieve high rates of carbon uptake and precipitation by bolstering photosynthesis with light-independent uptake mechanisms to provide an effective biological system to capture CO2 in the geologically stable carbonate, calcite.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".