Iron coatings on carbonate rocks shape the attached bacterial aquifer community
Bibliographic record
Abstract
Most studies of groundwater ecosystems target planktonic microbes, which are easily obtained via water samples. In contrast, little is known about the diversity and function of microbes adhering to rock surfaces, particularly to consolidated rocks. To investigate microbial attachment to rock surfaces, we incubated rock chips from fractured aquifers in limestone-mudstone alternations in bioreactors fed with groundwater from two wells representing oxic and anoxic conditions. Half of the chips were coated with iron oxides, representing common secondary mineralization in fractured rock. Our time-series analysis showed bacteria colonizing the chips within two days, reaching cell numbers up to 4.16 × 105 cells/mm2 after 44 days. Scanning electron microscopy analyses revealed extensive colonization but no multi-layered biofilms, with chips from oxic bioreactors more densely colonized than from anoxic ones. Estimated attached-to-planktonic cell ratios yielded values of up to 106: 1 and 103: 1, for oxic and anoxic aquifers, respectively. We identified distinct attached and planktonic communities with an overlap between 17 % and 42 %. Oxic bioreactors were dominated by proteobacterial genera Aquabacterium and Rhodoferax, while Rheinheimera and Simplicispira were the key players of anoxic bioreactors. Motility, attachment, and biofilm formation traits were predicted in major genera based on groundwater metagenome-assembled genomes and reference genomes. Early rock colonizers appeared to be facultative autotrophs, capable of fixing CO2 to synthesize biomass and a biofilm matrix. Late colonizers were predicted to possess biofilm degrading enzymes such as beta-glucosidase, beta-galactosidase, amylases. Fe-coated chips of both bioreactors featured more potential iron reducers and oxidizers than bare rock chips. As secondary minerals can also serve as energy source, they might favor primary production and thus contribute to subsurface ecosystem services like carbon fixation. Since most subsurface microbes seem to be attached, their contribution to ecosystem services should be considered in future studies.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".