The transition from freshwater to marine iron‐oxidizing bacterial lineages along a salinity gradient on the <scp>S</scp> heepscot <scp>R</scp> iver, <scp>M</scp> aine, <scp>USA</scp>
Bibliographic record
Abstract
Oxygen-dependent, neutrophilic iron-oxidizing bacteria (FeOB) are important drivers of iron transformations in marine and freshwater environments. Despite remarkable similarities in physiology and morphotype, known freshwater and marine FeOB are clustered in different classes of Proteobacteria; freshwater FeOB in the Betaproteobacteria and marine FeOB in the Zetaproteobacteria. To determine effects of salinity on these microbes, we examined the mineral biosignatures and molecular ecology of bacteria in FeOB mats collected along an estuarine salinity gradient. Light microscopy and scanning electron microscopy analyses showed the presence of iron oxide stalk and sheath structures in both freshwater and saline iron mats. Results of tagged pyrosequencing, quantitative PCR and fluorescent in situ hybridization, all based on the small subunit rRNA gene, confirmed Zetaproteobacteria were not present in freshwater mats, but were in saline mats at salinities down to 5‰. Among the Betaproteobacteria, Leptothrix spp. were only found in the freshwater mat. Gallionella spp. were limited to freshwater and low salinity mats (< 5‰). Sideroxydans sp. were salt tolerant; however, their relative abundance decreased with increasing salinity. These results suggest salinity is important in shaping the population biology of iron mat communities, and some coexistence between marine and freshwater populations occurs in brackish waters.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".