Seasonal and spatial variations in microbial activity at various phylogenetic resolutions at a groundwater – surface water interface
Bibliographic record
Abstract
We investigated the seasonal and spatial variation in activity and density of the metabolically active in situ microbial community (AIMC) at a landfill leachate-impacted groundwater - surface water interface (GSI). A series of AIMC traps were designed and implemented for AIMC sampling and microbial activity and density examinations. Measurements were made not only at the level of bacterial domain but also at the levels of alphaproteobacterial Rhizobiales order and gammaproteobacterial Pseudomonas genus, both of which included a large number of iron-oxidizing bacteria as revealed from previous analysis. Consistently higher microbial activities with less variation in depth were measured in the AIMC traps than in the ambient sediments. Flood disturbance appeared to control AIMC activity distributions at the gradually elevated GSI. The highest AIMC activities were generally obtained from locations closest to the free surface water boundary except during the dry season when microbial activities were similar across the entire GSI. A clone library of AIMC 16S rRNA genes was constructed, and it confirmed the predominant role of the targeted alphaproteobacterial group in AIMC activity and composition. This taxon constituted 2%-14% of all bacteria with similar activity distribution profiles. The Pseudomonas group occupied only 0.1‰-0.5‰ of the total bacterial density, but its activity was 27 times higher than the bacterial average. Of the 16S rRNA sequences in the AIMC clone library, 7.5% were phylogenetically related to putative IOB, supporting the occurrence and persistence of active microbial iron oxidation across the studied iron-rich GSI ecosystem.
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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 | 0.001 | 0.001 |
| 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 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".