Active Bacterial Populations and Grazing Impact Revealed by an In Situ Experiment in a Shallow Aquifer
Bibliographic record
Abstract
To elucidate bacterial population dynamics in an aquifer, we attempted to reveal the impact of protozoan grazing on bacterial productivity and community structure by an in situ incubation experiment using a diffusion chamber. The abundance and vertical distribution of bacteria and protozoa in the aquifer were revealed using wells that were drilled in a sedimentary rock system in Itako, Ibaraki, Japan. The water column in the wells possessed aerobic and anaerobic layers. Active bacterial populations under the grazing pressure of protozoa were revealed through in situ incubation with grazer eliminating experiment by the filtration. On August 19, 2003, the total number of bacteria (TDC) decreased from 1.5 × 106 cells ml− 1 at 2.2 m depth to 3.0 × 105 cells ml− 1 at 10 m depth. The relative contribution of the domain Bacteria to TDC ranged between 63% and 84%. Protozoa existed at a density of 4.2 × 104 to 1.9 × 105 cells ml− 1 in both aerobic and microaerobic conditions. A grazing elimination experiment in situ for 6 days brought about clearly different bacterial community profiles between the 2.2 m and 10 m samples. The bacterial composition of the initial community was predominantly β- and γ -proteobacteria at 2.2 m, while at 10 m β-, α - and γ -proteobacteria represented 56%, 26% and 13% of the community, respectively. The distribution of bacterial abundance, community composition and growth rates in the subsurface were influenced by grazing as well as by geochemical factors (dissolved oxygen and concentrations of organic carbon, methane and sulfate). Results of the in situ incubation experiment suggested that protozoan grazing contributes significantly to bacterial population dynamics.
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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) | 0.001 | 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 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".