Resuspension of Sediment‐Associated <i>Escherichia coli</i> in a Natural Stream
Bibliographic record
Abstract
In this study, a tracer bacteria was used to investigate the resuspension and persistence of sediment-associated bacteria in a small alluvial stream. The study was conducted in Swan Creek, located within the Grand River watershed of Ontario, Canada. A 1.1-m2 section of the bed was seeded with a strain of Escherichia coli resistant to nalidixic acid (E. coli NAR). The survival, transport, and redistribution of the tracer bacteria within a 1.7-km river section downstream of the source cell was assessed for a 2-mo period following the introduction of the tracer bacteria. This study has illustrated that enteric bacteria can survive in bed sediments for up 6 wk and that inactivation of the tracer bacteria resembled typical first-order decay. Critical conditions for resuspension, as well as resuspension rates, of sediment-associated bacteria were determined for several storm events. The critical shear stress for E. coli NAR resuspension in Swan Creek ranged from 1.5 to 1.7 N m(-2), which is comparable with literature values for critical shear stresses for erosion of cohesive sediments. Bacteria resuspension was primarily limited to the rising limb of storm hydrographs implying that a finite supply of sediment-associated bacteria are available for resuspension during individual storm events. The information presented in this paper will further the development of representative microbial water quality models.
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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) | 0.000 | 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".