Long-Term Monitoring of Waterborne Pathogens and Microbial Source Tracking Markers in Paired Agricultural Watersheds under Controlled and Conventional Tile Drainage Management
Bibliographic record
Abstract
Surface waters from paired agricultural watersheds under controlled tile drainage (CTD) and uncontrolled tile drainage (UCTD) were monitored over 7 years in order to determine if there was an effect of CTD (imposed during the growing season) on occurrences and loadings of bacterial and viral pathogens, coliphages, and microbial source tracking markers. There were significantly lower occurrences of human, ruminant, and livestock (ruminant plus pig) Bacteroidales markers in the CTD watershed in relation to the UCTD watershed. As for pathogens, there were significantly lower occurrences of Salmonella spp. and Arcobacter spp. in the CTD watershed. There were no instances where there were significantly higher quantitative loadings of any microbial target in the CTD watershed, except for F-specific DNA (F-DNA) and F-RNA coliphages, perhaps as a result of fecal inputs from a hobby farm independent of the drainage practice treatments. There was lower loading of the ruminant marker in the CTD watershed in relation to the UCTD system, and results were significant at the level P = 0.06. The odds of Salmonella spp. occurring increased when a ruminant marker was present relative to when the ruminant marker was absent, yet for Arcobacter spp., the odds of this pathogen occurring significantly decreased when a ruminant marker was present relative to when the ruminant marker was absent (but increased when a wildlife marker was present relative to when the wildlife marker was absent). Interestingly, the odds of norovirus GII (associated with human and swine) occurring in water increased significantly when a ruminant marker was present relative to when a ruminant marker was absent. Overall, this study suggests that fecal pollution from tile-drained fields to stream could be reduced by CTD utilization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".