Core-satellite populations and seasonality of water meter biofilms in a metropolitan drinking water distribution system
Bibliographic record
Abstract
Drinking water distribution systems (DWDSs) harbor the microorganisms in biofilms and suspended communities, yet the diversity and spatiotemporal distribution have been studied mainly in the suspended communities. This study examined the diversity of biofilms in an urban DWDS, its relationship with suspended communities and its dynamics. The studied DWDS in Urbana, Illinois received conventionally treated and disinfected water sourced from the groundwater. Over a 2-year span, biomass were sampled from household water meters (n=213) and tap water (n=20) to represent biofilm and suspended communities, respectively. A positive correlation between operational taxonomic unit (OTU) abundance and occupancy was observed. Examined under a 'core-satellite' model, the biofilm community comprised 31 core populations that encompassed 76.7% of total 16 S rRNA gene pyrosequences. The biofilm communities shared with the suspended community highly abundant and prevalent OTUs, which related to methano-/methylotrophs (i.e., Methylophilaceae and Methylococcaceae) and aerobic heterotrophs (Sphingomonadaceae and Comamonadaceae), yet differed by specific core populations and lower diversity and evenness. Multivariate tests indicated seasonality as the main contributor to community structure variation. This pattern was resilient to annual change and correlated to the cyclic fluctuations of core populations. The findings of a distinctive biofilm community assemblage and methano-/methyltrophic primary production provide critical insights for developing more targeted water quality monitoring programs and treatment strategies for groundwater-sourced drinking water systems.
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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".