Impacts of different salinities on bacterial biofilm communities in fresh water
Bibliographic record
Abstract
Natural and anthropogenic salinization continuously impacts inland aquatic ecosystems. Associated bacterial biofilms respond rapidly to environmental conditions and are potential bioindicators for changes in water quality. This study evaluates the effects of different salinity concentrations (0.3‰-10‰) on bacterial biofilms communities grown in fresh water from Lake Bosten. Bacterial communities associated with biofilms were analyzed using terminal restriction fragment length polymorphism and clone library analyses of 16S rRNA genes. Results indicated that the attached bacterial community composition (ABCC) changed over several weeks of biofilm growth, but all followed similar bacterial successional trends in the different salinity groups. Detailed analysis showed the following. (i) ABCC did not differ (P > 0.05) in the low-salinity groups (0.3‰-3.5‰), which may be related to the lower osmotic pressure and the shorter time scale (weeks) of their present habitats. (ii) There were significant differences between the oligosaline (3.5‰) and saline (10‰) groups (P < 0.05). In particular, genus Flavobacterium became dominant in attached bacterial communities in the saline groups. The higher abundance of genus Flavobacterium was possibly due to the biological and metabolic characteristics of the bacteria. (iii) Some bacterial taxa can maintain the higher abundance within attached bacteria in the entire process of biofilms growth, such as the genera Hydrogenophaga and Methyloversatilis in Betaproteobacteria and the family Sphingomonadaceae in Alphaproteobacteria. These data suggested that the bacterial successional trends within biofilms seem almost unaffected by salinity (0.3‰-10‰), but ABCC in saline groups (10‰) are notably changed.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".