Comparing sediment bacterial communities in the macrophyte-dominated and algae-dominated areas of eutrophic Lake Taihu, China
Bibliographic record
Abstract
Bacterial community structure and the effects of several environmental factors on bacterial community distribution were investigated in the sediment of the macrophyte-dominated and algae-dominated areas in a large, shallow, eutrophic freshwater lake (Lake Taihu, China). Surface sediment samples were collected at 6 sampling sites (3 sites from each of the 2 areas) on 15 February and 15 August 2009. Based on cluster analysis of the DGGE banding patterns, there were significant seasonal variations in the structure of the sediment bacterial community in the macrophyte- and algae-dominated areas, and site-specific variation within an area and between 2 areas. However, there were no significant between-area variations due to the large within-area variation. Analysis of DNA sequences showed that there were differences in the species composition of the sediment bacteria between the macrophyte- and algae-dominated area clone libraries. In the macrophyte-dominated area library, the bacterial community was dominated by Deltaproteobacteria, Verrucomicrobia, Acidobacteria, Bacteroidetes, Gammaproteobacteria, and Betaproteobacteria. OP10 was found in the library of this area but not in the algae-dominated area library. The algae-dominated area library was dominated by Betaproteobacteria, Deltaproteobacteria, Gammaproteobacteria, and Acidobacteria. Cyanobacteria, Alphaproteobacteria, and Planctomycetes were found in this area library but not in the macrophyte-dominated area library. Canonical correspondence analysis demonstrated that total phosphorus and water temperature were the dominant environmental factors affecting bacterial community composition in the sediment.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".