Higher seasonal variation of actinobacterial communities than spatial heterogeneity in the surface sediments of Taihu Lake, China
Bibliographic record
Abstract
Much more attention has been paid to the actinobacterial community in soils or water columns of aquatic habitats. However, there are few studies on their composition and diversity in lake sediments. Here, we used denaturing gradient gel electrophoresis and clone libraries of partial 16S rRNA gene to study the spatial variations of actinobacterial communities across 4 seasons in the surface sediments of the shallow, subtropical Taihu Lake. Cluster analysis based on fingerprints showed clear spatiotemporal variations of actinobacterial communities and higher seasonal variation than spatial heterogeneity. Based on clone libraries, this pattern was supported by the principal coordinates analysis in the phylogenetic context and by detrended correspondence analysis on the operational taxonomic unit table. Additionally, phylogenetic analysis showed that the putative freshwater-specific actinobacterial lineages (e.g., acI) were also detected in the lake sediments, which suggests that these subclusters may also adapt to the sediment environments. Summarily, our results suggested that actinobacterial communities of the surface sediments were more affected by seasonal variation than spatial heterogeneity in the intrahabitat of Taihu Lake.
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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 | 0.001 | 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".