Comparative bacterial community analysis in relatively pristine and anthropogenically influenced mangrove ecosystems on the Red Sea
Bibliographic record
Abstract
Mangrove habitats are ecologically important ecosystems that are under severe pressure worldwide because of environmental changes and human activities. In this study, 16S rRNA gene amplicon deep-sequencing was used to compare bacterial communities in Red Sea mangrove ecosystems at anthropogenically influenced coastal sites with those at a relatively pristine island site. In total, 32 phyla were identified from the mangrove rhizospheres, with Proteobacteria predominating at each of the studied sites; however, the relative abundance was significantly decreased at the coastal sites (Mastorah, MG-MS; Ar-Rayis, MG-AR) compared with the pristine island site near Dhahban (MG-DBI). The phyla Actinobacteria, Firmicutes, Acidobacteria, Chloroflexi, Spirochetes, and Planctomycetes were present at a relative abundance of >1% at the MG-MS and MG-AR sites, but their concentration was <1% at the MG-DBI site. A total of 1659 operational taxonomic units (OTUs) were identified at the species level, and approximately 945 OTUs were shared across the different sampling sites. Multivariate principal coordinate data analysis separated the MG-DBI site from the MG-AR and MG-MS cluster. Specific bacterial taxa were enriched at each location, and in particular, the genera Pseudoalteromonas and Cobetia were predominantly identified in the MG-DBI site compared with the anthropogenically influenced coastal sites.
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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 | 0.000 |
| 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".