Abundance, Characterization and Diversity of Culturable Anoxygenic Phototrophic Bacteria in Manitoban Marshlands
Bibliographic record
Abstract
Marshes are an important ecosystem, acting as a biodiversity hotspot, a carbon sink and a bioremediation site, breaking down anthropogenic waste such as antibiotics, metals and fertilizers. Due to their participation in these metabolic activities and their capability to contribute to primary productivity, the microorganisms in such habitats have become of interest to investigate. Since Proteobacteria were previously found to be abundant and the waters are well aerated and organic-rich, this study on the presence of anoxygenic phototrophic bacteria, purple non-sulfur bacteria and aerobic anoxygenic phototrophs in marshes was initiated. One sample was collected at each of the seven Manitoban sites, and anoxygenic phototrophs were cultivated and enumerated. A group of 14 strains, which represented the phylogenetic diversity of the isolates, was physiologically investigated further. Aerobic anoxygenic phototrophs and purple non-sulfur bacteria were present at each location, and they belonged to the α- and β-Proteobacteria subphyla. Some were closely related to known heavy metal reducers (Brevundimonas) and xenobiotic decomposers (Novosphingobium and Sphingomonas). All were able to synthesize the photosynthetic complexes aerobically. This research highlights the diversity of and the potential contributions that anoxygenic phototrophs make to the essential functions taking place in wetlands.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.004 | 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 teacher head, 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".