A new environment for aerobic anoxygenic phototrophic bacteria: biological soil crusts
Bibliographic record
Abstract
Phototrophic microorganisms are critical to the carbon cycling and productivity of biological soil crusts, which enhance water content, nutrient relations and mechanical stability of arid soils. Only oxygen-producing phototrophs, including cyanobacteria and algae, are known from soil crusts, but Earth's second major branch of photosynthetic organisms, the evolutionarily earlier anoxygenic phototrophs, is unreported. We announce the discovery of aerobic anoxygenic phototrophs in three Canadian soil crust communities. We found in a culture-based study that they comprised 0.1-5.9% of the cultivable bacterial community in moss-, lichen- and cyanobacteria-dominated crust from sand dunes and sandy soils. Comparable in density to aerobic phototrophs in other habitats, the bacteriochlorophyll a-possessing pink and orange isolates were related to species of Methylobacterium (99.0-99.5%), Belnapia (97.4-98.8%), Muricoccus (94.4%) and Sphingomonas (96.6-98.5%), based on 16S rRNA gene sequences. Our results demonstrate that proteobacterial anoxygenic phototrophs may be found in dry soil environments, implying desiccation resistance as yet unreported for this group. By utilizing sunlight for part of their energy needs, aerobic phototrophs can accelerate organic carbon cycling in nutrient-poor arid soils. Their effects will be especially important as global climate change enhances soil erosion and consequent nutrient loss.
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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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".