Ambient Air Pollution Shapes Bacterial and Fungal Ivy Leaf Communities
Bibliographic record
Abstract
Ambient air pollution exerts deleterious effects on our environment. Continuously exposed to the atmosphere, diverse communities of microorganisms thrive on leaf surfaces, the phylloplane. The composition of these communities is dynamic, responding to many environmental factors including ambient air pollution. In this field study, over a 2 year period, we sampled Hedera helix (ivy) leaves at six locations exposed to different ambient air pollution conditions. Daily, we monitored ambient black carbon (BC), PM2.5, PM10, nitrogen dioxide, and ozone concentrations and found that ambient air pollution led to a 2–7-fold BC increase on leaves, the phylloplane BC load. Our results further indicated that the phylloplane BC load correlates with the diversity of bacterial and fungal leaf communities, impacting diversity more than seasonal effects. The bacterial genera Novosphingobium, Hymenobacter, and Methylorubrum, and the fungal genus Ampelomyces were indicators for communities exposed to the highest phylloplane BC load. Parallel to this, we present one fungal and two bacterial phylloplane strains isolated from an air-polluted environment able to degrade benzene, toluene, and/or xylene, including a genomics-based description of the degradation pathways involved. The findings of this study suggest that ambient air pollution shapes microbial leaf communities, by affecting diversity and supporting members able to degrade airborne pollutants.
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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 | 0.000 | 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) | 0.000 | 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".