Characterisation of the Carpinus betulus L. Phyllomicrobiome in Urban and Forest Areas
Bibliographic record
Abstract
Urban green areas are highly valued by citizens for their contribution to the quality of life in cities. Plants play an important role in mitigating airborne pollutants, and are assisted in this role by the metabolic capacities of the millions of microbial cells that colonise leaf surfaces (phyllosphere). Many factors influence phyllosphere microbial community composition and function, but to what extent does airborne pollution in cities impact the composition of microbial communities and their functional degradation genes? Here we describe the characterisation of the phyllospheric bacterial communities of Carpinus betulus L. trees (hornbeam) across three locations: the city centre of Warsaw (Poland), a forest in a UNESCO World Heritage site (Białowieża), and a forest in one of the world’s oldest operational oil fields (Bóbrka). C. betulus contained higher particulate matter (PM) concentrations, with higher concentrations of palladium and radon in the PM, on leaves in Warsaw than in the forests. Volatile organic compound (VOC) analyses of sampled air revealed higher concentrations of butanone methyl propanal, butylbenzene and cyclohexane in Bóbrka than Warsaw and Białowieża, while in Warsaw, xylene and toluene were higher. Shotgun microbiome sequencing uncovered a dominance of Gammaproteobacteria (71 %), mainly Pseudomonas spp., Actinobacteria, Alpha- and Beta-proteobacteria and Firmicutes. Community composition and function differed significantly between the forests and Warsaw city center. Statistically more hydrocarbon degradation genes were found in Białowieża compared to Warsaw and Bóbrka, and in vitro tests of diesel degradation and plant growth promotion traits of culturable representatives revealed that Białowieża held the highest number of bacteria with plant beneficial properties and degradation genes.This study provides the first detailed insights into the microbiome of C. betulus, and sets the stage for developing to a more integrated understanding of phyllosphere microbiota in cities, and their relationships with human health.
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) | 0.000 | 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 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".