Plant-microbe interactions in the phyllosphere: facing challenges of the anthropocene
Bibliographic record
Abstract
Abstract Global change is a defining feature of the Anthropocene, the current human-dominated epoch, and poses imminent threats to ecosystem dynamics and services such as plant productivity, biodiversity, and environmental regulation. In this era, terrestrial ecosystems are experiencing perturbations linked to direct habitat modifications as well as indirect effects of global change on species distribution and extreme abiotic conditions. Microorganisms represent an important reservoir of biodiversity that can influence macro-organisms as they face habitat loss, rising atmospheric CO2 concentration, pollution, global warming, and increased frequency of drought. Plant-microbe interactions in the phyllosphere have been shown to support plant growth and increase host resistance to biotic and abiotic stresses. Here, we review how plant-microbe interactions in the phyllosphere can influence host survival and fitness in the context of global change. We highlight evidence that plant-microbe interactions (1) improve urban pollution remediation through the degradation of pollutants such as ultrafine particulate matter, black carbon, and atmospheric hydrocarbons, (2) have contrasting impacts on plant species range shifts through the loss of symbionts or pathogens, and (3) drive plant host adaptation to drought and warming. Finally, we discuss how key community ecology processes could drive plant-microbe interactions facing challenges of the Anthropocene.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".