Plant‐bacteria associations are phylogenetically structured in the phyllosphere
Bibliographic record
Abstract
Determining whether and how global change will lead to novel interactions between hosts and microbes is an important issue in ecology and evolution. Understanding the contribution of host and microbial ecologies and evolutionary histories in driving their contemporary associations is an important step towards addressing this challenge and predicting the fitness consequences of novel associations. Using shotgun metagenomic and amplicon sequencing of bacterial communities from the leaf surfaces (phyllosphere) of trees, we investigated how phylogenetic relatedness among hosts and among their associated bacteria influences the distribution of bacteria among hosts. We also evaluated whether the functional traits of trees and bacteria explained these associations across multiple host species. We show that phylogenetically similar hosts tended to associate with the same bacteria and that phylogenetically similar bacteria tended to associate with the same host species. Phylogenetic interactions between tree and bacterial taxa also explained variation in their associations. The effect of host and symbiont evolutionary histories on bacterial distribution across hosts were observed across phylogenetic scales, but prominently explained variation among higher taxonomic categories of hosts and symbionts. These results suggest that ecological variation arising early in the plant and bacterial phylogenies have been particularly important for driving their contemporary associations. Variation in bacterial functional genes associated with the biosynthesis of aromatic amino acids and compounds and with cell motility were notably important in explaining bacterial community turnover among gymnosperm and angiosperm hosts. Overall, our results suggest an influence of host and bacterial traits and evolutionary histories in driving their contemporary associations.
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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) | 0.001 | 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".