Host ancestry and morphology differentially influence bacterial and fungal community structure of <i>Rhododendron</i> leaves, roots, and soil
Bibliographic record
Abstract
Rhododendron are popular ornamental plants that are well-known for forming mycorrhizal associations with ericoid fungi, but little is known about how host traits influence their microbiome more broadly. This study investigated leaf, root, rhizosphere soil, and bulk soil bacterial and fungal community structure for 12 Rhododendron species, representing four taxonomic clades with different leaf habits. Samples were collected when ephemeral hair roots colonized by ericoid mycorrhizae were absent, and microbial community structure was compared to leaf and root morphology for the same plants. Root morphology and the fungal communities of roots and rhizosphere soil were primarily structured by host ancestry. Leaf bacterial and fungal communities were even more distinct across clades than for roots or rhizosphere, and microbial communities of leaves and bulk soil were similarly structured by clade-wise differences in leaf morphology, suggesting a role for Rhododendron leaf litter in belowground microbial community structure. This work sheds new light on host traits influencing microbial community structure of ericaceous plants, showing a strong influence of ancestry, but also that different host traits drive bacterial and fungal communities across different plant compartments, suggesting future work on factors that drive similarity among close relatives in the non-ericoid microbes associating with Rhododendron.
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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) | 0.001 | 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 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".