Microbial communities of wild bees and comparative phylogenetics of key bacterial taxa across the bee tree of life
Bibliographic record
Abstract
Recent years have seen a rapidly growing interest in the study of microbiomes across many animals to understand their health and well-being. Within bees, much of this work has focused on managed species of agricultural importance, such as honey bees and bumble bees. However, unmanaged wild bees are also vital to both agricultural and natural systems, and studying their microbial associates is essential to better understand the impacts of microbiomes on bee health. We used metabarcoding based on 16S and ITS1 loci to identify the bacterial and fungal associates of adult bees from 16 species representing a diverse sampling of wild bees common to eastern North America. We measured alpha and beta diversity across these species which span 10 genera and five families. Additionally, we conducted a broad phylogenetic comparison of bacterial communities across bees using previously published 16S datasets, and contrasted these findings with functional and life history traits across the bee tree of life. This study provides expanded insights into the adult microbial associates of wild bees, as well as the broadest investigation to date into patterns of phylogenetic conservation in bacterial communities across a total of 42 species representing the five most diverse bee families.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".