Pollen diet, more than geographic distance, shapes provision microbiome composition in two species of cavity-nesting bees
Bibliographic record
Abstract
The microbial composition of stored food can influence its stability and the microbial species consumed by the organism feeding on it. Many bee species store nectar and pollen in provisions constructed to feed developing offspring. Yet, whether microbial composition is determined by the pollen types within provisions, variation between bee species at the same nesting sites, or geographic distance was unclear. Here, we sampled two species of cooccurring cavity nesting bees in the genus Osmia at 13 sites in California and examined the composition of pollen, fungi, and bacteria in provisions. Pollen composition explained 15% of variation in bacterial composition and ∼30% of variation in fungal composition, whereas spatial distance among sites explained minimal additional variation. Symbiotic microbe genera Ascosphaera, Sodalis, and Wolbachia showed contrasting patterns of association with pollen composition, suggesting distinct acquisition and transmission routes for each. Comparing provisions from both bee species comprised of the same pollens points to environmental acquisition rather than bee species as a key factor shaping the early stages of the bee microbiome in Osmia. The patterns we observed also contrast with Apilactobacillus-dominated provision microbiome in other solitary bee species, suggesting variable mechanisms of microbial assembly in stored food among bee species.
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 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 | 0.001 | 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".