Floral microbes provisioned by <i>Osmia lignaria</i> establish in larval food stores, but do not affect bee development or survival
Bibliographic record
Abstract
Abstract Microbial dispersal and subsequent establishment among linked habitats can be used to examine drivers of community assembly and function. Flowers host microbial communities that can be acquired and vectored by bees to new flowers, establish within the adult bee gut, and enter food stores (e.g., pollen provisions) of developing larvae. Yet, whether microbes vectored by insects or applied for biocontrol can establish across these habitats and if they affect bee fitness remain unknown. Here, we applied microbes to flowers visited by blue orchard bees ( Osmia lignaria ) and compared microbial communities in flowers, adult bee guts, and pollen provisions before and after inoculation to determine microbial establishment, environmental filtering, and overlap across habitat types. We also inoculated provisions with microbes to test their effects on larval survival and development. Experimentally inoculated microbes were detected in all habitats, demonstrating that flowers are a source of microbial acquisition for adult and larval bees. Additionally, larval health was not impacted by microbe supplementation, indicating tolerance of bee larvae to floral microbes in Osmia .
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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) | 0.002 | 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".