Linking bacterial diversity to floral identity in the bumble bee pollen basket
Bibliographic record
Abstract
Abstract Multitrophic interactions are ubiquitous in nature and form the basis of biodiversity. For example, bumble bees visit flowers to collect pollen, on which a variety of bacteria exist. Such bacteria consist of pathogens and mutualists and therefore have consequences for bumble bee colony fitness. However, we still know little about how plant diversity and floral selection by bees translate into the bacterial diversity and composition on the pollen consumed by important pollinators. The aim of this study was to characterize the bacterial and floral alpha and beta diversity from bumble bee corbicula (pollen baskets), identify core communities, and characterize their functional role. We found that bacterial alpha diversity (i.e., the diversity of bacteria determined from the pollen basket of a single bumble bee) was positively correlated with floral pollen alpha diversity (i.e., the diversity of plants from that same pollen basket). Bacterial beta diversity (i.e., bacterial composition) was generally weakly correlated with pollen beta diversity (i.e., floral composition). The abundance of some bacterial genera and pollen families was correlated, specifically Lactobacillus and Acinetobacter were positively correlated with Asteraceae pollen and negatively correlated with Lamiaceae pollen. The most widespread bacteria (the “core OTU”) in bumble bee pollen baskets included both possibly beneficial ( Lactobacillus ) and potentially pathogenic ( Pseudomonas ) taxa, but more core OTU functions were unknown vs. known for bumble bees, illustrating the importance of understanding bee–flower–microbe relationships in natural settings.
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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 | 0.001 |
| 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".