Data from: Nesting habits influence population genetic structure of a bee living in anthropogenic disturbance
Bibliographic record
Abstract
While most organisms are negatively affected by anthropogenic disturbance, a few species thrive in landscapes altered by humans. Typically, native bees are negatively impacted by anthropogenic environmental change, including habitat alteration and climate change. Here we investigate the population structure of the eastern carpenter bee Xylocopa virginica, a generalist pollinator with a broad geographic range spanning eastern North America. Eastern carpenter bees now nest almost exclusively in human made wooden structures, linking their geographic distribution and population structure to human activities and disturbance. To investigate the population structure of these bees, we sampled females from 16 different populations from across their range. Nine species-specific microsatellite loci showed that almost all populations are genetically distinct, but with high levels of genetic diversity and low levels of inbreeding overall. Broadly speaking, populations clustered into three distinct genetic groups: a Northern group, a Western group, and a Core group. The Northern group had low effective population sizes, decreased genetic variability and the highest levels of inbreeding in the dataset, suggesting that carpenter bees may be expanding their range northward. The Western group was genetically distinct, but lacked signals of a recent range expansion. Climatic data showed that summer and winter temperatures explained a significant amount of the genetic differentiation seen among populations, while precipitation did not. Our results indicate that X. virginica may be one of the rare “anthrophilic” species that thrive in the face of anthropogenic disturbance.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.024 |
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".