Conservation insights from wild bee genetic studies: Geographic differences, susceptibility to inbreeding, and signs of local adaptation
Bibliographic record
Abstract
Conserving bees are critical both ecologically and economically. Genetic tools are valuable for monitoring these vital pollinators since tracking these small, fast-flying insects by traditional means is difficult. By surveying the current state of the literature, this review discusses how recent advances in landscape genetic and genomic research are elucidating how wild bees respond to anthropogenic threats. Current literature suggests that there may be geographic differences in the vulnerability of bee species to landscape changes. Populations of temperate bee species are becoming more isolated and more genetically depauperate as their landscape becomes more fragmented, but tropical bee species appear unaffected. These differences may be an artifact of historical differences in land-use, or it suggests that different management plans are needed for temperate and tropical bee species. Encouragingly, genetic studies on invasive bee species indicate that low levels of genetic diversity may not lead to rapid extinction in bees as once predicted. Additionally, next-generation sequencing has given researchers the power to identify potential genes under selection, which are likely critical to species' survival in their rapidly changing environment. While genetic studies provide insights into wild bee biology, more studies focusing on a greater phylogenetic and life-history breadth of species are needed. Therefore, caution should be taken when making broad conservation decisions based on the currently few species examined.
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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 | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".