Conservation Genetics of a Declining Bumble Bee in Western North America; The Influence of Geography, Dispersal Limitation, and Anthopogenic Activity
Bibliographic record
Abstract
Conservation biology addresses the problem of species loss by identifying species in need of protection. Conservation biology has subfields to address different aspects of biodiversity loss, including genetics and sociology. I used genetic approaches to assess the conservation status of western bumble bees, a bumble bee species of conservation concern. The western bumble bee is a bumble bee species that ranges from Alaska to New Mexico and as far east as Wyoming and Colorado. This species is disappearing in some places. It may soon be listed as endangered in the United States and is already listed as endangered in parts of its Canadian distribution. To complicate the problem further, the western bumble bee might really be two cryptic species. Recent genetic analyses indicate that there might be a northern species (Mckay’s bumble bee) and a southern species (the western bumble bee). I used DNA from specimens collected across the range and ran genetic analyses to estimate the relationships between western bumble bees and Mckay’s bumble bees. This study provided enough evidence to conclude that they are, in fact, two species. Next, I compared patterns of genetic diversity in the two species to environmental variables to determine how the environment influences how the bees to move across the landscape. I compared patterns of genetic diversity in bees that were collected between 1960 through 2020. Western bumble bees showed patterns of slightly decreasing genetic diversity through time from 1960 to 2019, but Mckay’s bumble bee did not. For both species, nighttime temperatures during the spring and proximity to a native fungal parasite were important predictors of differences in genetic diversity among samples. The distance from parasites is probably important because specimens that are near infections are more likely to be infected themselves. Although we found decreases in genetic diversity for western bumble bees, there is still enough genetic diversity in present-day populations for the species to recover if the effects of the drivers of the declines are managed. Finally, I surveyed 974 conservationists from diverse backgrounds to measure their understanding, trust, and motivation to action from conservation genetic studies. This is important because molecular methods provide important insight into the conservation status of at-risk species, but they are not used very often when land managers make conservation decisions. The results indicate that lack of understanding, but not trust, may be a barrier to increased use of molecular methods in conservation actions.
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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 | 0.001 |
| 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) | 0.000 | 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".