Incorporating citizen science, museum specimens, and field work into the assessment of extinction risk of the American Bumble bee (Bombus pensylvanicus De Geer 1773) in Canada
Bibliographic record
Abstract
Many Bumble bee ( Bombus ) species are in decline and conservation efforts must be undertaken now to lessen or reverse the trend. For effective efforts to occur, the first step must be an accurate assessment of extinction risk. Yet only four of over forty Canadian Bombus species have been assessed by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC), despite evidence of decline for numerous species in this genus. Here, we evaluated the status of the American Bumble bee, Bombus pensylvanicus De Geer 1773 in Canada. A challenge with species assessments is obtaining adequate occurrence data temporally and spatially. Citizen science is a field where volunteers can collect data similar to that of experts over a broader coverage than researchers could often cover alone. We used data from the Bumble Bee Watch citizen science program, a database of North American Bombus records representing field survey and collection records from the late-1800s, and our own field surveys to evaluate the status of B. pensylvanicus in Canada using the International Union for the Conservation of Nature (IUCN) Red List assessment criteria. We found that B. pensylvanicus ’ Area of Occurrence has decreased by about 70%, its Extent of Occurrence by 37%, and its relative abundance by 89%, from 2007 to 2016 as compared to 1907–2006. These findings warrant an assessment of Critically Endangered using IUCN Red List criteria for B. pensylvanicus in Canada. Our findings will help inform management of B. pensylvanicus and exemplify the importance of citizen science programs for wildlife conservation.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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 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".