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
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 |
| 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 it