Estimating abundance of Eastern Canada-West Greenland bowhead whales using genetic mark-recapture analyses
Bibliographic record
Abstract
The Eastern Canada-West Greenland (EC-WG) bowhead whale (Balaena mysticetus) population is widely distributed across the eastern Canadian Arctic and across Baffin Bay to the western coast of Greenland. Their vast distribution makes obtaining population estimates via aerial surveys difficult, as coverage over their entire range is not possible. Genetic mark recapture analyses address this issue, as biopsy samples can be collected at various locales across the EC-WG bowhead whale population’s distribution and microsatellites can be analyzed to identify unique individuals. EC-WG bowhead whales were subject to intense commercial whaling pressure between the early 1700 s and early 1900 s, after which a moratorium on commercial whaling was put in place in 1915. We used available genetic samples from EC-WG bowhead whales in mark recapture models to estimate population abundance from 2012 to 2021 to gain insight on population dynamics ∼100 years post commercial whaling. The preferred model, using a Jolly-Seber structure, estimated the total abundance as 5173 individuals (CI: 3436–7788). Since the cessation of commercial whaling, the population has been thought to be rebounding, which is reflected by gradually increasing abundance estimates, from the low hundreds in the 1970 s and 1980 s, to ∼6000 in the early 2000 s, but our present estimate suggests population abundance may be plateauing well below the pre-commercial whaling carrying capacity estimate. This population estimate for EC-WG bowhead whales is required to update the population dynamics for conservation efforts.
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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 | 0.000 |
| 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 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".