Origin and Persistence of Markings in a Long-Term Photo-Identification Dataset Reveal the Threat of Entanglement for Endangered Northern Bottlenose Whales (Hyperoodon ampullatus)
Bibliographic record
Abstract
Photo-identification methods depend on markings that are stable over time. Using a large dataset of photographs taken over a 31-year period, we evaluate the reliability, rate of change and demographic trends in different mark types on northern bottlenose whales ( Hyperoodon ampullatus ) in the Endangered Scotian Shelf population, and assess the prevalence and severity of anthropogenically caused markings. Only fin notches and back indentations were stable over long timescales, leading to 48% of the overall population being assessed as reliably marked. Males and mature males were found to have higher incidence of most mark types compared to females and juveniles. The proportion of reliably marked individuals increased over time, a trend that should be accounted for in any temporal analysis of population size using mark-recapture methods. An overall increase in marked individuals may reflect the accumulation of scars on an aging population post whaling. Anthropogenic markings, including probable entanglement and propeller-vessel strike scars, occurred at a steady rate over the study period and were observed on 6.6% of the population. The annual gain rate for all injuries associated with anthropogenic interactions was over 5 times the annual potential biological removal (PBR) calculated for the endangered population. As entanglement incidents and propeller-vessel strike injuries are typically undetected in offshore areas, we provide the first minimum estimate of harmful human interactions for northern bottlenose whales. With low observer effort for fisheries across the Canadian Atlantic, photo-identification offers an important line of evidence of the risks faced by this Endangered whale population.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".