Abundance estimates of Cetaceans from the 2018 Pacific region international survey of marine megafauna
Bibliographic record
Abstract
Several marine mammal species on the west coast of Canada are reported as bycatch in fisheries. A provision of the United States (US) Marine Mammal Protection Act (MMPA) requires Canada, as an exporter of fish products, to provide population estimates and rates of incidental mortality from fisheries operations. However, abundance estimates in Canadian Pacific waters are lacking for most cetacean species, especially for the offshore areas, or are too old to meet MMPA requirements. The objectives of the Pacific Region International Survey of Marine Megafauna (PRISMM) were to provide recent abundance estimates and distribution data for large marine species in inshore and offshore waters of the Canadian Pacific. The survey was conducted between July 4–September 5, 2018, using two Canadian Coast Guard vessels, and produced a total of 8,400 km of visual effort and resulted in 2,000 sightings of 20 marine mammal species. Using design-based distance sampling methods, new abundance estimates were provided for nine cetacean species in Pacific Canadian waters: 30,117 Dall’s Porpoises (95%CI 22,142–40,965), 12,244 Humpback Whales (8,214–18,252), 7,352 Harbour Porpoises (3,547–15,237), 5,882 Pacific White-sided Dolphins (2,941–11,766), 3,829 Fin Whales (2,145–6,834), 2,207 Northern Right Whale Dolphins (726–6,709), 920 Risso’s Dolphins (178–4,758), 199 Blue Whales (59–670), and 70 Sei Whales (24–209). These estimates are corrected for availability bias based on time-in-view and diving behaviour, but uncorrected for perception bias. Except for Pacific White-sided Dolphins, the 2018 abundance estimates for cetaceans in inshore waters suggests that several populations are stable (Dall’s Porpoises, Harbour Porpoises, Fin Whales) or are continuing to recover from past depletion and are expanding to new areas (Humpback Whales). The return of these predators to habitats from which they were previously extirpated will have important ecosystem-level implications. These coast-wide, updated abundance estimates can also inform Potential Biological Removal limits for anthropogenic mortality.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".