Potential limits to anthropogenic mortality of small cetaceans in coastal waters of British Columbia
Bibliographic record
Abstract
Small cetaceans are by-caught in salmon gillnet fisheries in British Columbia (BC) waters. In Canada, there is currently no generic calculation to identify when management action is necessary to reduce cetacean bycatch below sustainable limits. We estimated potential anthropogenic mortality limits for harbour ( Phocoena phocoena ) and Dall’s ( Phocoenoides dalli ) porpoises and Pacific white-sided dolphins ( Lagenorhynchus obliquidens ) using quantitative objectives from two well-established frameworks for conservation and management (the United States’ Marine Mammal Protection Act and the Agreement on the Conservation of Small Cetaceans of the Baltic and North Seas), which are similar to some management objectives developed for marine mammal stocks elsewhere in Canada. Limits were calculated as functions of (i) a minimum abundance estimate (2004–2005); (ii) maximum rate of population increase; and (iii) uncertainty factors to account for bias in abundance estimates and uncertainty in mortality estimates. Best estimates of bycatch mortality in 2004 and 2005 exceeded only the most precautionary limits and only for porpoise species. Future research priority should be given to determining small cetacean stock structure in BC and refining species-specific entanglement rates in these and other fisheries. The approach offers a quantitative framework for Canada to meet its stated objectives to maintain favourable conservation status of cetacean populations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".