Aquaculture related humpback whale entanglements in coastal waters of British Columbia from 2008–2021
Bibliographic record
Abstract
Over the past two decades, increasing numbers of humpback whales have been returning to feed in the inshore waters of British Columbia (BC) where marine aquaculture farms are situated. This has led to growing concerns that the presence of aquaculture farms may pose an entanglement threat to humpback whales. However, it is not known whether aquaculture facilities attract humpback whales, or whether there are factors that increase the likelihood of humpback whale, becoming entangled and dying. We examined eight reports of humpback whales interacting with Atlantic salmon farms in BC from 2008 to 2021 to evaluate the conditions that may have contributed to their entanglements. Of the eight entangled humpbacks, three individuals died and five were successfully disentangled and released. All were young animals (1 calf, 7 subadults). Multiple factors were associated with two or more of the reported incidents. These included facility design, environmental features, seasonality, humpback whale age, and feeding behaviour. We found that humpback whales were most commonly entrapped in the predator nets of the aquaculture facilities (6/8 incidents), and were less often entangled in anchor support lines (2/8). The presence of salmon smolts did not appear to be an attractant for humpback whales given that half of the reported entanglements (4/8) occurred at fallowed salmon farms. Almost all of the entanglements (7/8) occurred in late winter (prior to the seasonal return of humpbacks) and during late fall (after most humpbacks have migrated south). Overall, the number of humpback whales impacted by fish farms was small compared to the numbers that return to BC (> 7,000) and accounted for <6% of all types of reported entanglements in BC. Human intervention was required to release humpback whales at fish farms, which points to the need to have well-established protocols to minimize entanglements and maximize successful releases.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".