Spatial assessment of albatrosses, commercial fisheries, and bycatch incidents on Canada’s Pacific coast
Bibliographic record
Abstract
Fisheries bycatch mortality poses a primary threat to the majority of the world’s 22 albatross species, 15 of which are at risk of extinction. Although quantitative estimates of albatross bycatch are often unavailable due to a relative or total absence of monitoring, spatial overlap between fisheries and albatrosses is often used to estimate the extent of interaction, a proxy for exposure to bycatch, and to inform avoidance and mitigation actions. Using comprehensive records of commercial demersal longline and trap fishing and survey information for albatrosses (black-footed albatross Phoebastria nigripes, Laysan albatross P. immutabilis, short-tailed albatross P. albatrus), the extent of spatial potential interaction was estimated in Canada’s Pacific coast waters and examined across breeding and non-breeding seasons. The distributions of albatrosses and longline and trap fisheries were found to substantially overlap, with potential interaction hotspots concentrated along the continental shelf break. Trap fisheries reported 1 albatross bycatch incident, suggesting that these fisheries are responsible for negligible albatross mortalities. In contrast, >80% of recorded albatross bycatch incidents occurred within 10 km of albatross-longline fisheries hotspot locations, providing evidence that longline-albatross potential interaction hotspots represent actual areas of elevated bycatch mortality risk. Indicative of potential conservation concern, 60% of short-tailed albatross sightings occurred within 10 km, and 93% within 30 km, of longline-albatross potential interaction hotspots. By contributing knowledge regarding albatross-fisheries interactions, in addition to undertaking the first evaluation of albatross-fisheries hotspots with recorded bycatch incidents on Canada’s Pacific coast, this study represents a step towards enhancing albatross conservation through bycatch avoidance and mitigation.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".