Spatial aggregations of seabirds and their prey on the continental shelf off SW Vancouver Island
Bibliographic record
Abstract
We investigated the spatial scales at which seabirds aggregate and associate with prey over the continental shelf off southwest Vancouver Island, British Columbia. Bird densities and hydroacoustic measures of prey abundance were recorded in all seasons from 1993 to 1995 from a vessel moving along fixed strip transects (mean distance 93 km; minimum spatial units 250 m). We used the neighbour K analysis to determine the spatial scale (patch radius) and number of birds (crowding) associated with aggregations of birds. Birds were grouped into 3 guilds: divers (dominated by common murres Uria aalge and other alcids), surface-feeders (dominated by California gulls Larus californicus and other gulls) and shearwaters (mainly sooty shearwaters Puffinus griseus). Flying birds occurred in smaller aggregations spread over a wider area than birds on the water. For birds on the water, patch radii were usually 2 to 8 km, and crowding averaged 574, 143 and 50 birds per patch for surface-feeders, shearwaters and divers, respectively. Patch radii showed few significant differences among bird species and guilds, and remained relatively constant throughout the year for most species, despite large seasonal changes in density and mean crowding. Abundance of prey (small schooling fish and euphausiids) was highest in the upper 10 m, declining progressively with deeper depths and showed marked seasonal trends (mean scores 4 to 5x higher in summer than in winter). Significant associations between birds and prey were usually within patch radii of 2 to 8 km. The appropriate scale to map and monitor seabirds and seabird-prey associations, for oil spill assessments and other reasons, would therefore be 1 to 10 km.
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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 | 0.001 | 0.002 |
| 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".