Incidental catch of seabirds in Newfoundland and Labrador gillnet fisheries, 2001-2003
Bibliographic record
Abstract
Incidental catch of seabirds in gillnet fisheries in Newfoundland and Labrador, Canada, has been identified in several fisheries, but defendable estimates are unavailable. Despite reduced fishing effort in several fisheries, concern remains that catch rates might negatively impact local seabird populations. Based on data sources within Fisheries and Oceans Canada (St. John's, Canada), total numbers of incidentally caught seabirds in nearshore and offshore Newfoundland waters were estimated for the years 2001, 2002 and 2003. Incidental catch rates were derived using net-days as measures of effort, with fishing trips as sampling units. Confidence intervals were estimated using resampling techniques. Most reports originated from the nearshore gillnet fishery for Atlantic cod Gadus morhua, although many birds were captured in other fisheries. The most commonly captured seabirds were murres Uria sp. and shearwaters (genera Calonectris and Puffinus), although other species were also captured in smaller numbers. As many as 2000 to 7000 murres, over 2000 shearwaters (various species), and tens to hundreds of northern fulmars Fulmarus glacialis, gannets Morus bassanus, double-crested cormorants Phalacrocorax auritus, loons (genus Gavia), eider ducks Somateria mollissima, razorbills Alca torda, puffins Fratercula arctica, black guillemots Cepphus grylle and dovekies Alle alle were estimated to have been captured annually in the area during the period 2001 to 2003, although catches varied considerably from year to year. Populations of these species are not presently thought to be declining due to this incidental mortality; however, present catch levels may contribute to limited growth in these populations, and populations might be affected if fishing effort were to increase.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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 teacher head, 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".