Migrations and harvest rates of Arctic charr <i>(Salvelinus alpinus)</i> in a marine protected area
Bibliographic record
Abstract
ABSTRACT Arctic charr are a particularly important species in Arctic and sub‐Arctic regions and face conservation challenges including human exploitation. Arctic charr migration pattern and harvest rate in the Gilbert Bay Marine Protected Area in southern Labrador, Canada were examined. The marine movements of Arctic charr tagged with sonic transmitters were studied using an array of moored data logging ultrasonic receivers in Gilbert Bay and nearby Alexis Bay. During subsistence gillnet fisheries conducted inside and outside the MPA 38% (8 of 21) of the tagged Arctic charr were recaptured. Surviving fish spent 7–8 weeks in the marine environment near coastal areas, often outside existing MPA boundaries. They then returned from these feeding areas to the Shinneys River in Gilbert Bay, a distance up to 25 km, during a 10 day period by directed and rapid movements. This study provides the first information on the extent and timing of Arctic charr marine migrations in southern Labrador, and it identifies a potentially high rate of fishing mortality. The Gilbert Bay Marine Protected Area could provide more protection to the local Arctic charr population were MPA regulations applied to this species. Copyright © Her Majesty the Queen in Right of Canada 2012
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".