Estimating movement and abundance of Atka mackerel (<i>Pleurogrammus monopterygius</i>) with tag–release–recapture data
Bibliographic record
Abstract
Abstract A mark–recapture experiment was conducted in Seguam Pass, Alaska, to estimate local Atka mackerel ( Pleurogrammus monopterygius ) abundance and to evaluate the efficacy of trawl exclusion zones around Steller sea lion ( Eumetopias jubatus ) rookeries. Atka mackerel were found in dense aggregations near the Aleutian Islands where they are a major prey item of endangered Steller sea lions. In 1999, 1375 tagged fish were released and a biomass of 76 679 metric tonnes (t) was estimated outside a trawl exclusion zone using a simple Petersen model. In 2000, 8773 tagged fish were released and the estimated biomasses were 117 900 t inside and 82 057 t outside the trawl exclusion zones using an integrated tagging model. Movement into the open zone was small after 107 days (0.6%), whereas movement from the open area was potentially large but highly uncertain after 107 days (81%). Our model suggests that trawl exclusion zones in Seguam Pass are effective in separating a large biomass of potential prey for Steller sea lions from the immediate effects of local fisheries. Atka mackerel do not appear to move substantially outside their local aggregations (<70 km), and they show strong habitat preferences within their local home ranges. In one instance, fish released in an area of low Atka mackerel abundance returned to their capture location about 2 miles away. Thus individual Atka mackerel may have an affinity for particular areas within their home range, perhaps resulting from adaptations to local oceanic conditions along the Aleutian Island archipelago.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".