Evaluating the Efficacy of Trawl Exclusion Zones by Estimating Local Atka Mackerel Abundance and Movement Patterns in the Central and Eastern Aleutian Islands
Bibliographic record
Abstract
Abstract Atka Mackerel Pleurogrammus monopterygius is the most abundant commercially exploited groundfish in the Aleutian Islands, Alaska. It is also the predominant prey of the endangered Steller sea lion Eumetopias jubatus in the Aleutians Islands range. In 1992, trawl exclusion zones (TEZs) that ranged from 10 to 20 nautical miles were established around rookeries to protect Steller sea lion prey abundance. This study examined the efficacy of the TEZs by estimating the movement and local abundance (10–20 nautical miles) of Atka Mackerel inside and outside of these zones using an integrated tagging model that incorporated independent data for tagging survival, recruitment, and tag reporting rates. Atka Mackerel were tagged, released, and recovered from 2000 to 2006 at four Aleutian Island locales, from both inside and outside of the TEZs. Atka Mackerel local abundance and their movement patterns across these harvest boundaries were estimated for all the study areas inside and outside the TEZs, and local exploitation rate by the fishery was calculated for each area open to fishing outside the TEZ boundary. In areas with high Atka Mackerel abundance and little movement from inside to outside the protection zones (e.g., Seguam Pass and Kiska Island), the TEZs were expected to work well to preserve the prey field for Steller sea lions. In areas of low Atka Mackerel abundance and frequent movement from the inside to the outside of the protection zone (e.g., Amchitka Island), the TEZs were expected to be less effective. Our study indicated that TEZs can be effective for preserving prey fields of Atka Mackerel for Steller sea lions, but each study area needs to be carefully evaluated in order to understand area-specific variations in abundance and movement patterns. Received October 21, 2014; accepted December 16, 2015
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".