The influence of forage fish abundance on the aggregation of Gulf of Maine Atlantic cod (<i>Gadus morhua</i>) and their catchability in the fishery
Bibliographic record
Abstract
Shifts in the distribution and aggregation patterns of exploited fish populations can affect the behavior and success of fishermen and can complicate the interpretation of fisheries-dependent data. Starting in 2006, coinciding with an increase in sand lance (Ammodytes spp.) abundance, Gulf of Maine Atlantic cod (Gadus morhua) concentrated on Stellwagen Bank, a small (405 km2) underwater plateau located in the southwestern portion of the larger (52 461 km2) stock area. The cod fishery in turn concentrated on Stellwagen Bank. Specifically, the proportion of Gulf of Maine cod landings caught in a single 10-minute square area (260 km2) encompassing the tip of Stellwagen Bank increased from 12% in 2005 to 45% in 2010. An increase in landings per unit effort in the fishery coincided with the concentration of the fleet on Stellwagen Bank. Overall, both fisheries-independent and fisheries-dependent data indicate that an increase in sand lance abundance resulted in cod aggregating in a small and predictable area where they were easily caught by the fishery. More broadly, this work illustrates how changes in the distribution patterns of fish and fisherman can decouple trends in abundance and fisheries catch per unit effort.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".