Changes in the Distribution of Atlantic Bluefin Tuna (Thunnus thynnus) in the Gulf of Maine 1979-2005
Bibliographic record
Abstract
The Gulf of Maine, NW Atlantic Ocean, is a productive, seasonal foraging ground for Atlantic bluefin tuna (Thunnus thynnus), but commercial landings of adult size classes were up to 40% below the allocated total allowable catch between 2004 to 2008 for the rod and reel, harpoon, and purse seine categories in the Gulf of Maine. Reduction in Atlantic bluefin tuna catches in the Gulf of Maine could represent a decline in spawning stock biomass, but given wide-ranging, complex migration patterns, and high energetic requirements, an alternative hypothesis is that their dispersal patterns shifted to regions with higher prey abundance or profitability, reducing availability to U.S. fishing fleets. This study fit generalized linear models to Atlantic bluefin tuna landings data collected from fishermen's logbooks (1979-2005) as well as the distances between bluefin tuna schools and Atlantic herring (Clupeaharengus), a primary prey species, to test alternative hypotheses for observed shifts in Atlantic bluefin tuna availability in the Gulf of Maine. For the bluefin model, landings varied by day of year, latitude and longitude. The effect of latitude differed by day of year and the effect of longitude differed by year. The distances between Atlantic bluefin tuna schools and Atlantic herring schools were significantly smaller (p<0.05) than would be expected from a randomly distributed population. A time series of average bluefin tuna school positions was positively correlated with the average number of herring captured per tow on Georges Bank in spring and autumn surveys respectively (p<0.01, r(2)=0.24, p<0.01, r(2)=0.42). Fishermen's logbooks contributed novel spatial and temporal information towards testing these hypotheses for the bluefin tuna fishery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".