Life stage and seasonal habitat use of the porbeagle Lamna nasus in the Northwest Atlantic Ocean
Bibliographic record
Abstract
For highly mobile marine species such as pelagic elasmobranchs, the development of effective spatial management requires a comprehensive understanding of movement ecology. Research incorporating movement data across seasons and life stages, including reproductive states, is valuable for informing spatial management, yet is absent for most species. In the Northwest (NW) Atlantic Ocean (hereafter referred to as NW Atlantic), the porbeagle shark Lamna nasus is a pelagic species that is overfished, has a live retention ban (Canada) or landings regulations (United States), and is also commonly captured incidentally as bycatch. Research on the spatiotemporal dynamics of NW Atlantic porbeagle habitat use is limited, with all previous research utilizing pop-off satellite archival tags that are prone to large uncertainty in location estimates. This study used higher-accuracy fin-mount satellite tags to identify patterns in habitat use across life stages and seasons for porbeagle sharks tagged off the northeastern coast of the United States. During the summer and fall, the 95% kernel density estimate (referred to as “activity space”) of tagged porbeagles occurred almost exclusively on the continental shelf in the Gulf of Maine and Georges Bank. Activity space expanded and shifted southwards to include offshore environments during the winter and spring for juveniles, mature non-gravid females, and mature females of unknown reproductive states, while the activity space of mature males and gravid females remained in shelf waters year-round. This finding differs from the previous assumption that southward migrations are linked to reproduction for NW Atlantic porbeagles. Tagged porbeagles were also found to have a relatively small 50% kernel density estimate (referred to as “high occupancy area”) located around Cape Cod, Massachusetts that was well-conserved across life stages and seasons. This relatively static, small high occupancy area has implications for the population’s conservation given the high amount of fishing activity (rod-and-reel, trawl, gillnet) occurring within this region. Given the overlap between porbeagle high occupancy area and fishing activity, as well as the relatively high recapture rate of tagged sharks (10.5%), the coastal waters around Cape Cod, Massachusetts should be considered for spatial management of the NW Atlantic porbeagle.
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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 | 0.000 |
| 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".