Deep-sea movement patterns of the Patagonian toothfish Dissostichus eleginoides Smitt in the Southwest Atlantic
Bibliographic record
Abstract
Context Knowledge on movement patterns within marine fish populations are essential for understanding key aspects of their biology, distribution and stock structure. Many deep-sea fish species possess complex life-history patterns with distributions occurring across vast areas. The nature of connectivity at different life-history stages in a dynamic Patagonian toothfish population on the Patagonian Shelf, Slope and deep-sea plateau around the Falkland Islands remains speculative. Aims We aimed to elucidate the movement patterns as well as the extent that these are driving connectivity during the adult life-history stages of Patagonian toothfish in the region. Methods A 5+-year tag–recapture program was executed and data were analysed using generalised additive models. Key results The majority of individuals (77.59%) displayed high site fidelity (<50 km), suggesting that seasonal spawning migrations are uncommon. However, 9.91% of individuals undertook large-distance movements across oceanographic and physical boundaries. These were characterised by large (>120 cm) fish inhabiting the slope and deep-sea plains (north of 52°S) undertaking southward (direction = 150–240°) home-range relocations to spawning areas. Conclusions and implications The results provide compelling evidence to a single Patagonian toothfish metapopulation, with important considerations in terms of the spawning stock dynamics, and the development of regional management agreements across their Patagonian distribution.
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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 | 0.000 |
| 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 | 0.000 |
| 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".