Population structure and management of Albacore tuna (Thunnus alalunga) in the North Atlantic Ocean) in the North Atlantic Ocean
Bibliographic record
Abstract
Albacore tuna (Thunnus alalunga) is a globally important species found in the tropical and temperate zones of every ocean including the Mediterranean Sea. The aim of this research is to advance the current knowledge concerning the population structure of albacore tuna in the North Atlantic Ocean as well as to improve fishery-dependent estimates of its relative abundance using vessel monitoring data from the Irish mid-water pair trawl fleet. The population structure was investigated at both a local and regional scale. At the local scale, otoliths from juveniles caught within the Bay of Biscay and off its western shelf were examined in order to determine their stock structure using otolith shape analysis. Results from the study revealed significant differences in otolith shape between the two areas. At the regional scale, otolith microchemistry and microstructure analyses were conducted on otoliths from juveniles, caught in and around the Bay of Biscay, and from adults collected in the offshore fisheries of Canada and Venezuela to determine if they shared similar larval or pre-juvenile habitats. The study revealed, based on the microchemistry analysis of the larval core, that there may be more than one spawning location in the North Atlantic for albacore tuna. The final study investigated the use of fishery-dependent data to derive indices of abundance. Vessel monitoring systems (VMS) data from the Irish pair trawl fishery were used to identify fishing pairs targeting albacore tuna from 2006-2016. A hidden semi-Markov model was used to infer fishing effort from VMS data. The impact of using fishing effort instead of days at sea was also compared using CPUE standardisation models. The results showed that hidden semi-Markov models are efficient at inferring fishing effort and that using VMS data to describe fleet behaviour can improve catch rate standardisation for albacore tuna.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".