Signature bioacoustique, distribution et abondance des poissons pélagiques et des mammifères marins en mer de Beaufort (Arctique canadien) : une réponse à l’énigme de la morue arctique manquante
Bibliographic record
Abstract
The Canadian Beaufort Sea faces the double pressure of climate change and increasing industrial activities.Despite the importance of the marine ecosystem of the region for local communities, some of its components remain poorly documented, in particular the distribution and abundance of pelagic fish and marine mammals.This thesis is based on hydroacoustic, net, and trawl datasets collected from 2006 to 2014 and documents the acoustic signature of pelagic fish and marine mammals to, ultimately, estimate their abundance and distribution more accurately.I study and discuss: (1) the vertical distribution and ontogenic migrations of pelagic fish over the annual cycle; (2) the spatial distribution and recruitment of pelagic fish in relation with the date of the ice breakup and sea-surface temperatures; and (3) Target Strengths and echotraces of the main marine mammal species.Arctic cod (Boreogadus saida) formed 95% of the pelagic fish assemblage and age-1+ individuals remained over the slope, in the Pacific Halocline and the Atlantic Layer (>100 m), throughout the year.In contrast, age-0 arctic cod colonized the epipelagic layer (<100 m) from hatching in spring until their descent to depth during fall.The abundance and biomass of arctic cod measured acoustically was significantly higher in southern Beaufort Sea and the Amundsen Gulf than in northern areas.Larval growth and recruitment increased during years with an early ice breakup and warmer seasurface temperatures in spring.The stock of pelagic arctic cod was generally high enough to support the energetic requirements of the main marine mammal species.However, they likely had to dive deeper to feed on large (>10 cm) bottom-dwelling arctic cod when the pelagic stock diminished.The acoustic signature of whales and seals documented here could be used to complement visual surveys with scientific sonars and echosounders.The occurrence of false positives, however, limits the use of these instruments under their current form and recommendations are provided to improve the efficiency of active acoustic monitoring at detecting marine mammals.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".