Mechanisms and consequences of variation in the migratory behaviour of Atlantic cod (Gadus morhua L.) in the northern Gulf of St. Lawrence
Bibliographic record
Abstract
This thesis aimed to characterize individual variation in the migratory behaviour of Atlantic cod (Gadus morhua) in the northern Gulf of St. Lawrence, and to assess the consequences of this variation on the structure and management of the population. First, I reviewed interplays between genetic, environmental, and social factors in the evolution and maintenance of individual variation in the migratory behaviour of marine fishes, with an emphasis on Atlantic cod. Evidence of fine-grained responses to environmental changes suggested that phenotypic plasticity is a substantial source of variation in migratory behaviours. However, because the genetic basis of migratory traits has been overlooked, the relative contributions of genetic, environment, and genetic by environment interactions have not been quantified for any marine fishes. Within the cod population from northern the Gulf of St. Lawrence, reconstruction of migration routes of cod equipped with data-storage tags revealed undocumented concurrent presence of resident and migratory individuals. Depth time-series analyses revealed high individual variability in vertical patterns of migration. Consequences of the observed individual variation in migration propensity on the structure of the population were then evaluated. Focusing on the fjord of Bonne Bay where I previously identified resident and homing cod, I assessed the degree of demographic dependency of Bonne Bay cod with Gulf cod. Although local recruitment occurs, Bonne Bay does not harbour an abundance of adult cod and external sources of recruitment are substantial. The bay however provides a nursery and a spawning area for Atlantic cod. Finally, I quantified effects of variation in adult migratory behaviour and population density distribution on the performance of a fishery closed area designed to protect a spawning aggregation. Closed area usage by free-ranging individuals revealed disproportional levels of protection between migratory groups. Estimated population density distributions during two periods of contrasted abundance level suggested that, when a closed area is located on the core of a population distribution, density-dependent contraction of population range increases closed area performance. Both individual closed area usage and population density distribution indicated that a displacement south and a reduction of the enforcement period would improve the performance of the study closed area.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".