The role of environmental conditions and exploitation in determining dynamics of redfish (<i>Sebastes</i> species) in the Northwest Atlantic
Bibliographic record
Abstract
Abstract The six stocks of redfish ( Sebastes spp.) in the Northwest Atlantic have been fished for the past 60 years, during which time they have also experienced considerable variability in environmental conditions. Despite their close proximity and with life‐history features characteristic of many deep‐sea fishes (long‐lived, slow‐growing, late‐maturing, relatively low fecundity), each redfish stock has displayed quite different dynamics. Some have been able to support apparently sustainable fisheries, whereas others have been forced to close. The causes of such differences are unclear. We used dynamic factor analysis to determine the relative impacts of exploitation (days fishing for redfish, days fishing for shrimp, days fished by all fisheries, catch in the redfish fishery, total redfish catch) and environment (North Atlantic Oscillation, surface temperature, salinity, shallow, middle, and deep bottom temperatures) on trends of abundance in each stock over the years 1960–2004. The results showed that a mix of exploitation and environmental variability, with various and different lag times, accounted for observed trends. The Gulf of St. Lawrence stock was affected most by exploitation. Flemish Cap and northern Newfoundland‐Labrador stocks were mostly affected by environmental factors with longer time lags than more southerly stocks. We conclude that management of redfish must take into account individual responses to exploitation and environment over the time periods during which such factors operate, often decades or more, as opposed to the usual practice of reviewing only dynamics of the past few years. Deep‐sea populations cannot be managed on the same scales as shelf fisheries.
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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 | 0.000 | 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 | 0.001 |
| 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 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".