Stock Assessment of Whelk in Quebec’s Coastal Waters in 2024
Bibliographic record
Abstract
Status The average catch per unit of effort (CPUE) for 2022–2024 is below the historical average (2002–2021) in Areas 1 (-24%), 2 (-40%), 3 (-54%), 4 (-16%), 5 (-29%), 6 (-34%) and 8 (La Romaine: -49% and Blanc-Sablon: -25%) on the North Shore; in Areas 12 (-60%) and 13 (-50%) in the Gaspé Peninsula–Lower St. Lawrence; and in Area 15 (-28%) in the Magdalen Islands. Stock status is uncertain in Areas 10 and 14, where there is no fishing, and in Areas 7, 9 and 11, where fishing effort is sporadic and low. Trends The CPUE trend has been downward for at least six years in all fishing areas in Quebec. The densities of legal-size whelk and recruits observed during the biennial research survey conducted in 2024 in Areas 1 and 2 on the Upper North Shore are lower than those of the 2022 survey and are among the lowest values in the historical series (2005–2024). Ecosystem and Climate Change Considerations The seabed of fishing sites in the Estuary and Gulf of St. Lawrence, mostly in the 10–30 m range, are experiencing an increase in water temperature and in the abundance of crustacean predators such as lobster and rock crab. However, these ecosystem changes and their effects on whelk stock productivity have not been quantified. Stock Advice The status of exploited stocks is worrying. These stocks do not appear to be able to sustain the fishing effort of recent years, and TACs should be adjusted accordingly. The very low abundance of recruits observed since 2017 in research surveys in Areas 1 and 2 on the Upper North Shore poses a risk to stock sustainability in the coming years. Because whelk populations are susceptible to local depletion, the breeding season should be protected. This could be achieved by establishing refuge areas within each fishing area or by implementing other strategies to protect the resource. Other Management Questions As indicated in the 2022 Science Advisory Report, management measures should be adjusted in Areas 4 and 5 to better align with the T50 (90 mm) to ensure the sustainability of the resource.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".