Stock assessment of whelks in Quebec's inshore waters in 2021
Bibliographic record
Abstract
In 2021, whelk landings in Québec totalled 909.6 t, a sharp decrease (-32%) compared to 2017 (1,332.0 t). In 2021, 73% of landings came from the North Shore, 18% from the Îles de-la-Madeleine and 8% from the Gaspé Peninsula–Lower St. Lawrence. Landings had decreased in most fishing areas compared to 2017. The largest decreases were seen in areas 1 (-31%), areas 4-5 (-76%, pooled data), area 6 (-55%), and area 12 (-63%). In contrast, landings in areas 2 (+136%) and 8 (+212%) increased from 2017. The TAC, where applicable, was met only in area 12. For areas managed by a total allowable catch (TAC), it was not reached in areas 1, 12, 13 and 15 and was exceeded by 4.2 t (3.8% of the current TAC) in area 2. The trend in catch per unit effort (CPUE) over the 2018-2021 period is positive in area 8, relatively stable in areas 1 and 2, and declining in areas 3, 4-5, 6, 12, 13, and 15. In 2021, CPUE in areas 3, 4-5, 12, 13, and 15 was between -3% and -49% below their 2002-2018 historical median. The research survey conducted in 2019 in areas 1 and 2 showed that the density of whelks ≥ 70 mm decreased from 2017 at Foresville, Pointe-aux-Outardes and Baie-Comeau sites. In addition, total whelk density (≥ 20 mm) was significantly lower than the highest value observed historically. Areas 10 and 14 are not fished, and fishing effort has been sporadic and low in areas 9 and 11. It is therefore impossible to comment on the status of the resource in these areas. According to a recent assessment, the average size at which 50% of female Buccinum undatum are sexually mature (T50) ranges from 62 to 93 mm. To protect reproductive potential, the minimum legal size (MLS) should be adjusted to reflect T50. Such an adjustment would represent an increase in MLS for areas 4, 5, 6, 7, 8, 12 and 13. The stock status in some areas of the Gaspé Peninsula (areas 12 and 13), the Middle North Shore (areas 3, 4, 5 and 6) and the Îles-de-la-Madeleine (area 15) is of concern. These stocks do not seem to be able to sustain the current fishing effort over the long term. There are declining trends in CPUE and local declines within some areas. These stocks are therefore vulnerable to overexploitation and local depletion. Consequently, management measures should be adjusted to better align with the T50 and lead to a significant decrease in fishing effort to ensure the sustainability of this resource. Monitoring of the severity of whelk infestation by parasitic polychaete borers in area 15, a threat raised in recent years by commercial fishermen, will need to continue to assess the impact on survival, reproduction, growth and recruitment of affected whelks.
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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) | 0.004 | 0.001 |
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".