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Record W7133277066

Assessment of Lobster in the Gaspé, Quebec, in 2022

2024· other· en· W7133277066 on OpenAlexaboutno aff
Fisheries and Oceans Canada, Pêches et Océans Canada

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsFishingCatch per unit effortSpring (device)Sampling (signal processing)Logbook
DOInot available

Abstract

fetched live from OpenAlex

Landings in the Gaspé increased sharply in 2022, reaching 3,796 t, one of the highest values in the time series. They were 64.1% higher in 2022 than in 2018 and 169.9% higher than the average of the previous 25 years (1,407 t, 1997–2021). Fishing effort has been stable since 2019 at 2.34 million traps, which is 23.1% below the average for the 1994–2005 period. In 2022, 75.6% of landings in Gaspé came from LFA 20, 9.9% came from LFA 21 and 14.5% from Area 19. For the entire Gaspé area, the catch per unit effort (CPUE) by weight from commercial sampling has been increasing significantly since 2014. In LFA 19C, the CPUE in 2022 (3.51 kg/trap) was 33% higher than in 2018. In LFA 20, the CPUE rose by 40.8% between 2018 and 2022 (1.22 kg/trap). The logbook CPUEs followed the same trend for the latter. In LFA 21B, the CPUE increased by 13.2% between the fall of 2018 and the fall of 2022 (4.99 kg/trap). In LFA 19C, the demographic indicators show that the average size of commercial lobsters sampled was larger in 2022 at 97.6 mm, which is 1.9% greater than the 2018 value. In LFA 20, the average size has also been trending upward, reaching 90.7 mm in 2022, which is more than 1.4% of the 2018 value. In LFA 21B, average sizes have been trending downward in the fall and spring fisheries since 2015, reaching 91.2 mm in 2022, which is 1.7% below the 2018 value. Fishing pressure indicators could not be estimated for LFAs 19 and 21. In LFA 20, the exploitation rates have been showing a slight decline since 2008. The rate was 78.1% in 2021, which is above the average for the 2016–2018 period (73.7%). In LFA 20, the productivity indicators have remained high. The abundance of berried females has been increasing since 2011. Theoretical egg production was 1.2 times higher in 2022 than in 2018 and 10.3 times higher than during the 1994–1996 period. Indicators of fishery pre-recruitment in LFA 20 were stable between 2018 and 2022, at a rate of 3.06 lobsters per trap. The number of degree-days of the 2022 fishing season (284 DD) was 7.2% below the average for the previous 25 years. Small rock crab are a key prey source for lobster. Despite the low fishing effort observed in recent years in the Gaspé, the size structures of commercial dockside sampling suggest a low abundance of rock crab below the legal size in LFA 19. In addition, the CPUE of rock crab in the commercial fishery has been in decline in that Area since 2017. In 2022, it was below the average for the 2000–2021 period. However, these trends were not observed in LFAs 20 and 21. High abundance, productivity and landings indicate that the Gaspé lobster stock is in good condition and in the healthy zone according to the precautionary approach. The health indicators of rock crab in Gaspé were examined from an ecosystem approach. Unlike in LFAs 20 and 21, the population status of this essential prey for lobster in LFA 19 is of concern. To ensure the sustainability of the lobster stock and that of its preferred prey while preserving their trophic link, a low rock crab mortality rate should be favoured.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.009
GPT teacher head0.262
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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