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Record W7133268311

Assessment of Lobster in the Magdalen Islands, Quebec, in 2022

2024· other· en· W7133268311 on OpenAlexfundaboutno 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
FundersFisheries and Oceans Canada
KeywordsFishingProductivityCatch per unit effortNorth seaEconomic indicator
DOInot available

Abstract

fetched live from OpenAlex

Landings reached an all-time high of 6,715 t in 2022, which is 124.3% above the average of the past 25 years (2,994 t, 1997–2021), along with an increase in fishing effort since 2020. The increase in landings between 2018 and 2022 was greater in the north (69.8%) than in the south (26.5%). In 2022, for the Islands as a whole, the catch per unit effort (CPUE) by weight of the commercial sample (1.26 kg/trap) was 29.2% higher than in 2018 and 139.4% (south: 120.1%, north: 197.1%) higher than the 1985–2021 average. The density of commercial lobsters in the trawl survey increased significantly from 2014 to 2019 (19.6 lobsters/1,000 m2). Since then, the density has decreased to 14.4 lobsters/1,000 m2 in 2022, which remains 37.1% higher than in 2018 and 80% higher than the 1995–2021 average (8.0 lobsters/1,000 m2). With respect to demographic indicators, the average size of commercial lobsters sampled was 92.3 mm in 2022 and has been stable since 2017. In the trawl survey, the value for 2022 is higher than that for 2018, and close to the peak observed in 2013. Fishing pressure indicators show a slight decrease in exploitation rates since 2005. The rates for 2021 (south: 59%, north: 60.3%) were comparable to those in 2017 and 2018. In 2021, the exploitation rate in the north was equal to the 1985–2021 average, while the rate in the south was 6.4% below the average for the same period. Productivity indicators remained high. For the Islands as a whole, theoretical egg production in 2022 was 1.7 times higher than in 2018 and 6.8 times higher than in 1994–1996. However, a decrease in individual mating success has been observed since 2004. Pre-recruitment indices in 2022 (Pr1=12.4 lobsters/1,000 m2) were 14.1% higher than in 2018 and 132.8% higher than the 1995–2021 average. The benthic recruitment index has been stable at high levels since 2018. The number of degree-days for the 2018 and 2019 fishing seasons is below the average for the past 25 years, while that for 2020 is above the average. Small rock crab is a key prey source for lobster. The size structures of the trawl survey in subareas A and B suggest very low abundance of crabs under the legal size. In addition, rock crab CPUE in the commercial fishery has been declining since 2020, and is below the 1998–2021 average in 2022. With abundance and productivity remaining high and growing, it can be concluded that the Magdalen Islands lobster stock is in good condition relative to current exploitation rates. However, since 2021, a discrepancy has been observed between fishing yield trends in the north and south of this area, skewed towards the north. According to the precautionary approach, the Islands’ lobster stock is currently in the healthy zone. Indicators of the health status of the rock crab population in the Magdalen Islands were examined using an ecosystem approach. The population status of this key prey source of lobster is of great concern. In an effort to ensure the sustainability of the lobster stock and that of its preferred prey, while maintaining their trophic link, all exceptional measures should be considered to minimize rock crab mortality.

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 score0.015
Threshold uncertainty score0.110

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 science0.0010.001
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 head0.008
GPT teacher head0.257
Teacher spread0.249 · 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 routes2
Has abstractyes

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Same venueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada→French-language works237,207→