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Record W4291383378 · doi:10.1111/fme.12590

Effect of catch‐and‐release and temperature at release on reproductive success of Atlantic salmon (<i>Salmo salar</i> L.) in the Rimouski River, Québec, Canada

2022· article· en· W4291383378 on OpenAlexaffabout
Raphaël Bouchard, Kyle W. Wellband, Laurie Lecomte, Louis Bernatchez, Julien April

Bibliographic record

VenueFisheries Management and Ecology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMinistère des Ressources naturelles et des ForêtsFisheries and Oceans CanadaUniversité Laval
Fundersnot available
KeywordsSalmoFisheryCatch and releaseRecreational fishingReproductive successFishingFish <Actinopterygii>Reproductive behaviorBiologyPopulation

Abstract

fetched live from OpenAlex

Abstract Catch‐and‐release fishing is a common conservation practice in recreational fisheries for Atlantic Salmon, although the effects on the reproductive success of caught‐and‐released fish are poorly understood. Herein, we compared the relative reproductive success of caught‐and‐released to non‐caught salmon and tested the effect of temperature at release on reproductive success in the Rimouski River, Québec, Canada. At least 83% of caught‐and‐released salmon that moved upstream of a dam successfully reproduced, including fish that have been released in water above 20°C. However, the reproductive success of caught‐and‐released female salmon was only 73% of the reproductive success of non‐caught salmon. Moreover, the increasing temperature did not affect the reproductive success of released fish that entered a trap, but fish caught at warmer temperatures were less likely to enter the trap. Our findings should be useful for evaluating the risks and benefits of catch‐and‐release, and for optimising conservation practices used for the preservation of Atlantic salmon populations.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.668
Threshold uncertainty score0.832

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.003
GPT teacher head0.175
Teacher spread0.172 · 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 teacher head, 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

Citations13
Published2022
Admission routes2
Has abstractyes

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