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Record W4405653827 · doi:10.1111/fme.12779

A Physical Bottleneck Increases Predation on Atlantic Salmon Smolts During Seaward Migration in an Irish Index River

2024· article· en· W4405653827 on OpenAlexaff
Lene K. Sortland, Glen D. Wightman, Hugo Flávio, Kim Aarestrup, William Roche

Bibliographic record

VenueFisheries Management and Ecology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsOcean Tracking NetworkDalhousie University
FundersInland Fisheries IrelandEuropean Commission
KeywordsBottleneckFisheryIndex (typography)PredationFish <Actinopterygii>IrishGeographyBiologyEcologyEngineeringComputer science

Abstract

fetched live from OpenAlex

ABSTRACT Counting departing smolts and returning adults in index rivers is essential to estimate marine survival and track population trends of Atlantic salmon ( Salmo salar ). However, mortalities between counting facilities and a river mouth can skew survival estimates. We used acoustic and radio telemetry to investigate survival, mortality sources and behaviour of wild salmon smolts in the River Erriff, Ireland's index river, and Killary Fjord. Smolts were tagged with acoustic tags in 2017 ( n = 40) and 2018 ( n = 35) and radio tags in 2018 ( n = 30). Survival was low for acoustic‐tagged smolts in 2017 (26%) and 2018 (47%), mainly due to riverine mortality. Terrestrial or avian predators consumed 65% of acoustic‐tagged smolts in 2017 and 67% of radio‐tagged smolts in 2018. Nocturnal migration and ebb tide transportation likely contributed to high estuary survival. High predation on smolts emphasised the importance of assessing freshwater mortality for effective salmon management.

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 score0.017
Threshold uncertainty score0.939

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 science0.0000.000
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 head0.008
GPT teacher head0.212
Teacher spread0.205 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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