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Record W4309920126 · doi:10.1139/cjfas-2022-0126

Iteroparity and its contribution to life-history variation in Atlantic salmon

2022· article· en· W4309920126 on OpenAlexvenueno aff
Lo Persson, Astrid Raunsgård, Eva B. Thorstad, Gunnel Marie Østborg, Kurt Urdal, Harald Sægrov, Ola Ugedal, Kjetil Hindar, Sten Karlsson, Peder Fiske, Geir H. Bolstad

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersNatureMiljødirektoratetNorges ForskningsrådNorsk institutt for naturforskningVetenskapsrådetSvenska Forskningsrådet Formas
KeywordsSemelparity and iteroparityBiologyReproductionLife history theoryLife historyPopulationEcologySexual maturityZoologyDemography

Abstract

fetched live from OpenAlex

Evolution of iteroparity is shaped by the trade-off between current and future reproduction. We studied variation in iteroparity among 205 050 individual Atlantic salmon caught in 179 rivers spanning 14° of latitude. The proportion of repeat spawners (iteroparous individuals) averaged 3.8% and ranged from 0% to 26% across rivers. Females were more often repeat spawners than males and had lower cost of reproduction in terms of lost body mass between spawning events. Proportion of repeat spawners for a given sea age at maturity, and the ratio of alternate to consecutive repeat spawners, increased with increasing population mean sea age at maturity. By combining smolt age, sea age at maturity, and age at additional spawning events, we identified 141 unique life-history types, and repeat spawners contributed 75% of that variation. Our results show that repeat spawners are important for life-history variation and suggest that the association between mean sea age and the frequency of repeat spawning is adaptive rather than a pleiotropic side effect arising from selection on sea age.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.194
Teacher spread0.179 · 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

Citations23
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicFish Ecology and Management Studies→French-language works237,207→