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Record W2105928226 · doi:10.1111/mec.12222

Puny males punch above their weight to preserve genetic diversity in a declining <scp>A</scp>tlantic salmon population

2013· letter· en· W2105928226 on OpenAlexaff
Jocelyn Moore, Dylan J. Fraser

Bibliographic record

VenueMolecular Ecology · 2013
Typeletter
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsConcordia UniversityUniversity of British ColumbiaRoyal British Columbia Museum
Fundersnot available
KeywordsBiologyDiversity (politics)Genetic diversityPopulationEvolutionary biologyEcologyZoologyDemography

Abstract

fetched live from OpenAlex

Many salmonid fish populations have anadromous (i.e. migratory) and nonanadromous individuals co-existing in sympatry. The nonanadromous individuals, frequently males, mature at a much smaller size in freshwater without undergoing marine migrations and often successfully fertilize many eggs laid by anadromous females. Because these small males do not recruit to fisheries, they are often not regarded in high esteem by fishers. In this issue of Molecular Ecology, Johnstone et al. (2013) demonstrate that by substantially contributing to reproduction, such males help maintain genetic diversity in a declining population of Atlantic salmon (Salmo salar). Their results show that estimates of effective population size (Ne), obtained by counting the number of anadromous adults returning from sea and correcting for unequal sex ratios, are lower than estimates generated from genetic markers. Many mechanisms are expected to reduce Ne below the adult census population size (N); the opposite pattern of Ne > N observed by Johnstone et al. (2013) is difficult to explain unless the reproductive effort of nonanadromous males is accounted for. The results have important implications for the conservation of small populations and highlight the challenges of relating Ne to N in organisms with complex life histories.

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)0.002
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0160.010
Insufficient payload (model declined to judge)0.0050.006

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 head0.012
GPT teacher head0.208
Teacher spread0.195 · 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

Citations4
Published2013
Admission routes1
Has abstractyes

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