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Marine landscapes and population genetic structure of herring (<i>Clupea harengus</i> L.) in the Baltic Sea

2005· article· en· W2070134003 on OpenAlex
Hanne Jørgensen, Michael M. Hansen, Dorte Bekkevold, Daniel E. Ruzzante, Volker Loeschcke

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMolecular Ecology · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsDalhousie University
Fundersnot available
KeywordsClupeaBiologyHerringReproductive isolationGene flowPopulationBaltic seaGenetic structureEcologyIsolation by distanceGenetic variationPanmixiaFisheryOceanographyFish <Actinopterygii>GeneGenetics

Abstract

fetched live from OpenAlex

Numerically small but statistically significant genetic differentiation has been found in many marine fish species despite very large census population sizes and absence of obvious barriers to migrating individuals. Analyses of morphological traits have previously identified local spawning groups of herring (Clupea harengus L.) in the environmentally heterogeneous Baltic Sea, whereas allozyme markers have not revealed differentiation. We analysed variation at nine microsatellite loci in 24 samples of spring-spawning herring collected at 11 spawning locations throughout the Baltic Sea. Significant temporal differentiation was observed at two locations, which we ascribe to sympatrically spawning but genetically divergent 'spawning waves'. Significant differentiation was also present on a geographical scale, though pairwise F(ST) values were generally low, not exceeding 0.027. Partial Mantel tests showed no isolation by geographical distance, but significant associations were observed between genetic differentiation and environmental parameters (salinity and surface temperature) (0.001 < P < or = 0.099), though these outcomes were driven mainly by populations in the southwestern Baltic Sea, which also exhibits the steepest environmental gradients. Application of a novel method for detecting barriers to gene flow by combining geographical coordinates and genetic differentiation allowed us to identify two zones of lowered gene flow. These zones were concordant with the separation of the Baltic Sea into major basins, with environmental gradients and with differences in migration behaviour. We suggest that similar use of landscape genetics approaches may increase the understanding of the biological significance of genetic differentiation in other marine fishes.

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.

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 score0.101
Threshold uncertainty score0.385

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 head0.003
GPT teacher head0.202
Teacher spread0.199 · 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