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Record W1971369475 · doi:10.3354/meps317157

Genetic population structure across a range of geographic scales in the commercially exploited marine gastropod Buccinum undatum

2006· article· en· W1971369475 on OpenAlexaboutno aff
David Weetman, Lorenz Hauser, MK Bayes, JR Ellis, Paul W. Shaw

Bibliographic record

VenueMarine Ecology Progress Series · 2006
Typearticle
Languageen
FieldEngineering
TopicMarine Biology and Environmental Chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyPopulationFisheryRange (aeronautics)EcologyBiologyDemography

Abstract

fetched live from OpenAlex

Marine invertebrates are exploited increasingly as food resources worldwide, but knowledge of genetic population structure is limited for most commercially valuable taxa. We investigated genetic structure in the widely distributed, subtidal gastropod Buccinum undatum by screening samples from 28 locations at 5 microsatellite loci. Multidimensional scaling and cluster analysis were applied to study macrogeographic structure, and revealed 4 well-supported groupings of populations: Canada, Iceland, Swedish Skaggerak, and a cluster containing most samples from the European continental shelf (hereafter 'Shelf'). A fifth cluster comprising all 5 samples from the Solent (UK) relied on exceptional differentiation of just 2 alleles, which is consistent with significant evidence for recent bottlenecks in this area. Within the Shelf cluster most pairwise tests of differentiation were significant, although the global F ST of 0.014 was very low for a direct-developing species. Our data suggest that use of highly polymorphic markers caused a relatively minor downward bias to F ST , although historical connectivity of populations that are not in migration-drift equilibrium might be more important. However, significant isolation by distance among British North Sea coast samples (F ST = 0.010) is consistent with approach to equilibrium and suggests recent gene flow, probably between semi-continuous populations. At a microgeographic scale, we found migration to be consistently higher from inshore to offshore within 3 separate areas; a factor that may underpin the lower diversity and greater differentiation observed for bay and inlet populations. Such populations might serve as important sources of genetic diversity, but are likely to be particularly vulnerable to exploitation.

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 score0.027
Threshold uncertainty score0.990

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 head0.190
Teacher spread0.187 · 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

Citations47
Published2006
Admission routes1
Has abstractyes

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