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Genetic survey of shallow populations of the Mediterranean red coral [<i>Corallium rubrum</i>(Linnaeus, 1758)]: new insights into evolutionary processes shaping nuclear diversity and implications for conservation

2010· article· en· W2164439855 on OpenAlexaff
Jean‐Baptiste Ledoux, Kenza Mokhtar‐Jamaï, Charlotte Roby, Jean‐Pierre Féral, Joaquim Garrabou, Didier Aurelle

Bibliographic record

VenueMolecular Ecology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsUniversité Laval
FundersAgence Nationale de la Recherche
KeywordsBiologyBiological dispersalGenetic diversityEcologyIsolation by distanceGenetic structureMediterranean climatePopulationEvolutionary biologyDemography

Abstract

fetched live from OpenAlex

Combined action from over-harvesting and recent mass mortality events potentially linked to ongoing climate changes has led to new concerns for the conservation of shallow populations (5-60 m) of Corallium rubrum, an octocorallian that is mainly found in the Mediterranean Sea. The present study was designed to analyse population structure and relationships at different spatial scales (from 10s of meters to 100s of kilometres) with a focus on dispersal pattern. We also performed the first analysis of the distribution of genetic diversity using a comparative approach between regional-clusters and samples. Forty populations dwelling in four distinct regions between 14 and 60 m in depth were genotyped using 10 microsatellites. Our main results indicate (i) a generalized pair-sample differentiation combined with a weak structure between regional-clusters; (ii) the occurrence of isolation by distance at the global scale, but also within two of the three analysed regional-clusters; (iii) a high level of genetic diversity over the surveyed area with a heterogeneous distribution from regional-cluster to sample levels. The evolutionary consequences of these results are discussed and their management implications are provided.

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 score0.070
Threshold uncertainty score0.971

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 science0.0000.001
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 head0.042
GPT teacher head0.245
Teacher spread0.203 · 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

Citations92
Published2010
Admission routes1
Has abstractyes

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