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Record W2159404375 · doi:10.1890/08-0859.1

Estimating dispersal from genetic isolation by distance in a coral reef fish (Hypoplectrus puella)

2009· article· en· W2159404375 on OpenAlexafffund
Oscar Puebla, Eldredge Bermingham, Frédéric Guichard

Bibliographic record

VenueEcology · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaSmithsonian Institution
KeywordsBiological dispersalEcologySeascapeGenetic structurePopulationMetapopulationCoral reef fishRange (aeronautics)GeographyIsolation by distanceCoral reefPelagic zoneReefSpatial ecologyBiologyHabitatGenetic diversity

Abstract

fetched live from OpenAlex

The spatial scale of dispersal in coral reef fishes eludes ecologists despite the importance of this parameter for understanding the dynamics of ecological and evolutionary processes. Genetic isolation by distance (IBD) has been used to estimate dispersal in coral reef fishes, but its application in marine systems has been limited by insufficient sampling at different spatial scales and a lack of information regarding population density. Here, we present an analysis of IBD in the barred hamlet (Hypoplectrus puella, Serranidae) at spatial scales ranging from 10 to 3200 km complemented with SCUBA surveys of population densities covering 94000 m2 of reef. We used 10 hypervariable DNA markers to genotype 854 fish from 15 locations, and our results establish that IBD in H. puella emerges at a spatial scale of 175 km and is preserved up to the regional scale (3200 km). Assuming a normal or a Laplace dispersal function, our data are consistent with mean dispersal distances in H. puella that range between 2 and 14 km. Such small mean dispersal distances is a surprising result given the three-week pelagic larval duration of H. puella and the low level of genetic structure at the Caribbean scale (Wright's fixation index, F(ST), estimate = 0.005). Our data reinforce the importance of considering population density when estimating dispersal from IBD and underscore the relevance of sampling at local scales, even when genetic structure is weak at the regional scale.

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 score0.272
Threshold uncertainty score0.490

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 head0.005
GPT teacher head0.218
Teacher spread0.213 · 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

Citations61
Published2009
Admission routes2
Has abstractyes

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