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Broad‐ to fine‐scale population genetic patterning in the smallmouth bass<i>Micropterus dolomieu</i>across the Laurentian Great Lakes and beyond: an interplay of behaviour and geography

2007· article· en· W2167569470 on OpenAlexaboutno aff
Carol A. Stepien, Douglas Murphy, Rex Meade Strange

Bibliographic record

VenueMolecular Ecology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersDivision of Biological InfrastructureOhio Sea Grant College, Ohio State UniversityNational Oceanic and Atmospheric AdministrationGreat Lakes Fishery Commission
KeywordsVicarianceMicropterusEcologyBiologyPopulationIsolation by distanceGenetic structureRange (aeronautics)Bass (fish)Fish migrationGlacial periodPhylogeographyGenetic variationHabitatDemographyPhylogenetic tree

Abstract

fetched live from OpenAlex

Analysis of population genetic relationships reveals the signatures of current processes such as spawning behaviour and migration, as well as those of historical events including vicariance and climate change. This study examines these signatures through testing broad- to fine-scale genetic patterns among smallmouth bass Micropterus dolomieu spawning populations across their native Great Lakes range and outgroup areas, with fine-scale concentration in Lake Erie. Our primary hypotheses include whether genetic patterns result from behavioural and/or geographical isolation, specifically: (i) Are spawning groups in interconnected waterways genetically separable? (ii) What is the degree of isolation across and among lakes, basins, and tributaries? (iii) Do genetic divergences correspond to geographical distances? and (iv) Are historical colonization patterns from glacial refugia retained? Variation at eight nuclear microsatellite DNA loci are analysed for 666 smallmouth bass from 28 locations, including 425 individuals in Lake Erie; as well as Lakes Superior, Huron, and Ontario, and outgroups from the Mississippi, Ohio, St. Lawrence, and Hudson River drainages. Results reveal marked genetic differences among lake and river populations, as well as surprisingly high divergences among closely spaced riverine sites. Results do not fit an isolation-by-geographical-distance prediction for fine-scale genetic patterns, but show weak correspondence across large geographical scales. Genetic relationships thus are consistent with hypotheses regarding divergent origins through vicariance in glacial refugia, followed by colonization pathways establishing modern-day Great Lakes populations, and maintenance through behavioural site fidelity. Conservation management practices thus should preserve genetic identity and unique characters among smallmouth bass populations.

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)0.001
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 score0.215
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.004
GPT teacher head0.229
Teacher spread0.225 · 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

Citations65
Published2007
Admission routes1
Has abstractyes

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