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Reconstructing recent divergence: evaluating nonequilibrium population structure in New Zealand chinook salmon

2002· article· en· W2130710857 on OpenAlexaff
Michael T. Kinnison, Paul Bentzen, Martin Unwin, Tom Quinn

Bibliographic record

VenueMolecular Ecology · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsDalhousie University
FundersDartmouth CollegeUniversity of Washington
KeywordsGene flowBiologyPopulationPopulation geneticsEffective population sizeEcologyEvolutionary biologyGenetic variationGeneticsDemographyGene

Abstract

fetched live from OpenAlex

Newly established or perturbed populations are often the focus of conservation concerns but they pose special challenges for population genetics because drift-migration equilibrium is unlikely. To advance our understanding of the evolution of such populations, we investigated structure and gene flow among populations of chinook salmon that formed via natural straying following introduction to New Zealand in the early 1900s. We examined 11 microsatellite loci from samples collected in several sites and years to address two questions: (i) what population differentiation has arisen in the approximately 30 generations since salmon were introduced to New Zealand, relative to temporal variation within populations; and (ii) what are the approximate effective population sizes and amounts of gene flow in these populations? These questions are routinely addressed in studies of indigenous populations, but less often in the case of new populations and rarely with consideration of equilibrium assumptions. We show that despite the recent introduction, continued gene flow and high temporal variability among samples, detectable population structure has arisen among the New Zealand populations, consistent with their colonization pattern and isolation by geographical distance. Furthermore, we use simple individual-based simulations and estimates of effective population sizes to estimate the effective gene flow among drainages under likely nonequilibrium conditions. Similar methodology may be broadly applicable to other studies of population structure and phenotypic evolution under similar nonequilibrium, high gene flow conditions.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
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)0.0110.000

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 head0.014
GPT teacher head0.242
Teacher spread0.228 · 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.

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

Citations78
Published2002
Admission routes1
Has abstractyes

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