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Record W2039770018 · doi:10.1071/mu06009

Microsatellite analysis reveals substantial levels of genetic variation but low levels of genetic divergence among isolated populations of Kaka (<i>Nestor meridionalis</i>)

2006· article· en· W2039770018 on OpenAlexfundno aff
James Sainsbury, Terry Greene, Ron J. Moorhouse, Charles H. Daugherty, Geoffrey K. Chambers

Bibliographic record

VenueEmu - Austral Ornithology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
FundersVictoria UniversityUniversity of Victoria
KeywordsBiological dispersalBiologyGene flowThreatened speciesPopulationGenetic variationConservation biologyEcologyGenetic structureEffective population sizePopulation geneticsEvolutionary biologyGeographyDemographyGeneticsHabitatGene

Abstract

fetched live from OpenAlex

The Kaka (Nestor meridionalis) is a threatened, endemic forest parrot of New Zealand with a fragmented distribution. We present data from eight microsatellite DNA loci for 126 Kaka from nine locations along the length of New Zealand. The observed patterns of variation reveal little population structure in Kaka, despite substantial levels of genetic variation. Our estimate of RST over all populations is low (0.04) and a hierarchical analysis of molecular variance (AMOVA) shows that most allelic variation (93.7%) is within populations rather than divided among them. Further, most inter-population genetic differentiation is attributed to the divergence of the possibly bottlenecked Kapiti Island population from all other populations surveyed. This overall homogeneity probably reflects historic population structure and is being maintained by the ongoing dispersal of individuals between populations. Conservation management of Kaka should reflect this New Zealand-wide gene flow, although special consideration may be given to Kapiti Island.

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 score0.285
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.033
GPT teacher head0.272
Teacher spread0.239 · 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

Citations10
Published2006
Admission routes1
Has abstractyes

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