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Gene pool sharing and genetic bottleneck effects in subpopulations of Eschweilera ovata (Cambess.) Mart. ex Miers (Lecythidaceae) in the Atlantic Forest of southern Bahia, Brazil

2019· article· en· W2972511081 on OpenAlexaff
Alesandro Souza Santos, Daniela B. Borges, Caio Vinicius Vivas, Cássio van den Berg, Polliana Silva Rodrigues, Roberto Tarazi, Fernanda Amato Gaiotto

Bibliographic record

VenueGenetics and Molecular Biology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsDiscovery Centre
FundersFundação de Amparo à Pesquisa do Estado da BahiaConselho Nacional de Desenvolvimento Científico e TecnológicoInstituto Chico Mendes de Conservação da BiodiversidadeIntegrated Envirotech Sdn BhdCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsBiologyGene flowGenetic diversityPopulation bottleneckMicrosatelliteGenetic structureForest fragmentationFragmentation (computing)EcologyGene poolEvolutionary biologyBiodiversityGenetic variationGeneticsPopulationGeneAllele

Abstract

fetched live from OpenAlex

Forest loss and fragmentation are the main threats to the maintenance of the Atlantic Forest, an important global biodiversity hotspot. Because of the current critical level of deforestation, ecological corridors are needed to facilitate species dispersion and gene flow among fragments. This study was conducted to investigate the genetic variability and gene pool sharing of Eschweilera ovata in five forest remnants in southern Bahia, Brazil using nuclear simple sequence repeat (nSSR) and plastid simple sequence repeat (cpSSR) microsatellite markers. cpSSR marker analysis revealed the domains of four haplotypes, showing that 80% of the individuals had only four maternal origins, reflecting a founder effect and/or genetic bottleneck. The results of cpSSR and nSSR analyses indicated moderate genetic diversity, particularly in conservation units with full protection, which showed the best parameters of all areas evaluated. Another indication of the susceptibility of these populations to forest loss and fragmentation was the strong genetic bottleneck observed. In contrast, genetic structure analyses (FST and discriminant analysis of principal components) revealed gene pool sharing between the subpopulations, which may reflect the historical gene flow that occurred before forest fragmentation.

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 score0.248
Threshold uncertainty score0.665

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 head0.228
Teacher spread0.223 · 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

Citations8
Published2019
Admission routes1
Has abstractyes

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