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Record W2310584788 · doi:10.1093/cz/zow042

Red River barrier and Pleistocene climatic fluctuations shaped the genetic structure of<i>Microhyla fissipes</i>complex (Anura: Microhylidae) in southern China and Indochina

2016· article· en· W2310584788 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Zoology · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsRoyal Ontario Museum
FundersRussian Science FoundationChinese Academy of SciencesRussian Foundation for Basic ResearchNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsPleistoceneBiological dispersalLast Glacial MaximumEcologyPhylogeographyGenetic divergenceGlacial periodGeographyLand bridgeEndemismPopulationBiologyPaleontologyGenetic diversityPhylogenetic tree

Abstract

fetched live from OpenAlex

South China and Indochina host striking species diversity and endemism. Complex tectonic and climatic evolutions appear to be the main drivers of the biogeographic patterns. In this study, based on the geologic history of this region, we test 2 hypotheses using the evolutionary history of Microhyla fissipes species complex. Using DNA sequence data from both mitochondrial and nuclear genes, we first test the hypothesis that the Red River is a barrier to gene flow and dispersal. Second, we test the hypothesis that Pleistocene climatic cycling affected the genetic structure and population history of these frogs. We detect 2 major genetic splits that associate with the Red River. Time estimation suggests that late Miocene tectonic movement associated with the Red River drove their diversification. Species distribution modeling (SDM) resolves significant ecological differences between sides of the Red River. Thus, ecological divergence also probably promoted and maintained the diversification. Genogeography, historical demography, and SDM associate patterns in southern China with climate changes of the last glacial maximum (LGM), but not Indochina. Differences in geography and climate between the 2 areas best explain the discovery. Responses to the Pleistocene glacial-interglacial cycling vary among species and regions.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
Threshold uncertainty score0.465

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 head0.011
GPT teacher head0.236
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