Evidence map›Paper›PMID 39180155›Full record

ArticleSystematic biology2024

Hierarchical Heuristic Species Delimitation Under the Multispecies Coalescent Model with Migration.

Daniel Kornai, Xiyun Jiao, Jiayi Ji, Tomáš Flouri, Ziheng Yang

Abstract read
In one paragraph

Article in Systematic biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
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  7. When islands collide: Divergence predicts outcomes of secondary contact during the fusion of Sulawesi's paleo-archipelago.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  8. A New Species ofAnimals : an open access journal from MDPI · 2025
    Article
  9. The power of coalescent methods for inferring recent and ancient gene flow in endangered Bactrian camels.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  10. Article
  11. Distinguishing species boundaries from geographic variation.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  12. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Daniel KornaiDepartment of Genetics, Evolution, and Environment, University College London, Gower Street, London WC1E 6BT, UK.ORCID 0000-0003-4919-2384
Xiyun JiaoDepartment of Statistics and Data Science, China Southern University of Science and Technology, Shenzhen, Guangdong 518055, China.
Jiayi JiDepartment of Genetics, Evolution, and Environment, University College London, Gower Street, London WC1E 6BT, UK.
Tomáš FlouriDepartment of Genetics, Evolution, and Environment, University College London, Gower Street, London WC1E 6BT, UK.ORCID 0000-0002-8474-9507
Ziheng YangDepartment of Genetics, Evolution, and Environment, University College London, Gower Street, London WC1E 6BT, UK.ORCID 0000-0003-3351-7981

Funding

Biotechnology and Biological Sciences Research Council BB/T003502/1Guangdong Natural Science Foundation 2022A1515011767Natural Environment Research Council NE/X002071/1Shenzhen Training Project of Excellent Scientific & Technological Talents RCYX20221008093033012The Natural Science Foundation of China 12101295
6 · The paper itself

Abstract

The multispecies coalescent (MSC) model accommodates genealogical fluctuations across the genome and provides a natural framework for comparative analysis of genomic sequence data from closely related species to infer the history of species divergence and gene flow. Given a set of populations, hypotheses of species delimitation (and species phylogeny) may be formulated as instances of MSC models (e.g., MSC for 1 species versus MSC for 2 species) and compared using Bayesian model selection. This approach, implemented in the program bpp, has been found to be prone to over-splitting. Alternatively, heuristic criteria based on population parameters (such as population split times, population sizes, and migration rates) estimated from genomic data may be used to delimit species. Here, we develop hierarchical merge and split algorithms for heuristic species delimitation based on the genealogical divergence index (gdi) and implement them in a Python pipeline called hhsd. We characterize the behavior of the gdi under a few simple scenarios of gene flow. We apply the new approaches to a dataset simulated under a model of isolation by distance as well as 3 empirical datasets. Our tests suggest that the new approaches produced sensible results and were less prone to oversplitting. We discuss possible strategies for accommodating paraphyletic species in the hierarchical algorithm, as well as the challenges of species delimitation based on heuristic criteria.

Indexed as

ClassificationAlgorithmsAnimalsGene FlowGenetic SpeciationHeuristicsModels, GeneticPhylogenyBPPgenealogical divergence indexgene flowgiraffesmilksnakesmultispecies coalescentspecies delimitationsunfish

Identifiers

PMID39180155
PMCPMC11637770

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.