Evidence map›Paper›PMID 39436077›Full record

ArticleSystematic biology2025

The Fossilized Birth-Death Model Is Identifiable.

Kate Truman, Timothy G Vaughan, Alex Gavryushkin, Alexandra Sasha Gavryushkina

Erratum issuedAbstract read
In one paragraph

Article in Systematic biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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  3. Article
  4. Reading tree leaves: inferring speciation anfd extinction processes using phylogenies.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Review
  5. Article
  6. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Kate TrumanBiological Data Science Laboratory, School of Mathematics and Statistics, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand.ORCID 0009-0005-4630-3853
Timothy G VaughanDepartment of Biosystems Science and Engineering, ETH Zurich, Schanzenstrasse 44, Postfach 4009, Basel 9, Switzerland.ORCID 0000-0001-6220-2239
Alex GavryushkinBiological Data Science Laboratory, School of Mathematics and Statistics, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand.ORCID 0000-0001-6299-8249
Alexandra Sasha GavryushkinaBiological Data Science Laboratory, School of Mathematics and Statistics, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand.ORCID 0000-0002-1885-1108

Funding

Data Science Programmes UOAX1932European Union's Horizon 2020 Research and Innovation Programme 101001077Marsden 21-UOC-057Ministry of Business, Innovation, and Employment of New Zealand UOOX1912Royal Society Te Apārangi UOC1702
6 · The paper itself

Abstract

Time-dependent birth-death sampling models have been used in numerous studies to infer past evolutionary dynamics in different biological contexts, for example,  speciation and extinction rates in macroevolutionary studies, or effective reproductive number in epidemiological studies. These models are branching processes where lineages can bifurcate, die, or be sampled with time-dependent birth, death, and sampling rates, generating phylogenetic trees. It has been shown that in some subclasses of such models, different sets of rates can result in the same distributions of reconstructed phylogenetic trees, and therefore, the rates become unidentifiable from the trees regardless of their size. Here, we show that widely used time-dependent fossilized birth-death (FBD) models are identifiable. This subclass of models makes more realistic assumptions about the fossilization process and certain infectious disease transmission processes than the unidentifiable birth-death sampling models. Namely, FBD models assume that sampled lineages stay in the process rather than being immediately removed upon sampling. The identifiability of the time-dependent FBD model justifies using statistical methods that implement this model to infer the underlying temporal diversification or epidemiological dynamics from phylogenetic trees or directly from molecular or other comparative data. We further show that the time-dependent FBD model with an extra parameter, the removal after sampling probability, is unidentifiable. This implies that in scenarios where we do not know how sampling affects lineages, we are unable to infer this extra parameter together with birth, death, and sampling rates solely from trees.

Indexed as

ClassificationFossilsModels, BiologicalPhylogenyAnimalsBiological EvolutionBirth–death sampling modelsextinctionfossilsphylogeneticsspeciation

Identifiers

PMID39436077
PMCPMC11997801

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Registered trials

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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.