The fossilized birth-death model for the analysis of stratigraphic range data under different speciation modes

JOURNAL OF THEORETICAL BIOLOGY

卷:447

Article

Stadler, Tanja^1,2  Gavryushkina, Alexandra^1,2  Warnock, Rachel C. M.^1,2  Drummond, Alexei J.³  Heath, Tracy A.⁴ 

[1] ETH, Dept Biosyst Sci & Engn, CH-4058 Basel, Switzerland

[2] SIB, Lausanne, Switzerland

[3] Univ Auckland, Ctr Computat Evolut, Dept Comp Sci, Auckland 1010, New Zealand

[4] Iowa State Univ, Dept Ecol Evolut & Organismal Biol, Ames, IA 50011 USA

关键词: Birth-death process;    Sampling-through-time;    Tree prior;    Phylogenetic tree;    Macroevolution;    Fossils;   

DOI  :  10.1016/j.jtbi.2018.03.005

来源: Elsevier

【 摘 要 】

A birth-death-sampling model gives rise to phylogenetic trees with samples from the past and the present. Interpreting birth as branching speciation, death as extinction, and sampling as fossil preservation and recovery, this model- also referred to as the fossilized birth-death (FBD) model - gives rise to phylogenetic trees on extant and fossil samples. The model has been mathematically analyzed and successfully applied to a range of datasets on different taxonomic levels, such as penguins, plants, and insects. However, the current mathematical treatment of this model does not allow for a group of temporally distinct fossil specimens to be assigned to the same species. In this paper, we provide a general mathematical FBD modeling framework that explicitly takes stratigraphic ranges into account, with a stratigraphic range being defined as the lineage interval associated with a single species, ranging through time from the first to the last fossil appearance of the species. To assign a sequence of fossil samples in the phylogenetic tree to the same species, i.e., to specify a stratigraphic range, we need to define the mode of speciation. We provide expressions to account for three common speciation modes: budding (or asymmetric) speciation, bifurcating (or symmetric) speciation, and anagenetic speciation. Our equations allow for flexible joint Bayesian analysis of paleontological and neontological data. Furthermore, our framework is directly applicable to epidemiology, where a stratigraphic range is the observed duration of infection of a single patient, birth via budding is transmission, death is recovery, and sampling is sequencing the pathogen of a patient. Thus, we present a model that allows for incorporation of multiple observations through time from a single patient. (C) 2018 The Authors. Published by Elsevier Ltd.

【 授权许可】

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