Journal of Theoretical Biology · 2018 · 152 citations · 25 references
Life SciencesBiologyEvolutionary BiologyEvolutionary TheoryPhylogeneticsSpeciationEvolutionary RelationshipsPhylogenetic AnalysisPhylogenetic Tree ReconstructionBirth-death ModelsFossil Taxon PlacementFossilized Birth-death ModelsFossilized Birth-death ProcessPhylogenetic Time TreesRange Evolution ModelsStratigraphic Range EstimationStratigraphic Range Extension
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.
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MRBAYES: Bayesian inference of phylogenetic trees
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BEAST 2: A Software Platform for Bayesian Evolutionary Analysis
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