Application of a Markovian ancestral model to the temporal and spatial dynamics of cultural evolution on a population network

Takahashi, Takuri; Ihara, Yasuo

doi:10.1016/j.tpb.2021.10.003

Cited by 1 publication

(3 citation statements)

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“…Models of coalescent process have gradually been adapted to cultural traits, and recent theoretical studies applied the coalescent process to the transmission of cultural traits [ 17 , 18 ]. We have previously developed a retrospective model of trait evolution in a network of populations [ 11 ], which is thus far the most relevant to the current study. The model we will describe in the current article is an extreme case of the structured coalescent with population size 1 for each subpopulation, the transmission among which is represented by a weighted network.…”

Section: Introductionmentioning

confidence: 99%

“…First, we will model the spatial structure of populations by a network where the nodes represent populations and the edges are weighted by the transmission rate of the cultural trait of interest. Second, following the ancestral process in a network described in Takahashi and Ihara [ 11 ], we will compute the prior probability of the history of cultural transmission over the past generations. Third, we trace the coalescent process of trait copies observed in the present generation, to obtain the genealogical tree whose taxa represent trait variants observed in different populations.…”

Section: Introductionmentioning

confidence: 99%

“…Transmission of cultural traits or social information in space has been modelled by means of networks [8][9][10][11], where the nodes represent either individuals or populations. Although the network is a powerful tool to represent the cultural transmission among populations, these previous models are mostly theoretical and hardly applicable to empirical data to make inference.…”

Section: Introductionmentioning

confidence: 99%

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Spatial evolution of human cultures inferred through Bayesian phylogenetic analysis

Takahashi

Ihara

2023

J. R. Soc. Interface.

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Spatial distribution of human culture reflects both descent from the common ancestor and horizontal transmission among neighbouring populations. To analyse empirically documented geographical variations in cultural repertoire, we will describe a framework for Bayesian statistics in a spatially explicit model. To consider both horizontal transmission and mutation of the cultural trait in question, our method employs a network model in which populations are represented by nodes. Using algorithms borrowed from Bayesian phylogenetic analysis, we will perform a Markov chain Monte Carlo (MCMC) method to compute the posterior distributions of parameters, such as the rate of horizontal transmission and the mutation rates among trait variants, as well as the identity of trait variants in unobserved populations. Besides the inference of model parameters, our method enables the reconstruction of the genealogical tree of the focal trait, provided that the mutation rate is sufficiently small. We will also describe a heuristic algorithm to reduce the dimension of the parameter space explored in the MCMC method, where we simulate the coalescent process in the network of populations. Numerical examples show that our algorithms compute the posterior distribution of model parameters within a practical computation time, although the posterior distribution tends to be broad if we use uninformative priors.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%