Integrative Bayesian Modeling of Bantu Expansion from Genetic and Linguistic Data

The Bantu expansion represents one of the most profound demographic and cultural transformations in African history, reshaping the linguistic, genetic, and cultural landscape of sub-Saharan Africa over several millennia. Reconstructing the intricate details of this expansion, including its precise timing, routes, and the extent of interaction with indigenous populations, remains a significant challenge due to the complex interplay of human migration, language diffusion, and gene flow. This paper proposes and elaborates on an integrative Bayesian modeling framework to synthesize diverse lines of evidence, particularly genetic and linguistic data, to provide a more comprehensive and robust reconstruction of the Bantu expansion. By combining rich genomic datasets, including modern and ancient DNA, with extensive linguistic lexical and phylogenetic information, this framework moves beyond traditional qualitative comparisons and sequential analyses. It aims to develop spatially explicit co-estimation models that rigorously test competing hypotheses regarding expansion scenarios, quantify the degree of demic diffusion versus cultural assimilation, and estimate key demographic parameters with robust uncertainty quantification. Such an approach offers a powerful means to account for inherent uncertainties in historical inference, providing probability distributions for parameters rather than single point estimates. This integrative strategy not only deepens our understanding of this pivotal African history but also establishes a valuable methodological paradigm for studying other large-scale human migrations globally, by offering a more unified and statistically supported narrative.