Abstract

All large-scale human dispersals are complex: the units of migration (individuals, families, communities), the localised tempo and direction of dispersal, as well as the underlying drivers shifted frequently.

From around 4,000 BP, large-scale southern migrations expanded throughout sub-Saharan Africa resulting in major subsistence and cultural changes. The dispersal is associated with an ‘EIA cultural package’ consisting—wholly, or in part, at various times—of a more sedentary lifestyle, thick-walled pottery, iron metallurgy, cattle-keeping and crop cultivation. Some past archaeological studies have implicitly understood EIA expansion in sub-Saharan Africa as an expansion of a single, continuous event. However, cultural traits and subsistence strategies evolved through multiple interactions and shifting ecological environments. Whether the population spread continuously, in waves, or following a process of jumps remains an underlying question.

This paper explores the ‘EIA cultural package’ as a series of regional and complex movements, focusing on variations in the tempo of dispersal and arrival times of these traits within smaller geographic areas. The arrival times of these traits in geographic sub-regions are examined using a Bayesian ICAR model, where a hierarchical structure is introduced to account for the bias introduced by sample interdependence. The use of an ICAR structure allows the model to capture the underlying spatial autocorrelation in the data and provide broad arrival estimates in regions where we have no prior information. This framework is then built on by using Bayesian Wombling methods to consider if and how suitability to pastoralism and agriculture can explain the observed boundary differences in the dispersal process.

The results presented build a more detailed description of the localised dynamics of EIA communities in sub-Saharan Africa. Throughout, biases which influence the data—such as uneven spatial and temporal sampling density—are acknowledged and measurement uncertainty (calibration curve error and the sample’s C14 age error) is accounted for.

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