The Jomon culture is a tradition of complex hunter-gatherers which rose in the Japanese archipelago at the end of the Pleistocene (ca. 13,000 cal BP) and lasted until the 3rd millennium cal BP. Recent studies increasingly suggest how this long cultural persistence was characterised by repeated episodes of change in settlement pattern, primarily manifested as cyclical transitions between nucleated and dispersed distributions. Although it has been suggested that these events correlate with population dynamics, shifts in subsistence strategies, and environmental change, to date there have been very few attempts to provide a quantitative analysis of spatio-temporal change in Jomon settlement and its possible causes. This thesis is an attempt to fill that lacuna by adopting a twin-track approach to the problem. First, two case studies from central Japan have been examined using a novel set of methods, which have been specifically designed to handle the intrinsic chronological uncertainty which characterises most prehistoric data. This facilitated the application of a probabilistic framework for quantitatively assessing the available information, making it possible to identify alternating phases of nucleated and dispersed pattern during a chronological interval between 7000 and 3300 cal BP. Second, computer simulation (by means of an agent-based model) has been used to carry out a formal inquiry into the possible underlying processes that might have triggered the observed changes in the settlement pattern. The aim of this simulation exercise was two-fold. First, it has been used as a theory-building tool, combining several models from behavioural ecology and cultural transmission theory in order to provide explicit expectations in relation to the presence and absence of environmental disturbances. Second, the outcome of the simulation has been used as a template for linking the observed patterns to possible underlying socio-ecological processes suggested by the agent-based model. This endeavour has shown how some of the largest changes in the empirically observed settlement patterns can be simulated as emerging from the internal dynamics of the system rather than necessarily being induced by external changes in the environment
