Spatial and Temporal Models of Jomon¯ Settlement Enrico R. Crema A Thesis submitted for the degree of Doctor of Philosophy Institute of Archaeology University College London January 2013 Declaration I, Enrico Ryunosuke Crema, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. 2 ”Ce qui est simple est toujours faux. Ce qui ne l’est pas est inutilisable” (P. Valery) ”All models are wrong, but some are useful” (George E.P. Box) Abstract 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 settle- ment pattern, primarily manifested as cyclical transitions between nucleated and dispersed distributions. Although it has been suggested that these events corre- late with population dynamics, shifts in subsistence strategies, and environmental change, to date there have been very few attempts to provide a quantitative anal- ysis 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 us- ing 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 nu- cleated 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 transmis- sion theory in order to provide explicit expectations in relation to the presence and 3 4 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. Contents VOLUME 1 I Introduction 34 1 Introduction 35 1.1 Problem Statement . 35 1.1.1 Jomon¯ Settlement Pattern . 36 1.2 Research Questions . 38 1.3 Aims and Objectives . 39 1.4 Scope and Limits . 40 1.5 Thesis Outline . 40 2 J¯omonCulture of Japan 42 2.1 Geographical Settings and Environment History . 46 2.2 Main Features of Jomon¯ Culture . 51 2.2.1 Chronology and Chronometry . 51 2.2.2 Subsistence Pattern . 55 2.2.3 Population Size . 63 2.2.4 Settlement Patterns . 67 2.2.5 Social Complexity . 77 2.3 Jomon¯ Settlement Pattern in Kanto¯ Region between 7000 and 3220 calBP..................................... 82 5 CONTENTS 6 2.3.1 Case Study Location and Environmental Settings . 83 2.3.2 Settlement Patterns between 7000 and 3220 cal BP in Chiba and Gunma . 87 2.4 Models of Change . 93 2.5 Summary . 103 II Pattern Recognition 105 3 Theory and Method: Spatial and Temporal Analysis 106 3.1 Spatial Dependencies . 106 3.2 Uncertainty in Archaeological Analysis . 114 3.2.1 Spatial Uncertainty . 116 3.2.2 Temporal Uncertainty . 121 3.2.3 Aoristic Analysis and Monte Carlo Simulation . 124 3.3 Detecting instances of Dispersed and Clumped Patterns . 131 3.3.1 Group Size Distribution Analysis . 132 3.3.2 Spatial Analysis . 137 3.4 Summary . 141 4 Applied Spatial and Temporal Analysis 143 4.1 Data Collection and Pre-processing . 143 4.1.1 Aoristic Analysis and Monte-Carlo Simulation . 146 4.2 Results . 147 4.2.1 Non-spatial Analysis . 148 4.2.2 A-Coefficient . 153 4.2.3 O-ring Function . 156 4.3 Discussion . 160 4.3.1 Early Jomon¯ (t7000-t5500)...................... 160 4.3.2 Middle Jomon¯ (t5500-t4500)..................... 161 4.3.3 Late Jomon(¯ t4400-t3400)....................... 166 4.4 Summary . 167 CONTENTS 7 III Model Building 169 5 Theory and Method: Computational Model Building 170 5.1 Settlement Patterns as a Complex Adaptive System . 178 5.1.1 Phase Space and Attractors . 185 5.2 Models of Group Formation . 188 5.2.1 Group Formation Dynamics . 198 5.3 Building the Model . 202 5.4 Implementing the Model in an Agent-Based Framework . 207 5.4.1 Decision-making . 208 5.5 Summary of the Model . 216 6 Applied Models of Endogenous Change 218 6.1 Experiment Design and Parameter Sweeps . 219 6.1.1 Visualising Simulation Outputs . 225 6.2 Results . 229 6.2.1 General Properties of the Model . 229 6.2.2 Parameter Sensitivity and Group Formation Dynamics . 238 6.2.3 Summary . 241 7 Applied Models with Disturbance Processes 245 7.1 Theoretical Introduction . 245 7.2 Modelling Disturbance . 251 7.2.1 Endogenic Disturbance: Predator-Prey Interaction Model . 252 7.2.2 Exogenic Disturbance: Temporal Variation of K ........ 255 7.3 Experimental Design . 256 7.4 Results . 259 7.4.1 Endogenic Disturbance Model . 260 7.4.2 Exogenic Disturbance Model . 264 7.5 Summary . 274 7.5.1 Endogenic Disturbance Model . 274 CONTENTS 8 7.5.2 Exogenic Disturbance Model . 276 IV Discussion and Conclusions 281 8 Discussion: the Pattern and Process of J¯omonSettlement Change 282 8.1 Empirical Data, Environmental Change, and Model Expectations . 283 8.2 Discussion . 303 9 Conclusions 317 BIBLIOGRAPHY 325 VOLUME 2 PLATES 374 Figures . 374 Tables . 476 APPENDICES 486 A Supplementary Data 487 B ODD Protocol of the Agent Based Simulation 628 B.1 PURPOSE . 628 B.2 ENTITIES, STATE VARIABLES, AND SCALES . 629 B.3 PROCESS OVERVIEW AND SCHEDULING . 630 B.4 DESIGN CONCEPTS . 630 B.4.1 Basic Principles . 630 B.4.2 Emergence . 631 B.4.3 Adaptation . 631 CONTENTS 9 B.4.4 Objectives . 631 B.4.5 Learning . 631 B.4.6 Sensing . 631 B.4.7 Interaction . 632 B.4.8 Stochasticity . 632 B.4.9 Collectives . 632 B.4.10 Observations . 633 B.5 INITIALISATION . 633 B.6 INPUT DATA . 633 B.7 SUB-MODELS . 633 B.7.1 Fitness Evaluation . 633 B.7.2 Reproduction and Death . 634 B.7.3 Fission-Fusion and Migration . 635 B.7.4 Variation of the Resource Pool Size K .............. 637 C ABM Code 642 C.1 Disturbance-free Model . 642 C.2 Predator-prey model . 654 C.3 Exogenic Disturbance Model . 657 D Parameter Space Visualisation 659 D.1 Disturbance-free model . 660 D.1.1 A-Coefficient (A).......................... 660 D.1.2 Number of Groups (G)....................... 666 D.1.3 Number of Agents (N)....................... 672 D.1.4 Median Group Size (λ~)....................... 678 D.2 Predator-prey model . 684 D.2.1 A-Coefficient (A).......................... 684 D.2.2 Number of Groups (G)....................... 702 D.2.3 Number of Agents (N)....................... 720 D.2.4 Median Group Size (λ~)....................... 738 CONTENTS 10 D.3 Exogenic Disturbance Model . 756 D.3.1 A-Coefficient (A).......................... 756 D.3.2 Number of Groups (G)....................... 762 D.3.3 Number of Agents (N)....................... 768 D.3.4 Median Group Size (λ~)....................... 774 List of Figures 1 Main political and administrative subdivision of Japan . 376 2 a terrestrial ecoregions (after Olsen et al. 2001, retrieved from: http: //www.worldwildlife.org/science/ecoregions/item1267. html; b: annual mean temperature (1950-2000, after Hijmans et al. 2005, retrieved from: http://www.worldclim.org/); c: el- evation (CGIAR-CSI SRTM 90m Database, retrieved from: http: //srtm.csi.cgiar.org); d: annual precipitation (1950-2000, af- ter Hijmans et al. 2005, retrieved from: http://www.worldclim. org/) of Japan. 377 3 Major environmental changes in the Japanese archipelago (notice that studies based on uncalibrated dates and mentioned in the text has been omitted). The dotted-square defines the temporal scope of the present study. 378 4 Location of the two case studies in Kanto¯ ................ 379 5 Case study at Chiba with elevation profile . 380 6 Case study at Gunma with elevation profile . 381 7 Uchiyama’s model of clumped and dispersed settlement pattern (above) and the suggested sequence in Northern and Southern Honshu,¯ (af- ter Uchiyama 2006: 140-141) . 382 11 LIST OF FIGURES 12 8 The concept of evolutionary trap. Individual a climbs the fitness landscape (1) and eventually reaches the global optimum (2, the highest peak), while individual b reaches a less adaptive local peak. This divergence is determined by small differences in the initial con- ditions (1). When environmental changes (3), individual b sees only a marginal decrease in its fitness, while individual a is strongly af- fected. ..