This book highlights new and innovative approaches to archaeological research using computational modeling while focusing on the Neolithic transition around the world.
The transformative effect of the spread and adoption of agriculture in prehistory cannot be overstated. Consequently, archaeologists have often focused their research on this transition, hoping to understand both the ecological causes and impacts of this shift, as well as the social motivations and constraints involved. Given the complex interplay of socio-ecological factors, the answers to these types of questions cannot be found using traditional archaeological methods alone. Computational modeling techniques have emerged as an effective approach for better understanding prehistoric data sets and the linkages between social and ecological factors at play during periods of subsistence change. Such techniques include agent-based modeling, Bayesian modeling, GIS modeling of the prehistoric environment, and the modeling of small-scale agriculture. As more archaeological data sets aggregate regarding the transition to agriculture, researchers are often left with few ways to relate these sets to one another.
Computational modeling techniques such as those described above represent a critical next step in providing archaeological analyses that are important for understanding human prehistory around the world. Given its scope, this book will appeal to the many interdisciplinary scientists and researchers whose work involves archaeology and computational social science.
Author(s): Salvador Pardo-Gordó, Sean Bergin
Series: Computational Social Sciences
Publisher: Springer
Year: 2022
Language: English
Pages: 273
City: Cham
Preface
Acknowledgments
Contents
Contributors
Chapter 1: An Introduction to Simulating Transitions to Agriculture in Prehistory
1.1 Modeling and the Spread of Agriculture
1.2 Computational Models in Archaeology
1.3 Computational Modeling and Complex Adaptive Systems
1.4 Benefits of Computational Modeling in Archaeology
1.4.1 Models Allow Replication
1.4.2 Models Enable Experimentation
1.5 About This Book
1.6 Conclusion
References
Chapter 2: The Spread of Agriculture: Quantitative Laws in Prehistory?
2.1 Introduction
2.2 Comparison of Neolithic Spread Rates
2.3 Relative Importance of Demic and Cultural Diffusion
2.4 Conclusions
References
Chapter 3: The Essential Geography of the Impresso-Cardial Neolithic Spread
3.1 Introduction
3.2 Material and Methods
3.2.1 The Impresso-Cardial Neolithic
3.2.2 Spatial Interpolation of Chronological Information
3.2.3 Radiocarbon Evidence in the West Mediterranean
3.2.4 Modelling the Essential Geography of the Neolithic Spread
3.3 Results
3.3.1 Individual Geographic Maps and Maximum Distance
3.3.2 Ranking Geographic Maps and Maximum Distance
3.4 Discussion
3.5 Conclusions
References
Chapter 4: A Bayesian Chronomodel for an Economic Approach to the Onset of Farming in Northwestern Mediterranean and the Western Alpine Foreland
4.1 Introduction
4.1.1 Archaeological Context
4.1.2 Archaeozoological and Archaeobotanical Context
Statistics to Model 14C Data. Bayesian Methodology as an Example
4.2 Material and Methods
4.2.1 Radiocarbon Dates Core
4.2.2 Student’s T-Test and Bhattacharyya Coefficient: Measuring the Distance Between the Stochastic Boundaries
Temporal Characterisation of the Hunter-Gatherer and Farming Groups Reality
Archaeobotanical and Archaeozoological Data Arranged According to the Scenarios of Interaction
4.2.3 Ecoregions with Scenarios Overlap
4.2.4 Ecoregions with Scenarios of No Overlap
4.3 Conclusions
References
Chapter 5: Assessing Population Dynamics in the Spread of Agriculture in the Mediterranean Iberia Through Early Warning Signals Metrics
5.1 Introduction
5.2 Archaeological Background
5.3 Materials and Methods
5.4 Results
5.5 Conclusions
References
Chapter 6: Cultural Hitchhiking in the Context of the First Agricultural Groups of South-Western Europe: A Simulation Study
6.1 Introduction
6.2 Cultural Spread: A Simple Model of Cultural Hitchhiking
6.2.1 Overview
6.2.2 Design Concepts
6.2.3 Details
6.3 Model Parametrization and Analyses
6.3.1 Parametrization
6.3.2 Analyses
6.4 Results
6.5 Discussion
6.6 Conclusions
References
Chapter 7: The Dynamics of Risk Perception in a Mediterranean Agroecosystem
7.1 Introduction
7.2 Decision-Making in a Game Against Nature
7.2.1 The Payoff Matrix
7.2.2 Subjective Expected Yields
7.3 Early to Mid-Holocene Drought Risks
7.3.1 Paleoclimate Simulation
7.3.2 Estimating Drought Risks
7.4 Modeling Risk Perception
7.4.1 Prior Beliefs and Bayesian Agents
7.4.2 Bayesian Updating and the Weight of Past Experience
7.5 Risk Management and the Dynamics of Risk Perception
7.6 Conclusion
References
Chapter 8: Early Neolithic Farming Activities in High Mountain Landscapes of the Pyrenees: Simulating Changes in Settlement Patterns
8.1 Introduction
8.2 Materials and Methods
8.2.1 Materials
Early Mesolithic (MESO I): 8500–6500 cal BC
Late Mesolithic (MESO II): 5725–5375 cal BC
Early Neolithic (E_NEO): 5600–4300 cal BC
Late Neolithic/Chalcolithic (L_NEO): 3400–2300 cal BC
8.2.2 Methods
8.3 Results
8.4 Discussion
8.5 Conclusions
Bibliography
Cartography
Chapter 9: Evaluating the Influence of Neolithic Agropastoral Land Use on Holocene Fire Regimes Through Simulated Sedimentary Charcoal Records
9.1 Introduction
9.1.1 Advancing Interpretations Through Simulations and Proxy Modeling
9.2 Background
9.2.1 Neolithic Revolution in the Mediterranean Basin
9.2.2 Case Studies of Social and Ecological Change During the Neolithic Period in Eastern Spain
Canal de Navarrés: Environmental and Cultural Background
L’Estany de Banyoles: Environmental and Cultural Background
Villena Paleolake: Environmental and Cultural Background
9.2.3 The Charcoal Record Simulation Model (CharRec)
9.3 Methods
9.3.1 Coring Locations, Deposition Rates, and Sedimentary Charcoal Data
9.3.2 CharRec Model Parameters
9.4 Results
9.5 Discussion
9.5.1 Long-Term Convergence and Divergence from Climate-Driven Fire Regimes in Eastern Spain
Canal de Navarrés
L’Estany de Banyoles
Villena Paleolake
9.6 Conclusions
References
Chapter 10: “Digital Proxies” for Validating Models of Past Socio-ecological Systems in the Mediterranean Landscape Dynamics Project
10.1 Models in Archaeology
10.1.1 Validating Models
10.2 The Mediterranean Landscape Dynamics Project
10.2.1 MedLanD Modeling Laboratory
10.3 Validating Socio-ecological Systems Models
10.3.1 Empirical Proxy Data and Analysis
10.3.2 Modeling Experiments and Digital Proxies
10.4 Results and Validation Tests
10.5 Conclusions
10.6 Access to Data and Analysis
References
Chapter 11: The Transition to Early Farming in Europe
11.1 Introduction
11.2 Transitioning in Space and Time
11.3 Returning to the LBK
11.4 Discussion
References
Index
