The Dispersal of the Neolithic over the Arabian Peninsula 9781407305028, 9781407334868

Table of contents :
Drechsler_BAR_090602_600dpi_part1.pdf
1_BAR_Summary.pdf
2_BAR_Acknowledgments.pdf
3_BAR_ToC.pdf
4_BAR_Introduction.pdf
5_BAR_Chapter1.pdf
6_BAR_Chapter2.pdf
7_BAR_Chapter3.pdf
8_BAR_Chapter4.pdf
9_BAR_Chapter5.pdf
10_BAR_Appendix1.pdf
11_BAR_References.pdf
Drechsler_BAR_090602_600dpi_part2.pdf
1_BAR_Summary.pdf
2_BAR_Acknowledgments.pdf
3_BAR_ToC.pdf
4_BAR_Introduction.pdf
5_BAR_Chapter1.pdf
6_BAR_Chapter2.pdf
7_BAR_Chapter3.pdf
8_BAR_Chapter4.pdf
9_BAR_Chapter5.pdf
10_BAR_Appendix1.pdf
11_BAR_References.pdf
Front Cover
Title Page
Copyright
Dedication
SUMMARY
ACKNOWLEDGEMENTS
TABLE OF CONTENTS
INTRODUCTION
CHAPTER 1. ARCHAEOLOGICAL AND ENVIRONMENTAL BACKGROUND
CHAPTER 2. THE DISPERSAL OF THE NEOLITHIC - MODELS AND SIMULATIONS
CHAPTER 3. SIMULATING PATHWAYS OF DISPERSAL OVER ARABIA
CHAPTER 4. TRACING THE DISPERSAL ROUTES USING THE EVIDENCE FROM ARCHAEOLOGICAL REMAINS
CHAPTER 5. BRINGING IT ALL TOGETHER - COMPARISONS BETWEEN SIMULATIONS AND ARCHAEOLOGICAL EVIDENCE
APPENDIX 1
REFERENCES

Citation preview

l na tio ne di nli ad l o ith ria W ate m

BAR  S1969  2009   DRECHSLER   THE DISPERSAL OF THE NEOLITHIC OVER THE ARABIAN PENINSULA

The Dispersal of the Neolithic over the Arabian Peninsula Philipp Drechsler

BAR International Series 1969 9 781407 305028

B A R

2009

The Dispersal of the Neolithic over the Arabian Peninsula Philipp Drechsler

BAR International Series 1969 2009

Published in 2016 by BAR Publishing, Oxford BAR International Series 1969 The Dispersal of the Neolithic over the Arabian Peninsula © P Drechsler and the Publisher 2009 The author's moral rights under the 1988 UK Copyright, Designs and Patents Act are hereby expressly asserted. All rights reserved. No part of this work may be copied, reproduced, stored, sold, distributed, scanned, saved in any form of digital format or transmitted in any form digitally, without the written permission of the Publisher. ISBN 9781407305028 paperback ISBN 9781407334868 e-format DOI https://doi.org/10.30861/9781407305028 A catalogue record for this book is available from the British Library BAR Publishing is the trading name of British Archaeological Reports (Oxford) Ltd. British Archaeological Reports was first incorporated in 1974 to publish the BAR Series, International and British. In 1992 Hadrian Books Ltd became part of the BAR group. This volume was originally published by Archaeopress in conjunction with British Archaeological Reports (Oxford) Ltd / Hadrian Books Ltd, the Series principal publisher, in 2009. This present volume is published by BAR Publishing, 2016.

BAR PUBLISHING BAR titles are available from: BAR Publishing 122 Banbury Rd, Oxford, OX2 7BP, UK E MAIL [email protected] P HONE +44 (0)1865 310431 F AX +44 (0)1865 316916 www.barpublishing.com

FOR ANNA MAGDALENA

SUMMARY

SUMMARY

ZUSAMMENFASSUNG

Recent archaeological excavations in the southern part of the Arabian Peninsula uncovered growing evidence for the presence of domesticated sheep, goat and cattle in the 6th and 5th millennium cal BC. Considering the primacy of the subsistence strategy, the corresponding cultural complexes have to be termed Neolithic. Since a large proportion of the Arabian Peninsula lies beyond the natural habitat of the wild ancestors of these herding animals, the question about their origin arises. An extended review of the existing literature indicates two different positions to explain the origin of the Neolithic on the Arabian Peninsula. One posits a dispersal from the adjacent centre of domestication in the Levant, while the other favours an autochthonous development in Arabia. These two positions derive from different archaeological sources. The presence of domesticated sheep, goat and cattle in archaeological sites points to a Levantine origin of the Neolithic. In contrast, part of the material culture belonging to these inventories supports local cultural developments. To resolve this apparent dilemma, the history of research has been reviewed in detail. It demonstrates that preconceived notions about the prehistory of Arabia emerge not only from archaeological findings, but also from the influence of changing research paradigms. Despite the shifting foci of research, the results reveal a widely homogenous, basic pattern of the early and middle Holocene cultural complexes, which provides the foundation for a new way of structuring the Neolithic in Arabia. This new structure considers both the climatic history of the region and the evidence for the Levantine origin of the Arabian Neolithic. In contrast, the idea of a locally developed Neolithic in the southern part of the Arabian Peninsula is rejected based on the present archaeological evidence.

Neue archäologische Ausgrabungen im Süden der Arabischen Halbinsel ergeben zunehmende Hinweise auf die Nutzung domestizierter Schafe, Ziegen und Rinder als wesentlicher Beitrag zur Subsistenz während des 6. und 5. Jahrtausends v.Chr. Das Vorkommen dieser domestizierten Tiere erlaubt es, die entsprechenden Fundkomplexe als neolithisch anzusprechen. Da weite Teile der Arabischen Halbinsel außerhalb der natürlichen Verbreitungsgebiete der Wildformen dieser Tiere liegen, ist die Frage nach dem Ursprung dieses arabischen Neolithikums Gegenstand des aktuellen wissenschaftlichen Diskurses. Eine Zusammenschau der gegenwärtigen Literatur legt zwei gegensätzliche Positionen zur Herkunft des Neolithikums der Arabischen Halbinsel offen. Entweder wird eine autochthone Entwicklung in Arabien als Erklärungsmodell herangezogen, oder es wird von einer Ausbreitung des Neolithikums aus der Levante ausgegangen. Ihren Ursprung haben diese zwei unterschiedlichen Ansätze in gegensätzlichen archäologischen Quellen. Während das Vorkommen von domestizierten Tieren auf eine levantinische Herkunft des Neolithikums verweist, zeigen andere Teile der materiellen Kultur lokale Entwicklungen an. Um diesen scheinbaren Gegensatz aufzulösen, erfolgt im ersten Teil des Buches eine Aufarbeitung der Forschungsgeschichte. Dabei kann demonstriert werden dass der gegenwärtige Diskurs im Fach nicht nur das Ergebnis archäologischer Funde, sondern auch unterschiedlicher Lehrmeinungen und Forschungsinteressen ist. Unabhängig von diesen Unterschieden lässt sich jedoch eine homogene Grundstruktur in den unterschiedlichen Ansätzen zur Gliederung der früh- und mittelholozänen Kulturerscheinungen in Arabien feststellen. Diese bildet den Ausgangspunkt für eine neue Terminologie, welche sowohl dem Vorherrschen der neolithischen Wirtschaftsweise in Arabien und ihrem Ursprung in der Levante als auch der Klimageschichte der Region Rechnung trägt. Im Gegensatz dazu wird die Idee einer lokalen Entwicklung des Neolithikums in Arabien auf der Basis der gegenwärtigen archäologischen Befundsituation verworfen.

Accepting the contribution of the Levantine Neolithic to the prehistory of the Arabian Peninsula and unmasking local development as a myth, I place the focal point of this book around the investigation of potential dispersal routes from the Levant. Because archaeological evidence is generally sparse in most parts of Arabia, a computer simulation implemented into a GIS has been developed which incorporates ideas from the fields of innovation diffusion research and ecology. The results of this simulation indicate two different pathways out of the Levant: a western dispersal along the Red Sea coast and an inland route crossing the Arabian Peninsula from northwest to southeast. Based only on spatial, environmental data sets and simple dispersal rules, the emerging picture is well supported by the archaeological finds in Arabia which resemble Levantine material remains. Spatial similarities between the simulations and the archaeological evidence support the view of an environmentally dependent process of the Neolithic dispersal. Furthermore, it is suggested that a period of increased aridity occurring between 6500 and 6000 cal BC in the lower latitudes has an impact on this dispersal. During this time, a bottleneck situation led to the development of the Middle Neolithic composed of both indigenous Arabian and foreign Levantine elements.

Nachdem der levantinische Ursprung des arabischen Neolithikums aufgezeigt ist, stellt sich die Frage nach den möglichen Ausbreitungswegen. Da die archäologische Evidenz in weiten Teilen der Arabischen Halbinsel zu gering ist, um potentielle Ausbreitungswege direkt aufzuzeigen, wird ein Modell der Ausbreitung auf der Basis von Forschungen zur räumlichen Diffusion von Innovationen und ökologischen Forschungsansätzen entwickelt. Die Umsetzung dieses Modells in ein Computerprogramm, welches in ein Geographisches Informationssystem implementiert ist, erlaubt die Simulation von Ausbreitungswegen auf der Basis der lokalen naturräumlichen Gegebenheiten und einfacher Ausbreitungsregeln. Die Ergebnisse der Simulationen deuten auf zwei unterschiedliche Ausbreitungswege des Neolithikums von der Levante über Arabien hin. Ein westlicher Weg folgt, von der südlichen Levante ausge-

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA hend, der Küste des Roten Meeres nach Südwestarabien. Ein zweiter, östlicher Weg dagegen quert den nördlichen Teil der Arabischen Halbinsel von Nordwest nach Südost. Dieses aus den Simulationen gewonnene Ergebnis spiegelt die räumliche Verteilung archäologischer Funde wider, welche stilistische Ähnlichkeiten mit levantinischem Fundmaterial zeigen. Somit bestätigt die archäologische Evidenz nicht nur die beiden durch die Simulationen gefundenen Ausbreitungswege, sondern gleichzeitig auch die der Simulation zugrunde liegende Annahme eines umweltabhängigen Ausbreitungsprozesses. Im weiteren Verlauf der Arbeit werden Unterschiede zwischen den Ergebnissen der Simulationen und der räumlichen Verteilung archäologischer Funde mit einer Phase sich verschlechternder klimatischer Verhältnisse zwischen 6500 und 6000 v.Chr. in Verbindung gebracht. Es wird vorgeschlagen, dass es zu dieser Zeit, welche als eine „ökologische Flaschenhals-Situation“ betrachtet werden kann, zur Herausbildung des Mittelneolithikums gekommen ist, welches sich in Subsistenz und materieller Kultur sowohl durch indigene arabische als auch levantinische Elemente auszeichnet.

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ACKNOWLEDGEMENTS

ACKNOWLEDGEMENTS

Many thanks are owed to the people who contributed to this book. From the first ideas about the Neolithic dispersal to the final stages of this work, the many lecturers and associates of the Institute of Pre- and Protohistory and Medieval Archaeology in Tübingen were instrumental: Michael Bolus, Monika Doll, Harald Floss, Miriam Haidle, Peter Jablonka, Claus-Joachim Kind, Hansjürgen Müller-Beck, Konstantin Pustovoytov, Simone Riehl, Jordi Serangeli, Margarethe Uerpmann and Ullrich Veit. Invaluable support also came from the Institute of Geography. HansJoachim Rosner and Thomas Blaschke taught me the use – and abuse – of Geographic Information Systems during my early years as a student in Tübingen. Volker Hochschild was always open to my questions and an inspiring discussant during the later stages of this research.

Many people have contributed to the pages of this book, through their stimulating discussion, plentiful advice, practical hints and often tremendous efforts. In fact, some were not even aware of their contribution. First and foremost, I thank my advisor, Hans-Peter Uerpmann. Hans-Peter is not only an exemplary teacher who deeply affected my perception of archaeological phenomena. He also became my mentor and confidant. It is further to his credit that his faith in my work was accompanied by a certain degree of criticism. Although always justified in its content, and never unfair, his comments forced me to look beyond established doctrine. Today, I cannot adequately express in words my gratitude for his strictness. I hope to repay this debt in the future, by striving to be an educator such as he was to me.

Of course, no one else can be held accountable for any deficiencies in the work: these are wholly my responsibility.

The second person who influenced my academic training was Nicholas Conard. It is especially his pursuit of theorydriven approaches to answer research questions and his emphasis on the importance of the history of research that found their greatest echoes in my work. I am grateful that he was willing to act as the second academic supervisor, working through the entire body of this dissertation.

During the last three and a half years I spent much time in the Institute. Here, I often pestered many friends with stupid questions, useless comments and my obsession with the Neolithic dispersal. I would like to thank all of you for your patience and tolerance: Felix Hillgruber, Knut Bretzke, Johannes Kutterer, Martina Barth, Michael Francken, Roland de Beauclair and Ursula Maurer.

Two colleagues made essential contributions to this research. The simulation of the dispersal of the Neolithic across the Arabian Peninsula, the centrepiece of this dissertation, required the development of a computer program. This was carried out by Dirk Tiede, who was responsive to all of my fanciful ideas. Thank you very much for your great effort. Financial support for computer programming came from the Joachim Hahn Stiftung. I am indebted to Hansjürgen Müller-Beck for his personal advocacy in obtaining this grant.

More than 20 years ago my mother signed me up for the Arbeitsgemeinschaft Junge Archäologen in Dresden. Since then my parents spent countless hours searching far and wide for archaeological monuments of every kind. I thank you for your generous and vital support and encouragement.

During the course of research, a major methodological step was the idea of using statistics to obtain information about human requirements with respect to environmental conditions. I would never have finished this dissertation without the brilliant support of Reinhard Vonthein. You were an incredible help.

Financial support for this research was provided by the Landesgraduiertenförderung Baden-Württemberg and the Deutscher Akademischer Austausch Dienst (DAAD).

Finally, I thank my wife Barbara. Without your encouragement, I never would have finished this book; and without your confidence, I never would have started it.

Andrew Kandel worked through the entire manuscript, correcting my sometimes crude English during the last phases of writing this dissertation. Not only was his revision outstanding, but he also strove for precision and uncovered major inconsistencies. Furthermore, he taught me the meaning of many foreign words – the most important one being “huh?”. For this, I am forever in your debt. This research benefited substantially from the two months that I spent visiting the University of Edinburgh. There, Tony Wilkinson supervised my studies. Thank you for your warm welcome, extended discussions and access to many original manuscripts and rare publications.

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA

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TABLE OF CONTENTS

TABLE OF CONTENTS Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Chapter 1: Archaeological and Environmental Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1 History of Research in Arabia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.1 Stone Age Research During the Early 20th Century . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2 Arabian Archaeology After the Oil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.3 The Present State of Research in Arabia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10 1.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14 2 The Holocene Prehistory of the Arabian Peninsula: Chronological and Spatial Structuring . . . . . . . . . . . . . . . . . .15 2.1 Established Chronological and Spatial Schemes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15 2.2 A New Proposal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21 3 Why Neolithic? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23 4 Early Herders on the Arabian Peninsula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24 4.1 Arguments for Autochthonous Developments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24 4.2 Evidence for the Spread of the Neolithic Herding Economy from the Levant . . . . . . . . . . . . . . . . . . . . . . . .25 5 Environmental Conditions as a Prerequisite for the Neolithic Dispersal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .29 6 The Advent of a Herding Economy in Arabia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31 7 Summary: The Dispersal of the Neolithic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34 Chapter 2: The Dispersal of the Neolithic - Models and Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 1 A Model for the Dispersal of Neolithic Herders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37 1.1 What are Models? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37 1.2 Current Models for Human Dispersals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38 1.3 Explanatory Concepts for the Dispersal of the Neolithic Over the Arabian Peninsula . . . . . . . . . . . . . . . . . .43 1.4 Innovation Diffusion as a Spatial Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .45 1.5 Innovation Diffusion or Population Movements? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .46 1.6 Possible Causes of Population Movement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .47 1.7 Environmental Conditions and Population Density as a Prerequisite for Spatial Dispersals . . . . . . . . . . . . .48 1.8 Freedom of Human Choice Versus Environmental Determinism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .49 1.9 Description of the Proposed Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .49 2 Transforming the Model Into a Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52 2.1 What are Simulations? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52 2.2 Geographic Information Systems as Simulation Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .53 2.3 Deterministic Versus Stochastic Spatially Explicit Models for the Simulation of Dispersal . . . . . . . . . . . . .54 2.4 The Significance of Geographic Space in Dispersal Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55 2.5 Simulation Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .56 2.6 The Simulation of Dispersal in Artificial Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .60 2.7 Analytical Possibilities for the Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .66 3 Summary: Use and Abuse of Models and Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67 Chapter 3: Simulating Pathways of Dispersal Over Arabia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 1 Environmental Conditions as an Imperative for the Neolithic Dispersal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69 1.1 Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70 1.2 Topography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .74 1.3 Hydrology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78 1.4 Pedology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .85 1.5 Vegetation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87 2 The Valuation of Environmental Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .88 2.1 Physiological Constraints in Animal Husbandry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .88 2.2 Statistical Results – Different Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .89 3 Simulating the Dispersal of the Neolithic from the Levant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .96 3.1 Exploration of Environmental Scenario 0:Uniform Environmental Conditions . . . . . . . . . . . . . . . . . . . . . . .97

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA 3.2 Exploration of Environmental Scenario 1: Statistical Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .98 3.3 Exploration of Environmental Scenario 2: Valuation of Hydrological Conditions . . . . . . . . . . . . . . . . . . . . .99 3.4 Exploration of Environmental Scenario 3: Restricted Set of Environmental Conditions . . . . . . . . . . . . . . .100 4 Excursus: Simulating Alternatives - Spreading Routes from East Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .105 5 Climatic Oscillations and their Impact on the Neolithic Dispersal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .107 5.1 Simulation Results and Archaeological Evidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .107 5.2 The Impact of Rapid Climatic Changes in Arabia on the Neolithic Dispersal . . . . . . . . . . . . . . . . . . . . . . .107 6 Summary: Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .108 Chapter 4: Tracing the Dispersal Routes Using the Evidence from Archaeological Remains . . . . . . . . . . . . . . . . . . . 111 1 Description of the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .111 1.1 Data Sources and Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .111 1.2 Spatial Distribution Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .113 1.3 Chronological Resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .114 1.4 Typology and Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .114 2 The Chrono-Spatial Distribution of Sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .115 3 The Chrono-Spatial Distribution of Chipped Stone Arrowheads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .123 3.1 Stylistic Variability in Space and Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .125 3.2 Attribute Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .126 3.3 Stylistic Analysis of Arrowheads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .136 3.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .143 4 Additional Material Evidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .144 4.1 Spatio-Temporal Distribution of Sickle Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .144 4.2 Spatio-Temporal Distribution of Blades . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .146 5 Redefining the Neolithic of the Arabian Peninsula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .147 5.1 The First Episode – Evidence for Hunter-Gatherers at the Onset of the Holocene . . . . . . . . . . . . . . . . . . . .147 5.2 The Second Episode – The Dispersal of the Neolithic across Arabia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .149 5.3 The Third Episode - Chronological Gap and Ecological Bottleneck . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .151 5.4 The Fourth Episode – The Arabian Middle Neolithic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .152 5.5 The Fifth Episode – End of the Holocene Moist Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .154 6 Summary: The Material Evidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .154 Chapter 5: Bringing it All Together - Comparisons Between Simulations and Archaeological Evidence . . . . . . . . . 158 1 Are Comparisons Possible? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .158 2 What Do the Simulations Indicate? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .159 3 What Does the Archaeological Evidence Suggests? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .161 4 Summary: Bringing it All Together . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .163 Appendix 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 Please note that the CD referred to throughout the text has now been replaced with a download available at www.barpublishing.com/additional-downloads.html

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INTRODUCTION

INTRODUCTION

“And a new way of seeing…can in its own right make an original contribution to science.” (Dawkins 1989)

was, with immense regions untouched by archaeological studies. Filling these gaps by applying an inductive approach to the sparse data seemed inappropriate; the danger to end up writing ‘palaeo-poetry’ was too high.

The dispersal of cultural elements in space and time represents one of the most inspiring occurrences in the record of prehistoric archaeology. Researchers have proposed several concepts to explain the emergence of new technologies, types and modes of subsistence. These explanations tend to culminate in the scientific dispute about whether the new trait developed locally or was introduced from abroad. The driving force behind this debate is often the question of the first or oldest occurrence of a specific characteristic. The area where an artefact first occurred determines the “centre of innovation”, while all other regions are consequently considered as being “behind the times”. Current examples of this scientific interest include the dispersal of modern humans in the Old World, the first occurrence of figurative art, the peopling of the Americas, and the origin and spread of the Neolithic.

Therefore, it has been decided to choose a different approach. I was convinced that human behaviour in general is related to the physical environment. This dependence on environmental conditions should increase as the environment becomes less favourable. I chose to understand the environment as the stage on which humans act and interact in specific and comprehensible ways. This dependence of human actions on environmental conditions forms the background for establishing a conceptual model that determines the parameters important to the Neolithic dispersal over Arabia. In a second step the model has been transformed into a computer simulation that generated its own data. This model output was then compared with the archaeological evidence. It is this invention that allows for a more accurate interpretation of the archaeological data. If matching patterns are noted, the probable mechanisms behind the observed dispersal process have been identified. Such a result could not be attained using just the sparse archaeological material. Although the mere agreement of archaeological findings and simulation results cannot validate the proposed model, it does help to understand the depiction of the archaeological evidence.

The research presented in this book fits directly within the fields outlined above. Inspired by excavations carried out at the Neolithic graveyard of Buhais-18, this work deals with the appearance of the Neolithic on the Arabian Peninsula. Buhais-18 is located at the south-eastern tip of the Arabian Peninsula, on the corner of this vast landmass opposite the Levant. The excavation at this site was established as a joint project of the Directorate of Antiquities of Sharjah Emirate (United Arab Emirates), and the Institute of Pre- and Protohistory and Medieval Archaeology of Tübingen University, directed by Sabah Aboud Jasim, and Hans-Peter and Margarethe Uerpmann. Yearly excavations were conducted between 1996 and 2005. As a graduate student of Hans-Peter Uerpmann, I was given the opportunity to participate in the excavations between 1999 and 2001. During this time, the age of this graveyard was a topic of major debate. A number of radiocarbon dates obtained from fireplaces associated with the graveyard indicated an age of more than 6000 years before present. However, the high number of animal remains from domesticated sheep, goat and cattle seemed to question this early chronological determination. Was this the first middle Holocene site with a find complex dominated by domesticated animals in the interior of the Arabian Peninsula? And if so, from where did its inhabitants originate? These questions were repeatedly discussed during breakfast at the site, as we took in the beautiful view across the graveyard and towards the stark ridges of the Hajar Mountains. During this time I became intrigued by all things Arabian, gaining a deep interest in the Neolithic and the relationship of spatial phenomena to human behaviour. Fortunately, after I completed my Master’s thesis, Hans-Peter Uerpmann offered me the opportunity to write a dissertation about the dispersal of the Neolithic over the Arabian Peninsula.

Two major developments during the last years have made this approach possible, the first being the increasing number of remote sensing data available on a continental scale. Earth scientists have taken advantage of these data for the exploration of remote areas for a long time. However, the main application for archaeologists still remains the identification of areas of archaeological interest using colour, airborne images. Other remote sensing data such as digital elevation models and ground penetrating radar have been applied to a much lesser extent. In this dissertation, remote sensing data are explicitly employed to obtain environmental information about areas too large for groundbased investigations. Although the spatial resolution of the available environmental data sets continues to increase, the character of the remote sensing data remains the same as for a conventional map. The data represent a model of a specific part of the earth’s surface, and thus, compel to generalise and simplify. The second development concerns the introduction of information technology in the earth sciences. Considerable hype was made with the advance of geographic information systems (GIS), an invaluable tool that widely extended the analytical possibilities in the spatial dimension. These systems of complex software allow for the sophisticated storage, modification, analysis and display of spatial data.

My first glimpse of the existing publications revealed how sparse the archaeological evidence for this research topic

1

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA with an inductive approach. The scanty amount of archaeological material does not speak for itself. As a consequence a simulation has been developed to compute data independent of the archaeological material and subsequently test these data against the archaeological evidence. The conceptual model behind the simulation considers the physical environment as one important factor for the dispersal of human groups by limiting freedom of decisions with respect to possible dispersal routes. The second aspect of the dispersal in the conceptual model refers to human behaviour itself, an attribute which has previously been confined to its explicit spatial aspects.

Without the existence of such a tool, the analyses required could not be performed.

The general research question followed during the course of the dissertation can be summarised as the following: Does the Neolithic in Arabia originate in the Levant? To approach this question, several facets of this topic have been investigated. The first aspect considered is the most fundamental one with respect to the general research question: What is the archaeological material evidence for the Neolithic dispersal over Arabia, and where did it originate? A review of the research history in Arabia reveals that systematic archaeological investigation in Arabia remains incomplete even today. On the Arabian Peninsula beyond their natural habitat, the presence of domesticated sheep, goat and cattle in archaeological contexts dating to the 6th and 5th millennia cal BC is one compelling piece of evidence in favour of a Levantine origin for the Neolithic. Along the hilly flanks of the Taurus and Zagros Mountains north of the Arabian Peninsula the natural habitats of sheep, goat and cattle overlap. The first evidence for the domestication of these animals comes from this region. Thus it is plausible that the Arabian domesticated animals derive from Levantine livestock. Additional support for the thesis of a Levantine origin of the Arabian Neolithic comes from the stone artefact assemblages discovered on the Arabian Peninsula that closely resemble Levantine PrePottery Neolithic inventories. Considering these arguments, the evidence that can be obtained from the literature about the Neolithic dispersal from the Levant is more suggestive than demonstrative.

To consider the importance of diverse sets of environmental data with respect to basic human needs, statistics have been employed to calculate dispersal surfaces. These surfaces depict the favourability of local environmental conditions for dispersing human population groups. Environmental data that have been integrated into the analysis include precipitation pattern, ground frost days, elevation, topographic basins, hydrological conditions, soil fertility, topographic wetness, river corridors and sea coasts. The basis for the statistical procedure is the location of known archaeological sites. These sites are understood to be situated in the most appropriate location with respect to their immediate surroundings. Using the logistic regression technique, areas can be calculated which closely resemble the conditions prevailing at the archaeological sites. It is assumed that dispersing human population groups will follow routes along environmental corridors that are similar to the already inhabited areas; which are those that require a minimum of adaptation. These calculated surfaces were then applied as dispersal surfaces during the simulations. In the simulations human behaviour is restricted to three basic aspects. First, to account for both the freedom of human decisions and the unknown element of behaviour expected for the dispersal, a random component has been implemented in the simulation procedure. Second, any dispersal is assumed to first cover regions directly adjacent to the original centres before it reached more peripheral areas. Third, dependencies between dispersal distance and population density have been considered with respect to local environmental conditions.

If one accepts the Levantine origin for the Arabian Neolithic, the next question which has to be answered is: How did it happen? Here, two opposing, general, explanatory concepts are provided in the archaeological, social and geographic sciences. In their most extreme form, the first concept stipulates the migration of people together with their material culture as the driving force behind the dispersal of material and economic traits, while the second concept accounts for the dispersal of innovations, but denies the physical movement of human populations. Based primarily on the weak evidence for the presence of people on the Arabian landmass at the onset of the Holocene, a necessary prerequisite for the dispersal of innovations, I chose to prioritise the first concept in this thesis. At the current state of research, I consider the mobile herders originating at the steppic margin of the Mediterranean and Southern Levant as the most likely bearers of the Neolithisation of Arabia.

As suggested by the archaeological evidence, the origin of the dispersal over Arabia should have been along the southern and south-eastern fringes of the Levant. Applying these assumed areas as starting points for the dispersal, two different pathways emerge from the simulations. One route develops down the Red Sea corridor towards south-western Arabia. A second route crosses the northern Arabian Shield towards the east and then turns southwards when it reaches the Arabian Gulf coast.

The third focus of this dissertation investigates the Neolithic dispersal over Arabia as a spatial process: What are the most advantageous routes the Levantine Neolithic herders could have taken during the dispersal? As a consequence of the fragmentary archaeological evidence in Arabia, it is not possible to pursue this question

To identify the dispersal routes suggested by the simulations in the archaeological record, an extensive analysis of chipped stone arrowheads, the most comprehensively documented artefact category in Arabia, has been conducted. The comparison between the simulation results and ar-

2

INTRODUCTION this climatic event influenced the prehistory of Arabia. It forced the dispersing Levantine Neolithic herders to retreat into spatially restricted, environmentally favoured areas within Arabia. Because these areas are presumed to be the same regions where indigenous groups withdrew during this period, interactions between the Levantine herders and indigenous hunter-gatherers are postulated. It is proposed that this interaction resulted in the emergence of the cultural complexes of the Arabian Middle Neolithic after the end of this dry phase.

chaeological evidence reveals both similarities and differences. The successful detection of material evidence for both routes not only supports the simulation results, thus validating the two dispersal routes, but confirms the assumption of the conceptual model of an environmental dependent process as well. The Neolithic dispersal over the Arabian Peninsula has to be considered as a process which was closely bound to local environmental conditions. This finding is not challenged by apparent discrepancies between the simulation results and the archaeological evidence. While the simulations indicate a continuous dispersal over the entire Arabian landmass along the eastern dispersal route, archaeological assemblages reminiscent of the Levantine PPNB cannot be found further south than 23° northern latitude. This contradiction can be resolved by considering the changing climatic conditions that are not incorporated into the simulations. A period of ameliorating climatic conditions during the second half of the 7th millennium cal BC might have been responsible for the disappearance of the Levantine Neolithic dispersal in the Southern Arabian archaeological record.

Chapter 2 discusses the conceptual model which was developed to consider the Neolithic dispersal from the Levant as a spatial process. This model is characterised by the following assumptions: (1) An explicit, initial area of the dispersal origin is postulated. Based on archaeological evidence, this area is located in the southern part of the Levant. (2) The dispersal starts within this centre and continues to the spatially adjacent periphery. (3) The probability of the occurrence of Neolithic mobile herders is highest in the direct neighbourhood of precedent Neolithisation. It is more likely that “roaming herding groups” are populating nearby places than places far away. (4) Environmental conditions deteriorate in a given area with respect to the presence of human populations. (5) Local environmental conditions influence human spatial behaviour: unfavourable environmental conditions promote fast movement and low population density, while favourable environmental conditions support a higher population density and slower rates of movement.

The structure of this book follows the research agenda outlined above: Chapter 1 describes the history of research in Arabia in detail. It is demonstrated that the present perception of the prehistory of this region is not only the result of archaeological findings but also influenced by changing research paradigms. While some scholars highlight the importance of autochthonous developments, others tend to emphasise the significance of foreign influences. Despite these different foci, a widely homogenous, basic structuring of the early and middle Holocene cultural appearances has been revealed, which provides the basis for a new structuring of the cultural complexes. In addition, new terminology for the early and middle Holocene has been developed to accentuate the appearance of the Neolithic in Arabia: Considering the primacy of the subsistence strategy in the definition of the Neolithic period, the classification of the respective cultural complexes is based on the presence of domesticated sheep, goat and cattle during the 6th and 5th millennia cal BC in Arabia.

This conceptual model has been transformed into a computer simulation to calculate the most probable dispersal ways using a GIS software environment. The core of the simulation is the generation of random points spatially arranged in a circular manner around the parent point. These random points interact dynamically with a virtual dispersal surface that represents the local environmental conditions. The spatial behaviour of this simulation is tested using several different environmental configurations to highlight and explain the strengths and weaknesses of the simulation. Chapter 3 provides details about the dispersal simulations performed with respect to the environmental situation on the Arabian Peninsula. A necessary prerequisite for this is the calculation of dispersal surfaces that reflect and combine environmental parameters identified as important to the dispersal of Neolithic herders.

Due to the distribution of the natural habitats of the wild ancestors of these animals and their original centres of domestication, the origin of the Arabian Neolithic must have been located on the northern fringes of the Arabian Peninsula and the Levant. A necessary prerequisite for the Neolithic dispersal from these regions was a phase of ameliorating climatic conditions both in the northern and southern parts of the Arabian Peninsula, which enabled mobile herders to roam this vast landmass. This phase was interrupted by a short climatic event taking place during the second half of the 7th millennium cal BC which led to increased aridity in the lower latitudes. It is suggested that

First, the environmental parameters are described with regard to their characteristics on the Arabian Peninsula. In each case, a brief description provides information about the origin of the sources of data and how it was processed. The impact of the environmental parameters with reference to present day mobile herders in the subtropics of Africa and Arabia is presented to provide support for the importance of the different parameters. It is demonstrated

3

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA that the ethnographic evidence alone is not sufficient to create the dispersal surfaces essential for the simulations. Therefore, a statistical procedure has been used to calculate the dispersal surface based on the logistic regression technique. Applying this procedure to different combinations of environmental data sets, three altogether different, environmental scenarios were calculated. These scenarios were used for the simulation experiments applying a wide range of different dispersal rules. Chapter 4 attempts to trace the dispersal routes suggested by the simulations by archaeological evidence. Two different approaches were used. First, a general analysis of the spatio-temporal occurrence of archaeological sites was conducted. Second, the spatial and temporal distribution of arrowheads as the most comprehensively documented artefact class was investigated in detail. During the course of the latter analysis, significant patterns were identified which support the dispersal routes calculated by the simulations and the structuring of the early and middle Holocene introduced in chapter 1. The spatio-temporal occurrence of arrowhead traits and specifications reveals connections between the north-western fringes of the Arabian Peninsula, the assumed centres of the origin of the Arabian Neolithic, and south-western Arabia. Further connections were identified between north-western and eastern Arabia. Placed in the 7th and beginning of the 6th millennia cal BC, these findings confirm the hypothesis of the Neolithic dispersal from the Levant across Arabia. A considerable change is recognised during the 6th and 5th millennia. At that time, connections between the Levant and the majority of the Arabian Peninsula weakened, while the occurrence of identical arrowhead styles in almost all environments of the peninsula indicates strong intra-Arabian relations. This changing pattern is explained by the emergence of a mobile herding strategy exploiting different habitats, as explicitly shown for the site of Buhais-18. The concluding chapter 5 summarises and compares the separate results of the dissertation. Emphasis is placed on the question of whether the simulation results and archaeological data can be directly compared. An affirmative answer is argued based on the fact that the simulations consider real-world data. The comparison indicates similarities between the simulated dispersal routes and the archaeological evidence. Therefore, it is suggested that the most probable dispersal routes for the Neolithic have been identified. The similarity in results obtained from two distinct sources of data – simulations and archaeological finds – confirms the validity of the conceptual model for the dispersal. It also identifies the local environment as the single, most influential, spatial parameter for the dispersal of the Neolithic over the Arabian Peninsula.

4

CHAPTER 1

CHAPTER 1

The late stone age occupants left their works everywhere. It is almost impossible to travel in the desert without finding worked flint. Those people travelled too. (Golding 1974:19)

ARCHAEOLOGICAL AND ENVIRONMENTAL BACKGROUND was carried out favoured the establishment of local research foci that were not necessarily comparable with other areas. Differences in the scientific approach enforced this development and led to historical interpretations that are not readily comparable

A new approach to explain the prehistory of Early Holocene Arabia requires careful evaluation of past and present research paradigms since these influence the perception of current knowledge. By a detailed analysis of the history of research in Arabia it has been revealed that the present doctrine concerning the course of the Neolithic in Arabia is the result of an ongoing repetition of paradigms based on rather meagre archaeological evidence. As the result of these prevailing views there has been only little space for innovative approaches in this area of research during the last decades.

The following chapter describes the history of archaeological research on the Arabian Peninsula from the beginning of the 20th century up to the present in an approximately chronological order. It will be demonstrated that the current interpretation of Arabia’s past is based not only upon the material culture that is found in the patchy remains of its past inhabitants, but is also influenced by the training and background of researchers, political circumstances, access to areas by archaeologists and chance. It will be focused on research covering the period from the end of the Pleistocene to the middle of the Holocene. The emerging picture then will be further used to compare and evaluate different approaches to structure and interpret the Holocene history of the Arabian Peninsula.

After outlining the history of research and briefly discussing the present attempts to structure the Early and Middle Holocene prehistory of Arabia chronologically and spatially, the question of a local origin of domestication on the Arabian Peninsula will be discussed. It will be argued that a local origin of domesticated animals in Arabia is hardly plausible. The incidence of the wild ancestors of domesticated animals does not correspond to the observed distribution of domesticated animals during the Arabian Neolithic. Therefore, while searching for the origin of the Arabian Neolithic it has been looked at the spatially adjacent main centres of early domestication: towards the flanks of the Zagros and Taurus Mountains. Starting from these regions, the Neolithic spread southward, first penetrating the southern Mediterranean Levant and later the northern fringes of the Arabian Peninsula. In the transitional zone between the Mediterranean and the steppic zones in the east, a mobile herding economy became established at the end of the Pre-Pottery Neolithic of the Levant. This mode of subsistence appears to have been a necessary prerequisite for the successful dispersal of the Neolithic across Arabia. Finally, based on already established chronological schemes, a new classification of the Early and Middle Holocene prehistory in Arabia will be proposed that integrates and unifies the present chronological and spatial structuring.

1.1 STONE AGE RESEARCH DURING THE EARLY 20TH CENTURY The beginning of systematic investigations on the Stone Age of the Arabian Peninsula date to the 1920s when the recent defeat of the Ottoman Empire opened up previously restricted areas in the interior of Arabia. The first investigations in prehistoric archaeology were carried out by H. Field in 1925 at the northern edge of the Arabian Peninsula during a stop at landing field H between Amman and Baghdad. Field collected several stone artefacts that fuelled five extensive expeditions into the northern Arabian Desert during the following years (1926-1928, 1934, 1950). During these expeditions Field (1960) gathered a wide range of data concerning archaeology, ethnography, geography and geology. The area investigated stretches from the Jordan Highlands east of the Dead Sea to Rutba in the interior of the Arabian Desert in Iraq, with shorter trips to Turaif in the south. D. Garrod studied the flint implements collected during these investigations and pointed out the similarities of these stone artefacts with materials from Levantine sites, with which she was familiar. Concerning the Neolithic material, she observed the absence of sickle blades in the assemblages, while accounting for all other elements of the Levantine Neolithic (Garrod 1960:124).

1 HISTORY OF RESEARCH IN ARABIA The history of archaeological research in Arabia is as complex as the history of the region itself. Arabia stretches from the shores of the Arabian Gulf in the east to the Red Sea in the west, and from the Indian Ocean in the south to the riverbanks of the Euphrates in the north. During the last century the Arabian Peninsula attracted numerous archaeologists with a wide range of academic training for a variety of reasons. But due to the vastness of the area and its restricted accessibility, research remained fragmented. The remoteness of the various locations where research

Based on the striking evidence for the presence of people in the northern Arabian Desert during several periods in prehistory, Field concludes that this area was more fertile

5

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA during prehistoric times and hence well accessible. This contradicted the prevailing opinion of that time, which considered this region as a general geographic barrier to ancient migration (Field 1960c:127).

beyond that suggests looking eastward to find related material (Caton-Thompson 1953:218).

At about the same time, H. Rhotert began exploring the Arabian Peninsula from the north. His research interests concerned the petroglyphs and stone artefacts discovered in 1932 within the Jebel Tubaik region near the border with Jordan and Saudi Arabia. During Rhotert’s reconnaissance in 1934, he collected 2854 stone artefacts and classified them within the recently established framework of the Levantine Palaeolithic and Neolithic (Garrod & Bate 1937, Rust 1933, cf. Rhotert 1938:2). Since all artefacts were collected from the surface, Rhotert was faced with chronological problems. Of special interest in regard to the Neolithic are his finds from the so called “Zentralfundplatz 19” where arrowheads, burins, blades and bipolar cores indicate the presence of a substantial Pre-Pottery Neolithic B1 (PPNB) settlement (Rhotert 1938:86pp.).

THE EARLY COLLECTIONS IN CENTRAL ARABIA

The earliest information about the presence of lithic tools from the interior of the Arabian Peninsula comes from Harry Philby, who in 1932 crossed the sand sea of the Rub‘ al-Khali, the “Empty Quarter” that covers a vast part of southern Arabia. In the tradition of explorers of the 18th and 19th century, Philby’s primary concern was to conduct a reconnaissance of the unknown territory. Philby lost the race to cross the Rub‘ al-Khali as the first western explorer to Bertram Thomas, who travelled from Salalah (Dhofar) to Doha (Qatar, Persian Gulf) in 1931. Philby started from the south in Riyadh and collected botanical specimens during his journey, as well as lithic tools and pottery. Although more of an adventurer than a scientist, Philby (1933:140) concluded from the discovery of these artefacts that the climate in the Rub‘ al-Khali had been considerably more humid during the Neolithic around 5000 cal BC2.

A large number of geologists and petroleum engineers arrived in Arabia during the 1950s and 1960s. As scientists employed by the Arabian American Oil Company (Aramco) to exploit the oil traps of the Kingdom of Saudi Arabia, during their geological surveys they discovered vast lithic surface scatters among other prehistoric remains. Trained in geology and geomorphology, but often with a general interest in prehistory, the geoscientists started collecting the most attractive artefacts: elaborate, bifacially retouched arrowheads and foliate points.

1.2 ARABIAN ARCHAEOLOGY AFTER THE OIL

With the discovery of the oil resources in the Kingdom of Saudi Arabia in 1939, global economic interest in this hitherto disregarded region increased dramatically. Associated with these growing economic interests, the pace of scientific exploration increased. During this time, new information about the presence of prehistoric finds from the interior of the Arabian Peninsula came from W. Thesiger, a member of the British Foreign Service dispatched to Dhofar. While instructed to investigate breeding sites of desert locusts, he succeeded Thomas and Philby in crossing the Rub‘ al-Khali in 1946 and documented prehistoric materials throughout the desert (Thesiger 1959).

Collections made by these amateur archaeologists at the fringes of the Rub‘ al-Khali were examined by F.E. Zeuner (1954) of the University of London, R. Gramly (1971) of the National Museum of Kenya and H. Field (1955, 1958, 1960a, 1960b) of Harvard’s Peabody Museum. The presence of bifacial, pressure-flaked projectile points and bifacial foliates provided the basis for a dating of these assemblages to the Neolithic in a chronological sense rather than an economic one. This tentative dating was confirmed by the 14C dating of a charcoal sample from a hearth associated with a lithic scatter, which yielded a radiocarbon date of 5090±200 BP uncal (Field 1960b). Zeuner and Gramly noted typological affinities to African assemblages, which led Zeuner to conclude that African elements played a decisive role in the ancestry of the southern Arabian Neolithic (Zeuner 1954:136).

The first archaeological investigations in southern Arabia carried out by archaeologists trained in prehistory were the surveys and excavations of G. Caton-Thompson and E. Gardner in Wadi Hadramaut between 1937 and 1938. While Caton-Thompson (1953:189) excavated an Iron Age temple in the Wadi ‘Amd, Gardner surveyed and sampled knapped stone artefacts found in situ in terrace gravels throughout the tributaries of the upper Hadramaut drainage system. Based on geomorphological and typological observations, Caton-Thompson claims a Pleistocene age for most of these artefacts. Trained in African archaeology, she points out similarities between the lithic assemblage of Wadi Hadramaut and northeast African inventories, and

THE DANISH ARCHAEOLOGICAL EXPEDITION TO QATAR One of the most influential projects in Arabian archaeology started in 1954 and continued until 1964: the Dutch expedition under the auspices of the Forhistorisk Museum in Aarhus headed by T.G. Bibby, P.V. Glob and H. Kapel. While the expedition originated in the excavation of Bronze Age burial mounds in Bahrain (Bibby 1973), a

1 The

chronological structuring and terminology of the Levantine Pre-Pottery Neolithic in this work follows Aurenche et al. 2001 and Kuijt & Goring-Morris 2002:366. 2 The following terminology is used for datings: cal BC refers to calendar years before Christ, BP uncal refers to uncalibrated 14C dates, while BP indicates years before present.

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CHAPTER 1

EARLY RESEARCH IN THE EASTERN PROVINCE OF SAUDI ARABIA

short reconnaissance carried out in Qatar in 1956 resulted in the discovery of Stone Age settlements. These findings led to expanded surveys from 1957 to 1964, in which the Dutch team succeeded in documenting at least 120 sites of prehistoric age (Kapel 1967:14). They classified the Stone Age remains based on the typological and technological character of the stone artefacts and categorised the sites into four groups (A, B, C, and D) based on the characteristics of the artefacts3.

Research in prehistory in the Eastern Province of Saudi Arabia started in a less systematic way. In 1968, G. Burkholder, an enthusiastic amateur archaeologist and teacher at the school for the Aramco in Dhahran, discovered the first sites with ‘Ubeid pottery close to the shores of the Persian Gulf and up to 65 km inland (Burkholder 1972:264pp.). Because the formation of the ‘Ubeid culture in Mesopotamia was widely unknown at this time, Burkholder located the development of the ‘Ubeid pottery in Saudi Arabia and suggested a spread into the marshlands of the Tigris and Euphrates (ibid. 1972:269).

Since all artefacts came from surface collections, no stratigraphic observations were available to establish the chronological order of the classification. Even Kapel himself expressed doubt about the chronological relationship of the groups (Kapel 1967:19). One radiocarbon date was obtained from a hearth adjacent to a small B-Group site characterised by a blade industry and yielded a date of 6970±130 BP uncal4. This date was used as a benchmark by the Danish team to look for artefact assemblages that were chronologically comparable. Based on this date, P. Mortensen, keeper of the National Museum in Copenhagen who was conversant in the Neolithic artefact assemblages of the Levant, suggested close similarities to assemblages associated with the early pre-pottery Neolithic cultures in Syria and Palestine.

This idea was further developed by A. Masry (1997), who wrote his Ph.D. thesis in cultural anthropology about “The Problem of Interregional Interaction” in north-east Arabian prehistory in 1973. He surveyed the known places with ‘Ubeid pottery and conducted soundings at the more substantial sites of Dosariyah, Abu Khamis and ‘Ain Qannas to obtain stratified archaeological material and information about environmental conditions. Based on his observations Masry proposed a model in which Arabian developments where seen as highly influential for the emergence of the Mesopotamian cultures (Masry 1997:132pp.).

During the work in Qatar the Sheikh of Abu Dhabi, Shakhbut bin-Sultan al-Nahyan, invited the Danish expedition to the island of Umm an-Nar in 1958. In the following year the reconnaissance was expanded to the interior of the Oman Peninsula around the oases of Buraimi and along the Trucial Coast as far as Ras al-Khaimah (Kapel 1967:5p.).

The latter view was contradicted by J. Oates and colleagues (1977) who performed a series of neutron activation analyses on ‘Ubeid pottery from Saudi Arabia, Qatar and Bahrain. These investigations suggest a Mesopotamian origin of the elaborate painted and plain ‘Ubeid pottery “beyond any reasonable doubt” (Oates et al. 1977:232). Therefore, Oates favours the “…one-sided nature of the relationship between Sumer and Arabia at this time…” (ibid. 232).

The Dutch work in Qatar was followed by a French expedition headed by J. Tixier between 1976 and 1978 to investigate a rich D-Group site near the present village of Khor close to the coast of south-western Qatar. While primarily concerned with the excavation of the site, the French team carried out surveys in different parts of Qatar. During these surveys the team investigated the site of Acila/al-Bahath site 36 H in the western part of the Qatar Peninsula to clarify the chronological position of the B-Group assemblages (Inizan 1988:26). While this goal was not achieved due to a lack of stratigraphic succession, M. Inizan reconfirmed the close typological and technological similarities between the Group B assemblages in Qatar and the PPNB assemblages of the Levant (Inizan 1980a:234pp., 1988:53p.) While Kapel’s classifications have “proved worthless with the end of the 1970s” (Tosi 1986a:466), the term “BGroup” remained the prevalent nomenclature for Holocene artefact assemblages containing a high portion of blades and blade arrowheads.

This scientific dispute highlights one of the problems in the cultural interpretation of archaeological remains in Arabia. Because this region was isolated politically and economically for many centuries, it remains a priori marginal and peripheral in the perception of western people (and scientists)–a role which Oates seemed to confirm with her analyses. In contrast, as a native-born Saudi Arabian archaeologist, Masry explicitly strengthened the position of Arabia against the proposed centres of civilization in Mesopotamia. Beyond this dispute, Masry’s excavations in ‘Ain Qannas resulted in a stratigraphic sequence in which aceramic layers (levels 14-12) with lithics indicating a blade industry and tanged points are superposed by layers (levels 10-8) containing a predominance of flakes and unifacially worked barbed arrowheads. The upper layers (levels 4-1) of the site contain ‘Ubeid ceramics together with small tanged arrowheads (Masry 1997:69pp.).

3 For

definitions, see chapter 1 section 2.1. the full list of 14C dates with Lab. codes and calibrated ages cf. Appendix 2 on CD.

4 For

7

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA

EARLY RESEARCH IN OMAN

Holocene based on the presence of pressure-flaked projectile points, blades, sickle blades and scrapers (Raikes 1967:28, Adams et al. 1977:27). The sites where these artefacts came from, referred to as Tell al-Muhassin and Tell al-Marrah, were already known in the late 1960s and at that time linked to the recent finds from Qatar (B-Group) and the Southern Levant (Raikes 1967:37).

While the discovery of oil throughout the Arabian Peninsula laid the ground for archaeological investigations in many areas, the Sultanate of Oman lagged behind because of the suspicious nature of the ruler, Sultan Said bin Tamur against western people. Only when his son, Sultan Qaboos bin Said, took over governance in 1970 was the country opened to outside scientists.

The Northern Province Survey in 1976 and 1977 was headed by P.J. Parr from the British School of Archaeology in Jerusalem. During these surveys, which included the sand dunes of the Nafud Desert, a substantial number of archaeological sites dating from Palaeolithic to Nabataean times were recorded. However, only ten sites were attributed to the aceramic Neolithic period and these were distributed over the entire survey region. Some of these Neolithic sites showed a close relationship to Levantine PPNB assemblages with prismatic blades, burins and bipolar bidirectional cores. In contrast, other Neolithic sites resembled the artefact inventory of the Rub‘ al-Khali with its finely retouched arrowheads with tangs. Parr, familiar with the Levantine archaeological material, pointed out that arrowheads similar to the Rub‘ al-Khali implements were found as far north as Azraq in eastern Jordan. Therefore he concludes:

In the early 1970s the Harvard Archaeological Survey headed by C.C. Lamberg-Karlovsky carried out a reconnaissance survey of the coastal and interior regions of Oman (Pullar 1974, Pullar & Jäckli 1978, Pullar 1985). Pullar’s group recorded more than 20 aceramic sites that consisted of scatters of lithic artefacts found along major watercourses of the interior at the edge of the Rub‘ al-Khali basin. However, evidence for a prehistoric coastal occupation was restricted to the cape of Ras al-Hadd in the Capital Area of Oman. Pullar recognised the presence of flint blades in Oman, which she classified as “flake-blades” in contrast to true blades. Although they were metrical blades, the dorsal scar patterns were predominantly convergent rather than parallel (Pullar 1974:35). This placed the finds from Oman in contrast with those from Qatar, where a true blade industry is present. With regard to the collections made in Oman, Pullar points out superficial parallels of the material with the Neolithic Levant, though diagnostic forms are missing and stronger analogies to east African artefact assemblages occur (ibid. 45).

“The extent and nature of a Neolithic presence within the Nafud, therefore, remains very unclear.” (Parr et al. 1978:36)

While the archaeological material found in the Eastern and Northern Provinces allowed a chronological structuring according to Near Eastern and Mesopotamian assemblages based on typological and technological similarities, this was no longer possible for the new finds from the first survey of the Central Province:

THE COMPREHENSIVE ARCHAEOLOGICAL AND EPIGRAPHIC SURVEY IN SAUDI ARABIA

“With the exception of the Rub‘ al-Khali “Neolithic” and closely similar industries in the Eastern and Central Provinces, the identification of stone tool industries within Saudi Arabia remains at a very rudimentary level.” (Zarins et al. 1979:13)

The rapid modernization of the Kingdom of Saudi Arabia resulted in the establishment of the Department of Antiquities and Museums in the early 1960s and a countrywide Comprehensive Archaeological and Epigraphic Survey. Begun in 1976, this project aimed to prepare a detailed inventory of the archaeological resources of the Kingdom (Adams et al. 1977:21). To facilitate this task the entire country with an area of over two million square kilometres was divided into six primary zones: the Northwestern, Northern, Eastern, Central, Southwestern and Western Provinces (Adams et al. 1977:Plate 1). Surveys were carried out by several scholars during the following decade, but the recorded information is not presented uniformly. The first areas investigated by the project were the Eastern and Northern Provinces. In the Eastern Province the survey was headed by R. McC. Adams of the University of Chicago. One focus of this expedition was the Yabrin Oasis on the northern periphery of the Rub‘ al-Khali where the presence of handaxes, cleavers, scrapers and blades indicated Palaeolithic occupation (Adams et al. 1977:29). Near alHasa Oasis, about 350 km northeast of Yabrin Oasis and close to Qatar, lithic material was dated to the Early

To deal with this uncertainty, the archaeological material from the Central Province was divided into three groups without attributing them to any particular chronological phase: handaxe sites, flake sites and “Neolithic” sites, the latter resembling material known from the Rub‘ al-Khali with a substantial presence of bifacially flaked implements including tanged or barbed arrowheads. The Southwestern Province was first investigated in 1979 together with a second examination of the western part of the Central Province. During both of these expeditions headed by J. Zarins, 267 sites were documented, but only a few were identified as Neolithic based on typological considerations. The dichotomy within the Neolithic material as known from the Northern and Eastern Province, a blade industry related to the classic PPNB of the Levant representing an early phase of the Neolithic, versus the later Rub‘ al-Khali Neolithic characterised by bifacially flaked implements was not recognised in the Nejd:

8

CHAPTER 1 ried out in 1981, both to investigate previously unvisited areas and to gather additional information concerning already known sites. Twelve Neolithic sites were documented, two of them with lithics reminiscent of the PPNB sites of the Levant. One of them, Kilwa, had been already described by Rhotert, in 1938, where blades, bladelets, blade cores and burins had been found. The other ten sites were placed in a later Neolithic context due to the occurrence of tabular flint scrapers, blades, and the presence of bifacial retouch. At three of these later Neolithic sites, ceramics have been identified (Gilmore et al. 1982:13). Stone artefacts with similarities to the Rub‘ al-Khali Neolithic material were not mentioned in the concluding report.

“Instead, one is left with describing a series of amorphous sites which belong neither to the aceramic ‘Neolithic’ of the Levant nor to the later ‘Neolithic’ material to be described below.” (Zarins et al. 1981:18)

The latter refers to the Rub‘ al-Khali Neolithic, with its “particular index fossil”, the “bifacially worked, tanged, and/or notched projectile point” (Zarins et al. 1980:19). A main focus of the Southwestern Province survey in 1980 was placed on the ‘Asir highlands including the eastern flanks bordering the Rub‘ al-Khali and the western flanks including the Tihama coastline of the Red Sea. Among the documented sites material with similarities to the early phase of the Neolithic characterised by blades and blade arrowheads was not found. But bifacial worked arrowheads similar to the ones from the Rub‘ al-Khali were observed at several sites from a variety of environmental settings. With the new finds from the Southwestern Province the Rub‘ al-Khali Neolithic had been documented in a broader geographical context:

During the following years the Comprehensive Archaeological and Epigraphic Survey focused on the Tihama plain in order to investigate prehistoric coastal settlement and adaptations, as well as possible links with the African continent (Zarins & al-Badr 1986:41). Only a handful of Neolithic sites were found along the coast, with lithic assemblages consisting of bifacially pressure-flaked, tanged and barbed projectile points that were widely parallel to the lithics of the interior of Saudi Arabia and Yemen (Zarins & al-Badr 1986:44).

“The Rub‘ al-Khali material then belongs to a larger, over-all Central Arabian Neolithic inter-acting with almost identical material from Eastern Arabia and Qatar.” (Zarins et al. 1981:20)

Based on these observations, C. Edens (1982:120) coined the term “Arabian Bifacial Tradition” to describe the former Rub‘ al-Khali Neolithic that was also referred to as “projectile point tradition” by Zarins et al. (1981:22). While slight differences were pointed out among the projectile points from different geographical regions with regard to the level of craftsmanship, these technological forms were described as basically comparable over a wide area. Another hallmark of these assemblages which had been identified was the absence of pottery.

RESEARCH IN THE CENTRAL RUB‘ AL-KHALI One of the most influential works in defining Arabian Neolithic stone artefact assemblages is that of C. Edens (1982), who examined the artefacts from four surface collections in the western Rub‘ al-Khali. While three of the sites, Sharorah, al-Mutabthat, and Mundafin are situated along the desert margin, one site, Jiledah, is located deep in the sands of the Rub‘ al-Khali. Edens summarised all of the previous research in the Rub‘ al-Khali with the goal of establishing a basic typology for the Arabian “late” Neolithic industries. To do this, the author presented a type-list based on common artefacts present among the four lithic collections. However, Edens ignored the fact that these assemblages were collected from the surface and represented palimpsests of materials from different times. While this type list was–and still is–used as the reference for Neolithic research in Arabia, Edens clearly did not intend this:

To obtain a chronological framework for the Late Neolithic, typological analogies to Levantine stratified artefact assemblages were used. Regarding the term “Neolithic” for these assemblages, Zarins indicates: “…no implication should be made that a certain way of life associated with animal and plant domestication was inherently practised and connected with this lithic tradition.” (Zarins et al. 1982:31)

“Strictly speaking, the type-list…refers solely to those four collections and does not presuppose extension in an unmodified form to other Rub‘ al-Khali materials.” (Edens 1982:110)

In the fifth year of the Comprehensive Archaeological and Epigraphic Survey, a reconnaissance was carried out in the Northwestern Province on the coastal plain of the Red Sea and in its wadis. Only a restricted number of sites with implements assigned to the Neolithic were identified. While some parallels with lithics found in the Central Arabian Province were observed, closer similarities to southern Levantine PPNB sites were highlighted. This was especially the case for the site of al-Aynah in the Tabuk region, where together with artefacts substantial architectural remains were recorded (Ingraham et al. 1981:66pp.).

Dominant types in the assemblages are bifacial forms, with “emphasis on stemmed and usually shouldered points and on narrow foliates” (ibid. 121). Regarding technological characteristics, he points to “a tendency toward lamellar flake hard hammer debitage, but not a true blade industry” (ibid). Comparing the lithic material from a broader geographical area he concludes: “These ranges of typological group frequencies, therefore, are not only characteristic of the sites in the western ar-Rub‘ al-Khali, but also of sites with a bifacial industry to the east and north. These ranges may be taken as broadly defining an Arabian bifa-

The final phase of the Comprehensive Archaeological Survey in the Northwestern and Northern Province was car-

9

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA mains and stone artefacts, but also burials, pendants, net sinkers and fish hooks. These remains indicated the sophisticated exploitation of a diverse environment. Radiocarbon dates obtained from charcoal placed the site at the end of the 3rd millennium cal BC. In the following years the research project was extended spatially, and the team expanded as H.-P. Uerpmann of the University of Tübingen joined the Italian expedition in 1979. Surveys and excavations at several sites were carried out until 1986 (Uerpmann & Uerpmann 2003:3). Not only did these investigations result in the oldest radiometric measurement from Oman at the site of Wadi Wutayya 1 (9615±65 BP uncal), but also in a substantial body of archaeozoological research. The results indicated the presence of domesticated sheep, goats, cattle and dogs as an important subsistence base at the shell middens on the Omani coast (ibid. 255pp.). In addition, the lithic and radiocarbon samples collected at different sites along the Omani coast made a chronological structuring of the lithic assemblages in this area possible (Uerpmann 1992:66). This classification of stone artefacts was complicated due to specific coastal adaptations and the fact that bifacially worked pieces form only a minor component of the stone artefact inventories. Therefore, typological comparisons with stone artefact assemblages from the interior were almost impossible. These investigations made by the team from Tübingen in the Muscat area were accompanied by geomorphological and geobotanical studies conducted by C. Hannß and H. Kürschner (Hannß 1991, Hannß & Kürschner 1998) to gain further insight into the relationship between human behaviour and environmental conditions.

cial lithic tradition, whose spatial limits are as yet poorly understood” (ibid. 120).

Besides a typological and technological description of the lithic material, Edens draws these conclusions about the economy of the Rub‘ al-Khali “Neolithic”: “Hunting of large- to medium-sized game (and utilization of vegetable material?); domesticates, either plant or animal, are not demonstrated” (ibid. 121).

This investigation by Edens represents a turning point for archaeological research in Arabia. For the first time, the uniform and specific character of part of the Arabian Neolithic was recognised. With such a revisable hypothesis, the door had been opened for more systematic studies based on the theoretical consideration of Arabian prehistory.

1.3 THE PRESENT STATE OF RESEARCH IN ARABIA During the 1980s the research agenda on the Arabian Peninsula shifted from site reconnaissance and data gathering to theoretically driven research projects. At this time, sociopolitical changes in the countries of the Middle East resulting from the Iranian Revolution and the Soviet intervention in Afghanistan in 1979 forced academic archaeologists working in these countries to divert their research programs southward into the Arabian Peninsula (Tosi 1986a:465). To deal with the incoherent mass of data collected until then, systematic research was inaugurated and expeditions shifted their priorities to the establishment of sub-regional subsistence strategies and cultural variability. Other questions concerned cultural connections to Africa and Mesopotamia, as well as human adaptations in a marginal desert environment.

Between 1985 and 1988 the Italian archaeological expedition conducted extensive surveys along the Omani coast between Bandar Khayran east of Muscat and Ra’s Sharbitat at the Dhofar border in the south (Biagi 1988). The team documented about 100 Stone Age sites along the coast, consisting of either shell middens or flint scatters (Biagi 1988:Table 1). These surveys indicated a substantial settlement along the Omani coast and emphasised the importance of marine resources.

EXPEDITIONS TO THE OMANI LITTORAL One of the most influential and longest ongoing research projects in southern Arabia began in 1977, when an Italian team headed by M. Tosi (University of Bologna, Italy) started excavating shell middens at Ra’s al-Hamra (RH) near Muscat in the Capital Area of Oman. This research was initiated by the movement of the nation’s capital from Nizwa, in the interior, to Muscat, on the coast. This relocation forced a rapid development of infrastructure and allowed for the investigation of archaeological sites before their concomitant destruction. The general objective of this project was to analyse subsistence patterns of the coastal settlements and their economic evolution through time (Durante & Tosi 1977:137). The wealth of marine life along the coast was seen as a prerequisite for these settlements. Therefore, one focus of this research was to reconstruct environmental conditions during the time of the coastal settlements in order to determine the ranges of resources, seasonality and scheduling factors in the economy (ibid. 138). Successful excavations were carried out at the aceramic shell midden RH 4, yielding not only shell re-

In addition, these surveys formed the basis for a wide range of archaeological investigations carried out by Italian and French teams along the Omani coast, which continue to the present day. One of these successive projects is the Joint Hadd Project led by S. Cleuziou from the CNRS and M. Tosi. Surveys and excavations in the Ja’alan region of Oman started in 1986 to investigate the development of Holocene communities along this part of the coast facing the Indian Ocean: ”First aim of the mission is to understand the evolution from Mesolithic (hunting and harvest) to Neolithic economy (agriculture in the oasis and fishing) in this region…” (University of Bologna 2006)

As with the previous expeditions in the Muscat area, archaeological, environmental and anthropological investigations were carried out to establish a complete picture of

10

CHAPTER 1 ences in Moscow that started in 1982 and lasted until 1995 (Amirkhanov 1997:247).

human behaviour. Nevertheless, Cleuziou and Tosi reject simple chains of cause and effect between environment and human societies and favour more complex explanations regarding the history of human communities (Cleuziou & Tosi 1998:122).

The Soviet team conducted surveys in the Hadramaut and Mahra provinces in the eastern part of the country close to the Omani border, as well as along the coast of the Gulf of Aden. In addition to unstratified, deflated surface sites, Amirkhanov documented stratified deposits from three multi-layered cave sites and six preserved open-air deposits. These stratified sites yielded artefact assemblages spanning from the Lower Palaeolithic to the Neolithic (Amirkhanov 1994:217). The site of Khabarut 1 in the mountainous part of the Mahra province, located in a valley which belongs to the Rub‘ al-Khali basin, is of particular interest for the Holocene chronology of this region. In a succession of 11 geological layers belonging to the Holocene, radiocarbon dates obtained from layer 4 indicate an age from the 7th/8th millennium cal BC. The corresponding artefact assemblage is dominated by flakes with just one flat, bifacially retouched, trihedral point (Amirkhanov 1996:138, 226, 1997). Remarkable is the absence of technological and typological similarities to the Early Neolithic in eastern Arabia. Therefore Amirkhanov postulates the existence of a South Arabian Neolithic complex independent from eastern Arabia during the Early Holocene (Amirkhanov 1996:138, 1997:248p.). Amirkhanov also noted the absence of tanged arrowheads as the type fossils of the Rub‘ al-Khali Desert Neolithic in the Neolithic sequence.

THE OMAN WAHIBA SANDS PROJECT OF THE ROYAL GEOGRAPHICAL SOCIETY Between 1985 and 1987 an interdisciplinary expedition directed by C. Edens explored five different regions around the margins of and within the Wahiba Sands, a desert area in east-central Oman comprised of longitudinal dunes (Edens 1988a:114). The general purpose of this survey was to document prehistoric and more recent traces of human occupation and assess the patterns of past land use (ibid.). Because the archaeological project was dovetailed with geomorphological investigations, the surveys were exploratory rather than systematic. Edens documented sites with stone artefacts in all of the surveyed regions. At most of these sites, points represented a distinctive component and could be separated into two different groups (ibid. 115). The first group consisted of blade points that were made on lamellar flakes on which a stem has been formed. In contrast to the already known blade points from eastern Saudi Arabia and Qatar, there was no evidence that the blanks of these points were the product of a true blade technology. Rather, they were selected (by-) products of an unspecialised flake production (ibid.). Because these points were first documented at Fasad, a locality in Dhofar (Pullar 1974), Edens suggested naming this type a “Fasad point” (Edens 1988a:116). The second group consisted of bifacially retouched stemmed points similar to the arrowheads found in the Rub‘ al-Khali. Because the two groups were found either separately or together, Edens (ibid. 122) concluded that Fasad points and bifacial points equally belong to a single industry within the Arabian Bifacial Tradition. Although there were no archaeozoological materials associated with these sites, the author correlated these sites with a hunter-gatherer occupation of southern Arabia during the moister climatic conditions of the Middle Holocene (ibid. 127).

THE FRENCH AND ITALIAN MISSIONS IN THE YEMEN ARAB REPUBLIC At about the same time, an Italian project was initiated in the Yemen Arab Republic (North Yemen) under the direction of A. de Maigret in 1981. While generally focused on the Classical periods of Yemeni history, additional surveys and excavations were carried out to document the prehistoric occupation of this area. The aim of this research was to examine how human occupation changed over time and to establish the different kinds of economy adopted within a particular geographical area (de Maigret 2002:117). The first area investigated was the Khawlan west of San’a, where within the Wadi ath-Thayyilah (WTH) several Holocene sites were discovered with buried, in situ material. These sites were assigned to the Neolithic based on the occurrence of lithic artefacts without pottery and their association with substantial architecture. One of these sites, WTHiii, was excavated in 1985 and 1986 by F. Fedele. These excavations uncovered three elliptical huts with fireplaces and abandoned stone tools inside. A significant number of animal bones were identified as cattle, while sheep and goat remains were under-represented. This was seen as an indicator for livestock husbandry, while hunting seems to have been totally absent (Fedele 1986:397, de Maigret 2002:125). Based on a radiocarbon date obtained from a palaeosoil outside the actual site and the occurrence of other palaeosoils in the region, the Neolithic occupation

THE SOVIET MISSION IN THE PEOPLE’S DEMOCRATIC REPUBLIC OF YEMEN In Yemen, adjacent to Oman, archaeological research was restricted due to political reasons too. A socialist uprising in southern Yemen against British colonial rule divided the country into two states and subsequently launched a civil war that lasted from 1967 until 1994. One of the most successful investigations in Yemen during this time, despite the political situation, was a Soviet survey project in the People’s Democratic Republic of Yemen (South Yemen) headed by H. Amirkhanov of the Russian Academy of Sci-

11

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA of WTHiii was set between the 6th and 4th millennium cal BC (Fedele 1988:35).

groups who used to be engaged in hunting activities” (Di Mario 1989:147).

M. Tosi was invited to join the project for surveys along the Red Sea coast in the Tihamah region in 1985. He led a series of reconnaissance missions in this area during the following years and located several prehistoric sites along Wadi Rima and Wadi Surdud. Some of the shell middens documented during these surveys were more than 10 km away from the present coast, indicating substantial changes in the coastline during the Holocene in this region.

In 1983 and 1984 M.L. Inizan completed two prehistoric surveys in the western Hadramaut on the western edge of the Jol plateau, where it borders the Ramlat as-Sab’atayn desert (Inizan & Ortlieb 1987). During these surveys Middle Palaeolithic artefacts were identified near outcrops of raw material on the Jol plateau. In contrast, the Neolithic sites were predominantly found on wadi banks that drain from the Jol plateau into the Ramlat as-Sab’atayn and the sand desert itself. The lithic industries associated with these sites were dominated by bifacially flaked arrowheads that resemble types known from the Rub‘ al-Khali. Charcoal from hearths found at two of the sites were radiocarbon dated to the 4th/beginning of the 5th millennium cal BC (ibid. 18).

From the site of Jahahbah 1 (JHB-1), located in a far inland position associated with the Early Holocene marine transgression, a radiocarbon date was obtained which set the occupation of the site in the 6th millennium cal BC. The presence of one tanged, pressure-flaked arrowhead analogous to the Neolithic projectile points from the interior of the Arabian Peninsula has been used to date the Arabian Bifacial Tradition back to the 6th millennium cal BC (Tosi 1986b:407). The few bone fragments found at the site were identified as large, wild, herd mammals (equids and bovids) representing part of the subsistence basis of intensive foragers (ibid.). One big disadvantage of the site of JHB-1 was the absence of in situ material: “most rewarding results originated from a more careful inspection of this site surface” (ibid.).

THE ROOTS OF AGRICULTURE IN SOUTHERN ARABIA (RASA) PROJECT In southern Jol J. McCorriston initiated a systematic survey and excavation program in 1996. The research agenda for this project focused on subsistence strategies of Holocene communities and the roots of agriculture in southern Arabia. Systematic surveys were carried out within the Wadi Sana, where a substantial number of sites were discovered at the confluence of Wadi Shumlya and Wadi Sana. These findings were interpreted to correlate with changing Holocene environmental conditions. The earliest finds were documented among alluvial gravels and scree or beside Early Holocene fluvial or aeolian deposits. The artefacts found in these situations included Fasad-type points. Therefore, McCorriston suggests a unifacial point tradition that antedates the occurrence of bifacial points (McCorriston et al. 2002:69). A series of rockshelters contained stratified deposits with bifacially worked artefacts and hearths. Four radiocarbon dates were obtained from ashy material within the stratified deposits, yielding dates ranging between ca. 6600 and 5300 cal BC. Over 4000 stone artefacts were recovered during the excavations, among them about 100 diagnostic tools. The type spectrum includes bifacially worked projectile points, drills, scrapers, borers and retouched flakes. For the projectile points, similarities to the Rub‘ al-Khali Neolithic type were diagnosed (ibid. 71). Because there were no significant changes in the projectiles and other tool types, McCorriston suggests a homogenous industry throughout the whole period of human occupation at the site.

The discovery of a substantial quantity of animal bones determined to belong to wild donkeys by S. Bökönyi (Cattani & Bökönyi 2002) at the site of ash-Shumah (ASH) supported Tosi’s view of a prevailing hunter-gatherer way of life in southern Arabia during the Early Holocene. The discrepancy between the observations made in the Yemeni highlands, where domesticated animals are present, and the absence of these at the coast, has been explained by the considerable environmental differences (de Maigret 2002:129). The third area investigated by the Italian mission was the Ramlat as-Sab’atayn, a dune field that marks the southwestern margin of the Rub‘ al-Khali. These surveys focused on the Desert Neolithic sites in this region. A number of surface artefact scatters were documented, while two particularly rich findspots in the Wadi Harib (HAR) were investigated more intensively, HARi and HARii. Pedological observations indicate the presence of shallow lake basins with still waters in the area during the time of the Holocene occupation (Di Mario 1989:111). The lithic industry of the sites shows close similarities with the Rub‘ al-Khali Neolithic. Flakes constituted the majority of debitage, with a minor metrical blade component that lacked true blade technology. The tool kit is dominated by projectile points, while other bifacially worked pieces (foliates) and unifacial tools are less common. A sample of 180 faunal remains collected at HARii was identified predominantly as wild equid and wild gazelle. The presence of domesticated species was almost completely ruled out, with the assemblage interpreted as the remains of “human

In addition to the occupations at rockshelters, a number of open-air findspots were documented along Wadi Shumlya. These sites are characterised by hearths with associated faunal and lithic material and seem to post-date the occupation of the nearby rockshelters. A number of radiocarbon dates place these sites in a time range between 5000 and 4500 cal BC. Associated with one of these hearths, a bifacial, stemmed point in the Rub‘ al-Khali Desert Neolithic

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CHAPTER 1 but this did not fit within the established range of Holocene technological traits: Excavations at the Bronze Age site of Hawagir in the Dhamar area yielded a similar assemblage (Edens 2001:141), tentatively placing the assemblages of blades in the Bronze Age.

tradition was recovered (ibid. 75). Faunal remains included medium and large mammal bones, one of them identified as cattle–wild or domesticated. In 2004, surveys carried out by the RASA Project team led to the discovery of the site of Manayzah, a rockshelter in Wadi Sana (Crassard et al. 2006). Excavations unearthed a succession of about 60 archaeological layers within a more than 2.20 m deep stratigraphic sequence covering the Early and Middle Holocene and possibly Late Pleistocene. Within this sequence, four hearths and numerous ashy deposits indicate domestic activities. In addition, post holes and a pit for rubbish disposal point to the presence of installations. Charred dung pellets suggest the sheltering of sheep and goat at the site. Direct evidence for the presence of domesticated animals comes from finds of animal bones dating into the beginning of the 6th millennium cal BC. Although a small sample, domesticated sheep, goat and cattle have been identified.

RECONNAISSANCE SURVEYS IN THE UNITED ARAB EMIRATES At the south-eastern tip of the Arabian Peninsula in the United Arab Emirates, the first systematic archaeological investigations were carried out comparatively late in the 1980s. An archaeological and geomorphological survey in the Emirate of Sharjah was initiated by a French team in 1984 headed by R. Boucharlat. During a first reconnaissance, Stone Age remains were documented both on the Arabian Gulf coast and in the interior (R. Boucharlat et al. 1997, 1st Report:5). During the following years these surveys continued, but the main research focus shifted towards younger periods. One minor excavation carried out at a site located on the north-eastern flank of Jebel Fa’iyah in 1989 (Site P28; Millet 1997, 5th Report:29) resulted in the recovery of substantial numbers of stone artefacts. The spectrum of artefacts recovered from these excavations and surveys in the adjacent areas includes bifacial pieces, interpreted as unfinished bifacial tools, a tanged arrowhead with typological affinities to the Rub‘ al-Khali Neolithic types, an elongate projectile point, as well as retouched flakes and denticulates (ibid. 30).

Numerous chipped stone artefacts were discovered from all archaeological layers. Main characteristic technological element of assemblages radiocarbon-dated into the sixth millennium cal BC is the application of fluting for the production of bifacially chipped stone arrowheads. Pressure flaking has been identified for the shaping of stone implements (ibid. 162). The typological spectrum of stone arrowheads includes shouldered and stemmed forms. Trihedral arrowhead points and bifacial tanged arrowheads with a slightly curved section are dated into the seventh millennium cal BC (ibid. 169). Although the archaeological sequence indicates an Early Holocene occupation at the site, no indications for a Levantine blade technology have been found.

Rapid urban development in the capitals of the Emirates located on the Arabian Gulf littoral (Abu Dhabi, Dubai, Sharjah, Ajman, Umm al-Qaiwain, Ras al-Khaimah) resulted in extensive archaeological surveys being conducted in these areas. While the westernmost section of the coast from Sabkhat Matti to Tarif was surveyed by a joint Abu Dhabi–German expedition in 1983 (Vogt et al. 1989), the coast of the Sharjah Emirate was investigated by the French mission from 1984 onwards. Ajman was surveyed by a Belgian Archaeological Expedition to the United Arab Emirates at the end of the 1980s (Haerinck 1991, 1994), while the Umm al-Qaiwain coast was (accidentally) surveyed by the French mission in the mid-1980’s. During the excavations at the Bronze Age site of Tell Abraq in the Umm al-Qaiwain territory, the Umm al-Qaiwain lagoon was investigated again in 1992 by a German team (Uerpmann & Uerpmann 1996). Finally the Ras al-Khaimah coast was systematically surveyed in 1987 and 1988 by another German team (Vogt 1994).

INVESTIGATIONS OF THE ORIENTAL INSTITUTE OF CHICAGO IN THE YEMEN HIGHLANDS The Oriental Institute of the University of Chicago started investigations headed by T. Wilkinson, M. Gibson and C. Edens in the Yemeni high plains in 1994 to assess an archaeological and environmental sequence in this hitherto neglected region. During initial surveys in 1994 and 1995 archaeological remains were documented within the Dhamar plain dating from the Middle Holocene until the Himyarite period of the early centuries AD. While a substantial human occupation was verified from the Bronze Age onwards, evidence for human activities prior to around 3000 cal BC proved elusive (Wilkinson et al. 1997:102). During these surveys no aceramic Neolithic sites with residential architecture were found. But a few findspots could be placed in the Middle Holocene based on geostratigraphical observations (ibid. 108, Wilkinson 2005:178p.). The lithic assemblages from most of these sites, which included bifacially worked pieces, could be comfortably aligned with already known Neolithic assemblages from the surrounding areas. In contrast, a pronounced blade component was documented at some sites,

The most conspicuous remains of Stone Age settlements along the coast were shell middens found predominantly on the edge of (former) lagoons. Based on radiocarbon dates the bulk of these sites can be placed in the second half of the 5th and the beginning of the 4th millennium cal BC. Among the shell middens, human burials, chipped stone artefacts, fishing equipment, beads and ceramics were found. The ceramic represents ‘Ubeid pottery with an as-

13

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA

THE JOINT GERMAN MISSION IN SHARJAH/ U.A.E.

sumed southern Mesopotamian origin. The flint industry of these shell middens shows close affinities to the Rub‘ alKhali Neolithic and can be seen as part of the Arabian Bifacial Tradition. The prevailing interpretation of this pattern in south-eastern Arabia is as follows: while the ‘Ubeid pottery is a foreign intrusive element, the bifacially flaked flint industry represents the local population (Uerpmann & Uerpmann 1996:131).

A comprehensive archaeological expedition to investigate the Middle Holocene way of life in the interior of southeastern Arabia started in 1996 at the Neolithic graveyard of al-Buhais 18 (BHS18). The Neolithic graveyard is located at the fringe of the al-Madam oasis in Sharjah Emirate. The archaeological team of the Directorate of Antiquities of Sharjah, headed by S.A. Jasim, discovered the site in 1995. Subsequently between 1996 and 2005, the site was excavated as a joint project of the Directorate of Antiquities and the Institute of Prehistory of Tübingen University under the direction of H.-P. and M. Uerpmann. In addition to more than 450 burials, a stone midden composed of cooking stones, ash and animal bones and a substantial number of fireplaces have been found within the context of the graveyard. About 20 radiocarbon dates from several contexts place the occupation between the end of the 6th millennium and the beginning of the 4th millennium cal BC (Uerpmann et al. 2006). The discovery of a high number of archaeozoological remains belonging to domesticated animals (sheep, goat and cattle) resulted in a re-interpretation of the subsistence strategies: the Middle Holocene inhabitants of south-eastern Arabia were not hunter-gatherers, but mobile herders with a mixed herding economy (Uerpmann et al. 2000:232, Uerpmann & Uerpmann 2000:48). The stone artefact assemblage of this site shows differences with the Desert Neolithic of the Rub‘ al-Khali. Nevertheless, a minor assemblage of bifacially worked projectile points fits in the context of the Arabian Bifacial Tradition.

ABU DHABI ISLANDS ARCHAEOLOGICAL SURVEY (ADIAS) Following up on the previously mentioned investigations in the Emirate of Abu Dhabi, the “Abu Dhabi Islands Archaeological Survey” project was established in 1992. The general focus of this project was the recording of archaeological sites on the islands and along the coast of Abu Dhabi. More than a thousand sites were documented, and in some cases, artefacts and environmental remains were selectively collected. At the sites with the most potential interest, systematic excavations were undertaken (Abu Dhabi Islands Archaeological Survey 2006). At Dalma (DA), a small island with substantial fresh water sources in the western region of Abu Dhabi Emirate, excavations were carried out at the site DA11 in 1993, 1994 and 1998. During these excavations, shells, animal bones, plant remains, stone artefacts and ceramics were recovered. The presence of ‘Ubeid ware in a context dating to the late 6th – early 5th millennium cal BC places marine contact between Mesopotamia and south-eastern Arabia about 500 years earlier than expected before. The associated stone tool kit included barbed and tanged arrowheads resembling forms which belong to the Arabian Bifacial Tradition as well as piercers, knives, scrapers and wedges (Popescu 2003:51). In addition, the site yielded the earliest evidence for the consumption of dates in south-eastern Arabia (Beech & Shepherd 2001).

1.4 DISCUSSION The outline of the history of research in Arabia makes the fragmentary nature of archaeological investigations on the Arabian Peninsula clear. Research from the beginning of the 1930s until the 1980s was dominated by field reconnaissance and random samples often made by amateur archaeologists. This situation changed during the end of the 20th century with a move towards more systematic investigations. Most research in the Stone Age periods focused on the Neolithic for the simple reason that the archaeological material of this period was accessible and available. An examination of the stone tool typology and technology suggests, on the one hand, considerable regional diversity within the Arabian Peninsula. On the other hand, general characteristics of the lithic material have been observed within a broad geographic range. This pattern has been explained either as the result of specialised foragers who lived in specific geographic areas but were connected by exchange systems (Tosi 1986a) or caused by mobile herders inhabiting different habitats during a year-round cyclical migration (Uerpmann et al. 2000, Uerpmann & Uerpmann 1996).

Surveys at the island of Marawah (MR), located ca. 100 km west of the city of Abu Dhabi, identified several archaeological sites. The most important of them, MR11, is a settlement site with substantial architectural remains with different building phases dating back to the mid 6th millennium cal BC. A ceramic jar in association with a burial within one of the houses (room 1) shows similarities to the Mesopotamian ‘Ubeid and Iranian finds (Beech et al. 2005:46p.). Again, the presence of bifacially worked projectile points sets this site in the wider context of the Arabian Bifacial Tradition. In Kuwait a similar site of slightly younger age named H3 has been excavated recently on al-Sabiyah island (Carter 2002, Carter & Crawford 2001, 2003). Site H3 yielded several phases of occupation with architectural remains, ‘Ubeid ceramics and lithics, indicating a wider sphere of interaction within the Persian Gulf at this time (Carter 2006:52).

Both views have wider implications. If one follows Tosi and colleagues, then the presence of specialised foragers on the Arabian Peninsula during the Early and Middle

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CHAPTER 1 Holocene forms the basis for all further developments without the necessity of any external input (Cleuziou et al. 2002, 11). However, the presence of domesticated sheep, goat and cattle within a mixed mobile herding economy presupposes a significant input from areas outside Arabia where the centres of domestication of these animals are located.

“Typologically, the assemblage is neolithic and comparable with the Fayum in the technique of manufacture.” (Zeuner 1954:134)

In this early context, the term ‘Neolithic’ is simply a descriptive one, without any implications for the prevailing economy: “The character of the sites as a hunters’ camp is borne out by the large number of projectile points.” (Zeuner 1954:134)

A careful examination of these diverging argumentations is necessary: since the beginning of research, conclusions about the prehistory of the Arabian Peninsula were reached based not only on the material evidence, but also on the academic background of the different researchers. Too often western academics have seen the Arabian Peninsula as an appendix of the “centres of civilisation” which had nothing to offer but much to gain. During the last decades this onesided view generated a contrary viewpoint: foreign influences were neglected in favour of local developments. But as I will demonstrate in the following pages, sometimes old paradigms are simply substituted by new ones.

The main focus of this mode of operation was the subdivision and definition of archaeological complexes, and not the establishment of an internal structure.

H. KAPEL 1967 AND M.L. INIZAN 1988 In 1967 H. Kapel attempted the first systematic structuring of the Stone Age of the Arabian Peninsula. During extensive surveys in Qatar, more than 120 sites with Stone Age remains were documented. The knapped stone artefacts from these sites were classified based on typological and technological traits. Additional information was obtained from an analysis of the geomorphological setting in which the sites were found.

2 THE HOLOCENE PREHISTORY OF THE ARABIAN PENINSULA: CHRONOLOGICAL AND SPATIAL STRUCTURING

All Stone Ages sites were classified into four groups, wherein the terminology for the groups (A, B, C, and D) was chosen as a working division. Because there were no stratified sites available for stratigraphic control of the established chronological order, the chronological relationship of the groups remained unclear (Kapel 1967:19).

While the history of research in Arabia is fragmentary and, in part, driven by forces beyond academic interest, the chronological and spatial structuring established for the Early to Middle Holocene prehistory of this vast area is surprisingly homogenous. Differences in the nomenclature can be identified, but after the 1960s, there is broad agreement with regard to the characteristics of the cultural units. The chronological sequence of the Levant and directly adjacent regions at the northernmost border of the Arabian Peninsula are not the focus of this chapter, but will be considered to highlight possible connections between the areas.

“…the construction of an absolutely certain sequence for the various Stone-Age cultures meets with considerable difficulties. At no site we have been able to ascertain any trace of a trustworthy stratigraphy. An estimation of the chronological sequence of the cultures based solely on typology runs…a risk of subjectivity and misinterpretation.” (ibid. 15)

Based on typological traits, A-Group sites were dominated by “large, unhandy, primitive implements resembling hand-axes”. The position of most of these sites on the uppermost terraces of limestone cliffs has been seen as an additional indicator of the older age of these sites (ibid. 16). In contrast, the B-Group sites are characterised by the occurrence of blades and blade cores with two striking platforms, together with blade arrowheads. Sites of this group were located at various points on the Qatar Peninsula, but most frequently at the top of low cliffs close to the present coastline. The C-Group was assumed to be the direct descendant of the A-Group with a mixture of coarser and finer implements. Characteristic of the D-Group are pressure flaked tanged arrowheads with barbs and other pressureflaked tools of various forms (ibid. 20). The presence of pressure-flaked arrowheads links the D-Group with the sites known from the interior of the Arabian Peninsula, that is, the Rub‘ al-Khali Desert Neolithic. Concerning the chronological arrangement of the four groups, Kapel was convinced that A-Group is the oldest, while B, C, and D are younger. Of these, the C-Group was regarded as older than

2.1 ESTABLISHED CHRONOLOGICAL AND SPATIAL SCHEMES FIRST ATTEMPTS During the first years of investigations on the Arabian Peninsula, reconnaissance surveys documented the presence of archaeological remains. New finds were related to already known assemblages, while unknown artefact types could establish a new archaeological complex. One example of this process is the accruing body of stone artefact collections belonging to the “Rub‘ al-Khali Neolithic” during the 1960s. The term ‘Neolithic’ was used to point out similarities with Neolithic stone artefact assemblages from northern Africa and the Levant:

15

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA To evaluate different lithic collections, Edens established a type list for the western Rub‘ al-Khali assemblages. Then he clustered the types into four typological groupings: I) bifacial and unifacial points; II) scrapers; III) other light tools; and, IV) heavy duty tools (ibid. 113). On the basis of these typological groups, all samples from the western Rub‘ al-Khali show a high degree of similarity in respect to Group I. Thus, bifacial and unifacial points represent the dominant form. In addition, artefact assemblages from the north-eastern fringes of the Rub‘ al-Khali and from Qatar fit the group frequencies of the western Rub‘ al-Khali collections very well. Therefore, Edens subsumed all of these sites into a unified Arabian Bifacial Tradition (ibid. 121):

the B and D-Groups. The B and D-Groups might in turn represent a succession or be contemporaneous (ibid. 19). While the A, C, and D-Groups were seen as a succession of local cultures, the B-Group is expected to originate elsewhere: “This blade-arrowhead culture is clearly differentiated in every respect from the other cultures occurring on Qatar, and it is not inconceivable that it was borne in an immigrant people whose way of life differed radically from that of the other…cultures.” (ibid. 16)

Artefacts from the B-Group sites were examined by P. Mortensen, who suggests connections between this material and assemblages found at early pre-pottery Neolithic sites in the Levant (ibid. 18). Therefore Kapel suggests:

“These ranges of typological group frequencies, therefore, are not only characteristic of the sites in the western ar-Rub‘ al-Khali, but also of sites with a bifacial industry to the east and north. These ranges may be taken as broadly defining an Arabian bifacial lithic tradition, whose spatial limits are as yet poorly understood.” (ibid. 120)

“…it would appear that this blade-arrowhead culture–or influences derived from it–has spread both northward and southward form an area of origin somewhere in the eastern Mediterranean region.” (ibid.)

The typological marker for this industry has been seen in the presence of bifacially worked, stemmed and barbed points. Edens suggests similarities or “points of correspondence” to a number of collections which show a bifacial component from a broad geographical area: ‘Ubeid sites in the Eastern Province of Saudi Arabia, sites located in the mountainous areas peripheral to the Rub‘ al-Khali to the southeast, south, and southwest, including Wadi Hadramaut in Yemen and Wadi Dawasir in Saudi Arabia.

This observation represents the starting point for any further developed concepts of a Levantine origin for the Neolithic on the Arabian Peninsula. But by the end of the 1970s the classification and chronological schemes applied by Kapel had been proved to be incorrect by the successive French investigations in Qatar: “The study of stone implements, pottery, structures, the outcomes of survey…upset the Danish expeditions’ data.” (Tixier 1980:197)

Concerning the dating of this Arabian Bifacial Lithic Tradition and the western Rub‘ al-Khali Neolithic in the narrower sense, Edens was aware of uncertainties. He suggests a three thousand year long period between the sixth and fourth millennium cal BC based on an association of “flint tools of Neolithic type” and Holocene lake sediments found in the Rub‘ al-Khali dated by McClure (1976) to a time ranging between 7000 and 4000 cal BC (Edens 1982:122).

Thus, the assemblages of the B-Group were placed at the beginning of the Holocene sequence. Kapel’s A, C and D assemblages were hence treated as a single entity succeeding Qatar B (ibid.). Because A, C, and D-Group artefacts were found together with ‘Ubeid ceramics, these assemblages were placed within the 5th millennium cal BC (ibid.), while the B-Group assemblages were placed in the time before the 6th millennium cal BC (Inizan 1988:205). Regarding the origin of the B-Group assemblages, Inizan confirmed typological and technological similarities to Levantine PPNB assemblages, but challenged the interpretation of this pattern:

Edens (1988b) published a complement to his previous paper, including results from further studies of artefacts found in the Eastern Province of Saudi Arabia, in which he redefines his definition of the Arabian Bifacial Lithic Tradition. The main focus of this publication was the issue of geographical variability within these artefact assemblages based on individual tool types and technological aspects. While his own observations coupled with the new finds from the surrounding areas indicated the presence of differences between regional facies, he reaffirmed “the basic unity” of the Arabian Bifacial Lithic Tradition sensu Edens 1982 (Edens 1988b:30).

“La seule convergence technologique des armatures associées à un type particulier de débitage laminaire ne peut cependant suffire à envisager une filiation entre les populations du Proche-Orient et du Golfe, gardons-la toutefois en mémoire.” (ibid. 54)

C. EDENS 1982 AND 1988 The first attempt to structure the Neolithic of the interior of the Arabian Peninsula was carried out by C. Edens based on four artefact assemblages that were collected along the fringes of the Rub‘ al-Khali desert (Edens 1982). He defined traits for these assemblages on the basis of typological and technological considerations, separating a western Rub‘ al-Khali facies from the wider Arabian Bifacial Lithic Tradition.

Edens distinguishes several geographic regions, each with its own characteristics, but all reminiscent to the Arabian Bifacial Lithic Tradition. Both in the western Rub‘ al-Khali and the Eastern Province/Qatar region, the assemblages are dominated by stemmed bifacial points. In contrast, sites in eastern Oman (Jebel Huwaya) show a clear bifacial

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CHAPTER 1 ninsula (Saruq, Bir Khafsa, Ramlat Fasad and Habarut). Similar to Kapel’s considerations in 1967, Potts points to close similarities between the B-Group assemblages and Levantine PPNB stone artefact technology and typology (Potts 1990:34, 1992:64, 1993:170). The identifying feature for the assemblages belonging to this horizon are slender, finely retouched blade-arrowheads with or without tang and the presence of blades and blade cores.

component but lack the stemmed points. Stemmed points again occur at Fasad and Habarut in southern Oman, but are not barbed and show a pronounced triangular crosssection, indicating a fourth regional group (ibid. 33). In turn, a fifth regional group identified in the areas west of the Rub‘ al-Khali, in the Wadi Dawasir and the ‘Asir highlands, has strong similarities to the Rub‘ al-Khali Neolithic. Further northwest and north in the southern Hejaz and the central Nejd, the presence of diagnostic stemmed bifacial points and foliates was confirmed, and these types continue into the northern portions of the Arabian Peninsula. Another regional group documented to the south in North Yemen shows close similarities to the western Rub‘ al-Khali assemblages (ibid. 34).

Notable in this context is the inclusion of the sites on the Oman Peninsula, which show a distinctive blade point component (Fasad points), but not a true blade industry (cf. Edens 1988b:119). Although Potts remarks that these points were actually not blade points, but made on lamellar flakes, he still implies a close affinity with the Qatar-B industry (Potts 1993:172p.). This inauspicious link between the B-Group industries with a true blade industry (sensu Levantine PPNB lithic industries) and the south-eastern Arabian industries with points similar to blade points, but made on blade-like flakes, can be found in almost all consecutive classification schemata.

Edens explains these regional lithic facies by the presence of local populations adapted to different regional environments. Beyond differences in the lithic assemblages, these adaptations include differences in the structuring of space on sites (ibid. 35) as well as differences in the prevailing economy: pastoralism in the southern Arabian highlands and the coastal sites of Oman and the Eastern Province of Saudi Arabia, and hunting/gathering in the Rub‘ al-Khali. While distinguished by these environmental adaptations, the different lithic facies are seen as formalised due to inter-regional exchange networks (ibid. 37). With this explanation, Edens implies the chronological coexistence of the different facies of the Arabian Bifacial Lithic Tradition. Therewith, this lithic tradition forms a second fundamental pillar for the chronological and regional structuring of the Holocene history of the Arabian Peninsula.

Following Potts, Wadi Wutayya, located on the coast of Oman represents a different local facies, but belongs to the same time horizon. In contrast to B-Group assemblages, this facies is not a blade industry (Potts 1993: 173). The latter view has been recently contradicted by the excavators of Wadi Wutayya, H.-P. and M. Uerpmann. In their final publication, they clearly distinguish between the B-Group assemblages with technological connections to the Levant and the lower levels of Wadi Wutayya related to pre-Neolithic populations inhabiting the coastal areas of Oman (Uerpmann & Uerpmann 2003:59).

D.T. POTTS 1990, 1992 AND 1993

Potts’ next period, ‘Late Prehistoric B’, tentatively dates between 4500 and 3800 cal BC. He incorporates a large number of sites that generally fall into the ‘Arabian Bifacial Tradition’ and that are characterised by fine pressureflaking and extensive retouch (Potts 1993:173). Another characteristic of sites belonging to this horizon is the presence of ‘Ubeid pottery along the Persian Gulf coast. Potts includes in this group the sites known from the Eastern Province of Saudi Arabia, the Rub‘ al-Khali, Kapel’s A, C, and D-Group sites in Qatar, the coastal sites of the United Arab Emirates and Oman, as well as sites with a bifacial component in the interior of the Oman Peninsula (Potts 1993, 173pp.). Following a suggestion made by H.-P. and M. Uerpmann, Potts conceives the populations of the Arabian Bifacial Tradition as herders who spent most of the year grazing their herds in the interior, but lived on the coast for part of the year (ibid. 177).

The first synthesis of all known evidence of the Holocene history of the Arabian Peninsula was attempted by D.T. Potts in the early 1990s (Potts 1990, 1992, 1993). He based his synthesis on the growing number of systematic archaeological investigations from the beginnings of the 1980s, which resulted in an increasing body of knowledge about the Holocene history of this area. At that time, the history of the Arabian Peninsula, at least of its coastal region facing the Persian Gulf, started in the Holocene. All Palaeolithic evidence had so far been neglected: “Although the reasons behind it are by no means clear, the absence of any Palaeolithic sites in the western Arabian Gulf littoral is now generally recognized…” (Potts 1990:28)

Potts established a tripartite subdivision of the Holocene Stone Age history of the Arabian Peninsula and introduced the terms ‘Late Prehistoric A’, ‘Late Prehistoric B’, and ‘Late Prehistoric C’ in order to avoid labels with implicit connotations (Potts 1993:168pp.). ‘Late Prehistoric A’, tentatively dating between 5000 and 4500 cal BC, refers to Kapel’s (Qatar-) B-Group, which “becomes the earliest post-Pleistocene archaeological component on the Arabian Gulf area” (Potts 1990:32). In addition to the sites in Qatar, related industries were documented in Saudi Arabia (Ain Qannas, Jebel Daba) and, following Potts, at the Oman Pe-

Into the last phase of the Stone Age, termed ‘Late Prehistoric C’ (3800–2800 cal BC), Potts subsumes the various post-‘Ubeid assemblages with chipped stone artefacts dating to the fourth and third millennia cal BC. Tentatively corresponding sites were found in the Hofuf oasis in Saudi Arabia, on the coast of the United Arabian Emirates (UAE), and, most prominent, along the coast of the Capital

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA

H.A. AMIRKHANOV 1996 AND 1997

Area in Oman. These sites tend to concentrate along the coasts, indicating strong marine adaptations during this time. This view is supported by finds of various fishing equipment, and fish and shellfish remains at these sites.

From a wider geographic perspective H.A. Amirkhanov suggests in the mid-1990s a bipartite system for the Arabian Holocene Stone Age history which distinguishes between an ‘Early Neolithic’ (spanning from the 8th to the 6th millennium cal BC) and a ‘Late Neolithic’ (covering the time between the 5th to the 3rd millennium cal BC) (Amirkhanov 1997:248, 1996:138p.). In contrast to other authors, Amirkhanov favours the explicit term ‘Neolithic’ for a classification of the Holocene Stone Age cultural complexes in Arabia because of the strong typological and technological similarities that he sees between this Arabian Early Neolithic and the Levantine PPNB (Amirkhanov 1996:136p.). Following the Late Neolithic, Amirkhanov introduces the term ‘Postneolithic’ for cultural complexes with a substantial stone artefact component, but dating to the 2nd millennium cal BC.

M. UERPMANN 1992 A further improvement to the structuring of the post-Pleistocene Stone Age of south-eastern Arabia with a more local focus has been done by M. Uerpmann (1992) based on chipped stone artefacts and radiocarbon dates. She distinguishes a succession of several local facies of stone artefact assemblages collected along the coast of the Gulf of Oman, which span a time period from the second quarter of the Holocene to the Early Bronze Age. The first quarter of the Holocene is excluded from this study because evidence for the presence of man in southwest Arabia is generally scarce (Uerpmann 1992:105). The oldest facies, named the ‘Wadi Wutayya Facies’ after its type site in the Capital Area of Oman, was only poorly defined. Its dependence on quartz as a raw material is stated, as well as the absence of bifacial retouched tools. Only a minor blade component was observed, while the inventory is generally dominated by flakes. Based on radiocarbon dates, Uerpmann expresses the contemporaneity with the blade industries of Qatar-B and related industries found in Dhofar and the Wahiba Sands (ibid. 88).

For the Early Neolithic of the Arabian Peninsula, Amirkhanov distinguishes between eastern and southern Arabia. The Eastern Arabian Early Neolithic cultural complex is characterised by flat cores with two striking platforms and a predominance of blade blanks. Tanged arrowheads and points on blades are the leading tool types for this complex. Following Amirkhanov: “This complex demonstrates its cultural similarity to the prepottery Neolithic B in the Near East (PPNB).” (Amirkhanov 1997:248)

The next facies, the ‘Saruq Facies’, is characterised by the occurrence of bifacial, retouched tools (bifacial foliates). Tanged and barbed arrowheads as the type fossils of the Arabian Bifacial Tradition were not found within the context of this facies. Nevertheless, Uerpmann interprets the Saruq Facies as a local variant of the Arabian Bifacial Tradition, which expanded into the coastal part of the entire Oman Peninsula to succeed the Wutayya Facies in the first half of the 5th millennium cal BC (ibid.).

In contrast, characteristics of the Southern Arabian Early Neolithic cultural complex are the absence of a blade industry, flake cores with a single striking platform, a developed technique of bifacial secondary treatment and a large quantity of trihedral and flat points (ibid. 249). Radiocarbon results date the beginning of this cultural complex to the mid 8th millennium cal BC. Concerning the origin of these industries, Amirkhanov states: “This variant most likely was formed on the basis of local substrate and was developing independently rather in conditions of isolation. There is a foundation to suppose its contacts with the bearers of PPNB culture, which nevertheless did not result in any shifts of regional specifics of the local Neolithic.” (Amirkhanov 1997:249)

During the course of the 4th millennium cal BC, various local facies can be distinguished. The ‘Ra’s al-Hamra Facies’, which represents the major phase of the shell midden formation on the northern coast of the Sultanate of Oman, dates to about 4000 cal BC. This facies is characterised by an absence of bifacial foliates, arrowheads and other recurring tool forms. Only piercing tools and drills seem to be characteristic (ibid. 91p.). Another local facies falling within this time horizon is the so called ‘Bir Bira Facies’, which was identified in the area around Sur.

Amirkhanov further suggests a relationship between the emergence of this early Neolithic and the “first noticeable moistening during the Holocene period in Arabia” (ibid.). The end of the Early Neolithic marks the disappearance of the Eastern Arabian cultural complex in the early 5th millennium cal BC and the synchronous transformation of the Southern Arabian cultural complex into the Late Neolithic. Concerning cultural contacts, Amirkhanov states a change in the orientation from the Near East (prevailing in the Early Neolithic) to northern Africa, though connections to Mesopotamia for eastern Arabia and the Levant for northern Arabia remained during the entire Neolithic (ibid.).

The ‘Bandar Jissa Facies’ represents the end of the Stone Age sequence of Uerpmann’s outline. Associated with a simple stone tool industry, the presence of metal artefacts suggests a general contemporaneity with the Early Bronze Age occupations in the interior of the Oman Peninsula (ibid. 105).

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CHAPTER 1 at ath-Thayyila III (WTHiii), the authors suggest a hunting economy during this time (Cleuziou & Tosi 1998:123).

The early stage of the Late Neolithic in Arabia is seen as characterised by an appearance of tanged arrowheads with bifacial treatment, as well as large, flat, bifacially retouched, non-tanged points as a typological link of this culture with the local Early Neolithic. The developed stage of the Late Neolithic, dated to the 4th and 3rd millennium cal BC, is described as a period of flourishing and further decline of the ‘Desert Neolithic’ in Arabia.

The second configuration is entitled with ‘hunting, gathering and fishing’ between the 7th and 6th millennium. Corresponding lithic industries are Kapel’s B-Group in Qatar and related blade dominated assemblages in Saudi Arabia, shell midden sites on the Omani coast, lithic inventories (with Fasad points) found in Dhofar, and coastal and highland sites in Yemen. While 14C dates indicate a broad contemporaneity for these sites, Cleuziou and Tosi clearly distinguish between assemblages with a true blade technology in eastern Arabia and flake dominated assemblages in central and south Arabia. Further impacts of the eastern Arabian assemblages, which were seen as derived from the Levantine PPNB, were neglected (ibid. 124). In the coastal areas, fishing forms the economical basis for the second configuration, while at other (inland) sites, hunting has been seen as the main economic factor. The presence of apparently domesticated cattle in the Yemen highlands is noted and interpreted as a point of connection to the third configuration.

“Stone industry of these sites is characterised by flat cores with parallel chipping, flake being the main type of blank, perfect technique of bifacial retouch, and the greatest for the local Neolithic diversity of flat tanged and non-tanged arrowheads, combined with trihedral points.” (ibid. 250)

This Late Neolithic cultural complex can be found in a wide geographical range, while some areas, such as the Mahrian plateau and Dhofar, lack corresponding industries. In these areas, a coeval industry is identified by Amirkhanov, which is characterised by the presence of different types of trihedral points contrary to the ‘Desert Neolithic’ (ibid.). Concerning cultural connections of the Late Neolithic complexes in Arabia to the surrounding areas, Amirkhanov suggests similarities between the Arabian Neolithic and Fayum A in northern Africa, the latter receiving the trihedral points from the Arabian Neolithic (ibid.).

The third configuration is paraphrased as the time when domestication and exchange intensified on the Arabian Peninsula. It points to a time interval between 5500 and 4000 cal BC. In contrast to other authors, Cleuziou and Tosi avoid the label ‘Neolithic’. The third configuration consists of coastal sites along the shores of the Persian Gulf (including Kapel’s A, C, and D-Groups and shell middens with ‘Ubeid ceramic), the vast majority of shell midden sites along the coasts of Oman and Yemen, as well as the Rub‘ al-Khali Neolithic sites. The diversity among the aforementioned industries is also pointed out. The general similarities of these sites are seen as the result of exchange networks both on the coast and in the interior. As in the previous configurations, the archaeozoological evidence is interpreted in terms of a prevailing hunting/gathering economy, with differences based on specific ecological situations. At the coastal sites, fishing and mollusc gathering dominate, while domesticated animals were of minor importance. Economic tasks in the interior concentrated on hunting, while the existence of cattle pastoralists is suggested for the Yemeni highlands (ibid. 125p.). Cleuziou and Tosi address the question of the presence of domesticated animals on the Arabian Peninsula, but disapprove the idea of mobile herders as an established economy:

S. CLEUZIOU AND M. TOSI 1998 S. Cleuziou and M. Tosi (1998) developed a corresponding structuring of the Holocene Stone Age cultures. They subdivide the Early and Middle Holocene into four configurations based on economic, social and technological considerations. Because they primarily emphasise changes within society, the correspondence of their structuring is less explicit than those systems based on technological and typological considerations. Climatic conditions as the imperative prerequisite for economic and social changes are widely neglected, though used as a framework for the chronological delineation of the different configurations. The first configuration is presented as ‘the empty quarter of the Holocene’, a term which is unmasked as a myth. This myth can be ascribed to the lack of knowledge at the beginning of the 1990s, when no indications existed for the presence of people on the Arabian Peninsula at the beginning of the Holocene.

“Nous n’entendons pas montrer que l’Arabie aurait été plus avancée dans la voie du «progrès» représenté par le néolithique qu’on ne le pense généralement, mais seulement que ces options étaient présentes, bien que leur utilisation soit restée marginale dans une économie de chasse-cueillette davantage préoccupée de consommation immédiate et de partage que de la consommation différée et de l’accumulation des produits de l’agriculture et de l’élevage.”(ibid. 126)

Sites to fill this gap in the knowledge of the Stone Age history in Arabia were identified on the Omani coast (Wadi Wutayya), North Yemen (Khabarut 1) and South Yemen (ath-Thayyilah III) mainly on the basis of radiocarbon dates, which place these sites roughly between 9000 and 7500 cal BC. Cleuziou and Tosi do not broach the issues concerning the origin of this Early Holocene occupation of the Arabian Peninsula, but place it before the onset of moister climatic conditions. Based on finds of cattle bones

In addition, seasonality and short term movements as elements of a mobile herding economy are neglected. Corresponding evidence, such as the absence of permanent

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA hedral rods. The assemblages of the Thayyilan industry also include some bifacial elements, such as large foliates and trihedral drills, but add a broad spectrum of non-standardised tools. Because of its geographical restriction to the Yemeni highland, the term ‘Upland Neolithic Tradition’ in contrast to the Arabian Bifacial Tradition was introduced by F. Fedele for the Thayyilan industry. Fedele presumes that the Qutran industry precedes the Thayyilan industry, the latter of which forms the substratum for the lithic industry of the Bronze Age (Fedele 1985:372). Both industries occur on sites with architectural remains that consist of small oval huts (Edens & Wilkinson 1998:63p.).

settlement structures at most coastal sites and in the interior, are interpreted in terms of camp sites used by huntergatherer groups for specific tasks (ibid. 127). The fourth configuration of Cleuziou and Tosi comprises the time during the 4th millennium cal BC after the end of the Holocene humid phase. During this time, the authors suggest remarkable social and economic changes representing the transition to Bronze Age societies. For the interior, they propose the beginning of an oasis agriculture and herding economy. For the coastal regions, an intensification of marine exploitation is mentioned for this time. Exchange networks are seen as supplemental to an increased use of local resources, which distributed both everyday needs and objects of symbolic wealth (ibid. 128).

The last unit described by Edens and Wilkinson is represented by shell middens and lithic scatters along the Arabian littoral. The sites are typically located in a rich mosaic of palaeoenvironments that offered a broad range of subsistence options. The lithic industries associated with these sites show some artefact types similar to the Arabian Bifacial Tradition. But other aspects of the chipped stone assemblages (e.g. backed points and microlithic lunates) represent unique elements that differ considerably from the ABT (ibid. 65). The chronological range of these sites based on radiocarbon dates spans a time between the late 7th millennium and the late 4th millennium BC with a main cluster between 4200 and 3300 cal BC (ibid. 68).

C. EDENS AND T. WILKINSON 1998 A general structuring of the Holocene based on technological and typological considerations was formulated for the southern part of the Arabian Peninsula by C. Edens and T. Wilkinson in 1998. They subdivide this period into four geographically and temporally distinct entities: 1) a true blade industry with similarities to the Levantine PPNB, found predominantly in north-western Arabia; 2) the Arabian Bifacial Tradition; 3) an ‘Upland Neolithic Tradition’ localised in the Yemeni highlands; and, 4) a distinct industry found around the Arabian littoral (Edens & Wilkinson 1998:62).

J. ZARINS 2001 In a relatively recent attempt to structure the Holocene archaeological complexes of southern Arabia, J. Zarins follows the established schema of a tripartite subdivision of the post-Palaeolithic. To do so, he uses the term ‘Neolithic’ in a strict typological and technical sense (Zarins 2007).

All of these distinct groups were subsumed under the general heading ‘Neolithic’ with an explicit economic meaning: “Early food-producing economies in the Arabian peninsula are slowly becoming known and are associated with several chronologically and geographically distinct lithic industries.” (ibid.)

Stage 1, also referred to as ‘Neolithic 1’, spans the time range between 6500 and 5000 cal BC. It is characterised by projectile points and other tools created from a blade tradition. Following Zarins, sites of this period have been found in Qatar, the Nejd plateau, Wadi Wutayya, the Wahiba Sands and on the Ja’alan coast. Zarins explicitly subsumes the Qatar-B related blade industries into this period, as well as flake dominated industries with blade-like Fasad points in south-eastern Arabia (Zarins 2001, 2007).

The first unit of Edens and Wilkinson with its geographic focus in Qatar and the Eastern Province of Saudi Arabia is defined by the presence of a true blade industry, already described as Qatar B-Group. Chronologically this entity is placed between the 8th and 6th millennia cal BC. This group is identical to Kapel’s B-Group and Potts’ ‘Late Prehistoric A’. The second unit of Edens and Wilkinson is the Arabian Bifacial Tradition (ABT) characterised by stemmed points, foliates, and lanceolates. Widespread throughout the entire Arabian Peninsula with a geographical focus in the desert interior, the chronological range of this group is given in a broad range between 6000 and 3500 cal BC with remarkable local differences.

Zarins’ Stage 2 refers to the geographically widespread Arabian Bifacial Tradition dated between 5000 and 3500 cal BC:

The third unit identified by Edens and Wilkinson is geographically restricted to the Yemeni highland. Here, two distinct industries, the Qutran and the Thayyilan, existed at almost the same time as the Arabian Bifacial Tradition. The Qutran industry with its closer relationship to the ABT is characterised by large and small bifacial points, and tri-

Concerning the northern and central part of the Arabian Peninsula, Zarins proposes intimate ties to the Southern Levant during this time in terms of lithic traditions and rock art. For the social background of these similarities, the author suggests a “widespread pastoral nomadic complex tied to the settled zones of the north”, while noting the ab-

“In Arabia as a whole, a veritable explosion of population occurs during this period, with occupation of all distinctive environments for the first time. The lithic hallmarks of Arabia are a wide variety of tanged, bifacial projectile points…” (Zarins 1998:187)

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CHAPTER 1 ond well-established foundation of Arabian Holocene prehistory, the Arabian Bifacial Tradition (cf. Spoor 1997:152).

sence of ceramics as a hallmark of the northern Pottery Neolithic period (ibid.). Zarins’ Stage 3 of the Holocene Stone Age sequence in Arabia points to a final phase within the Arabian Bifacial Tradition defined by the presence of “very finely knapped slightly notched points called trihedral rods” (Zarins 2007). These points are seen as imitations of bronze points that were produced by specialists.

The hallmark of this second entity, often referred to as Arabian Bifacial Tradition (sensu Edens 1982, 1988b), is the presence of bifacially retouched, winged and tanged arrowheads in the lithic assemblages. This entity covers almost the entire Arabian Peninsula, but can be found in its most distinctive form in the desert areas of southern Arabia. In other geographic regions adjacent to the Rub‘ alKhali, local variants of the Arabian Bifacial Tradition occur, having developed mainly during its later phase. These later forms may represent special adaptations to local environmental conditions.

2.2 A NEW PROPOSAL In addition to the technological and typological classification of the stone artefact assemblages and radiocarbon dates, the reconstruction of climatic conditions played a significant role in the structuring of Holocene sites. As early as the mid-1950s, more humid climatic conditions were suspected for the period in which these ‘Neolithic’ assemblages were produced (Zeuner 1954:135). This assumption was later supported by radiocarbon dates of lake sediments by H.A. McClure (1976) which yielded an age between 8500 and 5000 cal BC. This time range, in some cases slightly modified, was used by subsequent authors to bracket the major cultural phenomena related to the postPalaeolithic history of the Arabian Peninsula (Edens 1982:122, 1988b:15, M. Uerpmann 1992:103, Cleuziou & Tosi 1998:122). Although a subdivision of this Early to Middle Holocene humid phase was already suggested by L. Driester-Hass (1973:221), the possible influences of these climatic fluctuations with regard to the human history of the Arabian Peninsula were rarely considered by archaeologists. But a substantial advance in climatic studies during the last years indicates the existence of at least one major phase of drier climatic conditions in Arabia. This phase punctuates the Early to Middle Holocene humid phase between 6800 and 6000 cal BC (Mayewski et al. 2004). Because this is the time when most authors consistently suggest the end of the early cultural complexes on the Arabian Peninsula and, a little later, the onset of the Arabian Bifacial Tradition, climatic influences on human societies must be considered.

The chronological relationship of both entities is fairly well established by a small number of stratified sites where both complexes are documented in a stratigraphic succession, and on the basis of radiocarbon dates. In most cases, the first complex is set around 6000 cal BC, while the beginning of the second is fixed between 6000 and 5500 cal BC. Interestingly enough, while significant differences between the lithic technology and economic behaviour of both complexes were demonstrated (cf. ‘Ain Qannas, Masry 1997:65pp.), there seems to be a virtual absence of scientific hypotheses about the internal relationship between the two complexes–if one existed–or about the reasons for its lack. Presently, most authors concur on the existence of a chronologically early archaeological complex that points to a Levantine origin. For the second complex, evidence for the relationship between the Levant and its southern adjacent area, the Arabian Peninsula, is scarce. Nonetheless, there are some aspects in the lifeways of the societies in which the ABT originates which can be interpreted in terms of a Levantine heritage. Specifically, the existence of a mobile herding economy and some aspects of domestic architecture support this hypothesis (cf. Beech et al. 2005). To unify and expand these classification schemes, I propose a new terminology geared toward the schema suggested by Amirkhanov (1997) for the relative chronology of the Arabian Peninsula. In the following discussion the terms ‘Palaeolithic’ and ‘Neolithic’ will refer explicitly to the prevailing subsistence strategy and do not identify typological or technological traits (contra Zarins 2007).

The preceding review of the evolution of classification schemes for the Holocene of the Arabian Peninsula reveals wide analogies among the different scholars. However, in all of these schemes two different entities are distinguished. The first entity is characterised by a true blade industry with close formal relations to the Neolithic Levant and which was first described as B-Group by H. Kapel in the 1960s. The geographic focus of this industry is the north-eastern part of the Arabian Peninsula, but it is probably present in central and north-western Arabia as well. The status of the lithic assemblages containing Fasad points, repeatedly seen as related to the Qatar-B industries, is considered unresolved. An internal relationship between B-Group blade arrowhead points and Fasad points cannot be excluded at the present state of research. But it is also possible that the latter assemblages represent a geographically and/or chronologically distinct entity within the sec-

The climatic history of Arabia during the Early and Middle Holocene has been used as a general framework for the absolute chronology of this classification. A phase of moister climatic conditions lasting from the beginning of the Holocene (ca. 8500 cal BC) through the Middle Holocene (ca. 4000 cal BC) enabled human population groups to inhabit the interior of Arabia. This time of ameliorated climatic conditions was weakened during the 7th millennium cal BC by an event of rapid climatic change (Mayewski et

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA

Fig. 1: Chronological and spatial structure of Holocene prehistoric entities in Arabia.

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CHAPTER 1 At the end of the 5th millennium cal BC climatic deterioration occurs in southern Arabia, prograding from north to south. During this time substantial settlements were established along the coast of south-eastern Arabia, and these benefited from local adaptations to richer environmental niches (cf. Capital Area in Oman, Uerpmann & Uerpmann 2003:259). At the same time environmental conditions worsened in the interior and could no longer sustain substantial human occupation. Concerning the subsistence system on the coasts, the diet depended both on marine fauna and domesticated animals (ibid.). To differentiate between these later, local, environmental adaptations and the previous period of prosperous occupations in the interior of the Arabian Peninsula, the term ‘Late Neolithic’ will be used for the corresponding cultural complexes.

al. 2004). This event further structured the human occupation of Arabia. For the first quarter of the Holocene, the evidence of human population groups in southern Arabia is sparse, and knowledge about prevailing subsistence strategies can only be deduced from indirect sources. The time frame, geographic isolation, and the distribution of the wild ancestors of later domesticated animals are arguments against a producing economy during the Early Holocene in southern Arabia. Therefore, the term ‘Southern Arabian Late Palaeolithic’ is suggested to subsume hunter-gatherer groups inhabiting the southern part of the Arabian Peninsula at the end of the Pleistocene and into the beginning of the Holocene. The corresponding lithic industries are dominated by flakes; there is no evidence for a true blade technology. Bifacial retouch occurs, but is restricted to the south-western part of the Arabian Peninsula, pointing to a closer link with east Africa.

The term ‘Post Neolithic’ will be used sensu Amirkhanov (1997) for cultural complexes synchronous with the early Arabian Bronze Age, but which are dominated by lithic industries. For these cultural complexes in south-eastern Arabia, the exploitation of domesticated animals (and possibly plants) remains important, even as the climatic deterioration forced the use of local (marine) resources. In other areas the establishment of oasis agriculture and urban centres indicates the emergence of the Bronze Age.

In contrast to southern Arabia, the Early Holocene of north, east, and to some extent, central Arabia, is more closely linked to the origin of the Neolithic in the Mediterranean Levant. There is only sparse evidence for the presence of Pre-Pottery Neolithic A (PPNA) population groups around the north-western margin of the Arabian Peninsula. But during the PPNB, a southward expansion of economic and cultural elements is detectable in the Southern Levant, which successively filtered into the north-western part of the Arabian Peninsula (Fujii 2006a, 2006b, Betts 1989). At the end of the PPNB, a mobile herding economy was established at the eastern fringes of the Mediterranean Levant, which further penetrated the Arabian Peninsula from the north to as far south as Qatar, and possibly beyond. Because this dispersion is directly connected with the Levantine Neolithic, the term ‘Northern Arabian Early Neolithic’ will be used for the corresponding cultural complexes. They include the PPNB-related industries dominated by a true blade technology and the presence of blade arrowheads. Chronologically, the Southern Arabian Late Palaeolithic and the Northern Arabian Early Neolithic should be considered as widely contemporaneous.

3 WHY NEOLITHIC? It was V. G. Childe in his 1934 publication “New Light on the Most Ancient East” who stressed the importance of a shift in the prevailing subsistence strategy as the fundamental revolution towards the Neolithic. But the term Neolithic had already been introduced by Lubbock in 1865, who further divided the Stone Age according to Thomsen’s Three Age System into an earlier phase characterised by chipped stone (Palaeolithic) and a later phase with ground or polished stone tools (Neolithic). While Childe added supplementary attributes to characterise the Neolithic, including the existence of pottery, agriculture and substantial architecture, in more recent times the subsistence base became the prime attribute of the Neolithic (Thomas 1994:362pp.).

The geographic dichotomy between the northern and southern part of the Arabian Peninsula blurs during the Middle Holocene. The artefact assemblages belonging to the Arabian Bifacial Tradition can be found over a wide area in Arabia. Because there is strong evidence for the presence of domesticated animals associated with this lithic tradition, the term ‘Middle Neolithic’ should be used for the corresponding cultural complexes. To clarify the local idiosyncrasies that depend on specific environments, a tripartite terminology is proposed. The term ‘Inland Middle Neolithic’ is used for population groups adapted to the environments of the interior of the Arabian Peninsula, ‘Upland Middle Neolithic’ for Neolithic occurrences in the highlands of south-western Arabia and ‘Coastal Middle Neolithic’ for littoral adaptations.

An attempt to transfer this terminology to the Arabian Peninsula demonstrates that post-Pleistocene archaeological entities share some characteristics of the Neolithic (e.g. the presence of domesticated animals), but lack others (pottery). To resolve this problem of classification, two solutions can be proposed: the avoidance of an already assigned terminology or the identification of a prime attribute. The avoidance of an existing terminology allows the study of regional developments without concern for the classification of archaeological data. In this way, the history of a region can be studied directly on the basis of available data (cf. Uerpmann 1992). But for supra-regional comparisons, such a procedure seems inappropriate because it obscures existing parallels.

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA In the following chapter, the general evidence for a prevailing herding economy on the Arabian Peninsula during the first part of the Holocene is discussed. One major focal point addresses the issue of a local origin for domesticated animals in Arabia versus their derivation from the Neolithic Levant.

The second possibility is to look for the most important attribute of the Neolithic and use it as a prime marker. As such, the primacy of the subsistence strategy in the definition of the Neolithic period is widely, though not universally, accepted. Here, this position is adopted with the following consideration: the presence of domesticated animals in archaeological assemblages on the Arabian Peninsula during the Early Holocene legitimates the classification of these archaeological cultural entities as ‘Neolithic’.

4.1 ARGUMENTS FOR AUTOCHTHONOUS DEVELOPMENTS The idea that an independent centre of domestication developed in Arabia is spectacular for archaeologists, because it provides an opportunity to re-evaluate and compare common models for the development of the Neolithic in other areas of the world. But the material evidence for the autochthonous development of domesticated animals in Arabia is meagre.

4 EARLY HERDERS ON THE ARABIAN PENINSULA “The only definite conclusion to emerge from the Qatar sites is that they demonstrate the presence of hunters preparing their equipment sometime before the VIth millennium.” (Inizan 1988:205)

Before the 1980s western archaeologists perceived the Arabian Peninsula as the backyard to the surrounding ‘centres of civilisation’ in Mesopotamia, northern Africa and India. This view was supported by the known material evidence from Arabia. There were no indications of early agriculture, a prerequisite for sedentary societies, and prehistoric urban or religious centres with monumental architecture were absent. It seemed obvious that this area did not contribute to the development of the Neolithic or the emergence of early city-states. In addition, the scarcity of natural resources was linked to marginality and poverty, so this area seemed to represent an unfruitful field of investigation for archaeologists.

Until recently archaeologists have favoured the view that it was predominantly groups of hunter-gatherer who roamed the wide landmass of the Arabian Peninsula during the Early Holocene (Cleuziou et al. 2002:20, McCorriston et al. 2002:83, Cleuziou & Tosi 1998:123p., Edens & Wilkinson 1998:68, Potts 1993:168, Tosi 1986a). In some environments, such as highland and coastal communities, these groups incorporated domesticated animals (sheep, goat and cattle) to broaden their subsistence base. Thus, finds of bones belonging to domesticated species are seen as evidence for local domestication (Cleuziou et al. 2002:11, Cleuziou & Tosi 1998:123p.). Although rarely explicitly noted, the assumption of hunting and gathering as the predominant way of life is based on the overwhelming number of arrowheads found at countless locations on the Arabian Peninsula (Uerpmann et al. 2000:231). The comparatively small number of archaeological sites with clear evidence for the presence of domesticated animals supported the view that these bones represented an exotic complement to hunting.

This attitude was severely criticised, especially by M. Tosi (1986a). His intention was to draw attention to the Arabian Peninsula as an area with its own strengths and contributions to world history. Concerning the pre-Bronze Age period Tosi points to environmental adaptations of specialised foragers. He assumes a noticeable increase in wild biomass during the Early Holocene based on the moister climatic conditions that hunter-gatherers exploited. Marine resources formed a second foundation for the development of more complex societies and were seen as a pre-adaptive feature leading to food production (Tosi 1986a:473). Tosi concludes with a tripartite subdivision of “the long prelude to Arabian civilization”, of which the first two are of wider interest. During a formative stage represented by the ‘Terminal Stone Age’, intensive exploitation of desert, highland and littoral ecosystems took place from the Late Pleistocene through the Early Holocene. During the subsequent stage, early forms of food production were developed within the different ecosystems:

In contrast to this, recent excavations at the site of Buhais18 in the UAE yield convincing evidence for a prevailing mobile herding economy based on domesticated sheep, goat and cattle in the interior of the Arabian Peninsula between approximately 5200 and 4200 cal BC. The small proportion of wild animals at this site indicates the minor importance of hunting (Uerpmann et al. 2000, Uerpmann & Uerpmann 2000:48). The evidence emerging from this site changes the interpretation of other Early Holocene sites with bone preservation on the Arabian Peninsula. Almost all sites with preserved bone remains show evidence for the presence of domesticated animals, independent of the geographical setting, whether coastal, interior or montane. This evidence supports a completely different view with regard to the importance of domesticated animals in the economy of the Early Holocene: Domesticates formed the basis of subsistence, while hunting, gathering and fishing complemented the everyday diet whenever possible.

“The Middle Holocene Arabian foragers represent at any rate an extreme case of successful harvesting for a hyperarid environment…Progress in subsistence would have been represented in the first case by a shift to ovicaprid herding and camel domestication following overexploitation of the wild populations and in the second one by an increasing capacity for off-shore fishing and long-range navigation. Thus we may assert that the conquests of

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CHAPTER 1 originates more with the intention of promoting and highlighting Arabia’s past than from the archaeological evidence.

the desert and the ocean are the contributions of Arabian foragers to the overall development of civilization.” (ibid. 472)

The concept of the Arabian Peninsula as an autonomous centre of domestication with independent cultural developments was picked up by subsequent colleagues:

4.2 EVIDENCE FOR THE SPREAD OF THE NEOLITHIC HERDING ECONOMY FROM THE LEVANT

“Arabia is the only hyperarid region of the globe where in relatively few millennia populations of hunter-gatherers accumulated capital from primary resources, based on the opportunistic exploitation of plants and animals of local ancestry, like date palms and camels, ultimately establishing an independent civilization. Nowhere else in the arid world post-Pleistocene foragers have been as successful in the final outcome of their subsistence strategies.” (Cleuziou et al. 2002:11)

Arguments against an autochthonous development in Arabia and for a spread of the Neolithic herding economy from the Levant are twofold. The first argument concerns the question of the presence of people inhabiting the Arabian Peninsula at the onset of the Holocene. If there is only meagre evidence for the presence of human populations in Arabia at all, autochthonous developments without external influences are less plausible. This is because the sustainable establishment of an innovation results from the complex interaction of a high number of people with a comparable cultural background (Rogers & Shoemaker 1971, Rogers 1995:17pp., Eisenhauer 1999:222). The second argument against an autochthonous development of the Neolithic concerns the spatial distribution of the wild ancestors of the domesticated animals, a point which will be discussed further below.

The domestication of animals and specific forms of a herding economy are seen as local developments based on indigenous hunting, gathering and fishing societies: “Transitions from types of foraging economies to the different forms of pastoralism certainly took place from the end of the early Holocene in several areas of Oman, Yemen and Saudi Arabia...” (ibid. 17)

General models of the origin of domestication assume either a shortage of food resources as the initial condition or an abundance, which stimulated interactions with plants and animals. A shortage as the initial condition for domestication can be caused by a degradation of environmental conditions (Childe 1936, Close 1992), population pressure (Cohen 1977), sedentism (Binford 1968, Liebermann 1993, McCorriston & Hole 1991) or a strengthened requirement caused by social changes (Bender 1978). In contrast, abundance can also be seen as the initial condition for domestication. In almost all models this abundance is caused by favourable environmental conditions (Sauer 1952), that promote a dependence on specific resources (Uerpmann 1979). If these environmental conditions change, the unintended dependence on these resources forces their domestication.

THE PRESENCE OF HUMAN POPULATIONS AS A NECESSARY PREREQUISITE TO IDIGENOUS DEVELOPMENTS To investigate the question of the presence of human populations in Arabia prior to the Neolithic dispersal as it has been hypothesised in the introduction of this book further, it is first necessary to define the geographic extent of Arabia. The western, southern and eastern borders of the Arabian Peninsula are defined, in an anticlockwise direction, by the coasts of the Red Sea, Gulf of Aden, Arabian Sea, Gulf of Oman, and the Arabian Gulf. While the Arabian Gulf dried out during parts of the Pleistocene (Lambeck 1996, Teller et al. 2000), its refilling started about 14,000 BP. Sea level reached its peak between 6000 and 4000 BP when it stood at about 1–2 m above its present level (Lambeck 1996:54p., cf. Hellyer 2002 for archaeological evidence in the UAE). Thus although the eastern boundary of the Arabian Peninsula has varied, for most of the period under consideration it has remained well-defined. A similar situation can be assumed on the Red Sea coast, where significant fluctuations in sea level were observed during the Pleistocene (Siddall et al. 2003). Because of its different topography with steeper slopes and a greater general depth, sea level fluctuations in the Red Sea had a minor impact on the location of its shorelines compared to the Persian Gulf coast. Comparable circumstances can also be assumed for the coastline of the Indian Ocean, where sea level fluctuations with local effects can be verified during the Pleistocene (Hannß 1991).

A modification of the abundance model is proposed by Cleuziou, Tosi and Zarins for the Arabian Peninsula. Vast herds of desert animals roaming in this region formed the basis of subsistence for groups of hunter-gatherer who acquired the capability of controlling their animal stocks. This ability together with the intensified use of local resources led to an increase in residential stability and a subsistence dominated by domesticated species after 5000 cal BC (Cleuziou et al. 2002: 18pp.). Unfortunately, this proposed model for an independent domestication in Arabia is not further explicated, nor is its material evidence explained. One has to assume that the latter is based mainly on stone artefacts–the great number of arrowhead interpreted as an indicator of hunting activity–and early radiocarbon dates for sites with archaeozoological remains that were identified as domesticates in southern Arabia. Because of the lack of detailed models that describe the way of local domestication, one can presume that the hypothesis of an independent centre of domestication in Arabia

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA climatic conditions during the Younger Dryas. The exceptions were a few areas where occupation was sustained by favourable environmental conditions (e.g., Azraq Oasis, Jordan (cf. Betts 1998:11pp.)). At the same time, new settlements were founded in the surrounding area, especially in the river valley of the middle Euphrates.

The boundaries towards the north are less well defined. The northward extension of the Red Sea, marked by the Dead Sea Rift, Jordan Valley, Beqaa Plain and Ghab Valley can be considered as a natural borderline roughly separating the Mediterranean Levant from the Jordanian Highland and the Syrian Desert. But especially in the far north, the boundary remains elusive. Geologically, the Zagros Mountain chain, an uplifted area where a continental collision between the Arabian and Asian Plates is occurring, defines the northern border of the Arabian Peninsula. Geographically, the Arabian Peninsula merges into the Syrian Desert with no clearly defined boundary. To avoid this problem, a northern borderline is set with the course of the Euphrates River flowing into the Persian Gulf. It is clear that this spatial border was neither impermeable nor static in a historical sense, but from the Neolithic onwards it roughly follows the demarcation line between sedentary agricultural societies and more desert-orientated communities (cf. Cleuziou et al. 2002:13).

During the PPNA (10,000–8000 cal BC) settlements began to flourish along the northern border of the Arabian Peninsula, in the Jordan and Euphrates Valleys, and the area around Damascus. While smaller sites could be identified at the fringes of the semi-arid steppe and desert, evidence for the presence of PPNA groups in the arid regions of northern Arabia is almost absent. This situation changes during the PPNB and PPNC (8700– 6200 cal BC) when substantial numbers of sites reoccupied the arid areas that were previously avoided and little used (Bar-Yosef & Meadow 1995:81). Different economic tasks can be assumed depending on the prevailing environmental conditions. While permanent settlements with extensive architectural remains point to agricultural activities in areas with substantial water supply (El Kowm Oasis), more ephemeral sites may indicate hunting activities or represent the remains of mobile herders with domesticated animals in the open steppe (Black Desert, Azraq Basin, southern Jordan, Negev, and Sinai). Starting from the Levant this penetration into the arid areas of northern Arabia reaches the steppe of Syria, the Jordanian Plateau and north-central Saudi Arabia (Zarins 1990:40pp.).

This permeable border is important for the settlement history of the northern margin of the Arabian Peninsula. It seems highly probable that this area was inhabited, or at least visited by human population groups from the surrounding Mediterranean and mountainous regions. On the contrary, evidence for an uninterrupted settlement in northern Arabia is meagre, especially for the time of the Last Glacial Maximum (LGM) between 22,000 and 18,000 BP. For this interval, a small and sparsely distributed population is assumed (Akkermans & Schwartz 2003:14).

Since the beginning of Stone Age research on the Arabian Peninsula, H. Kapel (1967:18) noted the morphological similarity of some of the artefacts he found in his B-Group assemblages with PPNB forms of the Southern Levant and northern Arabia. This similarity was originally discovered on the basis of typological studies on projectile points that resemble Amuq points of the Levant and was confirmed by technological studies on projectile points and naviform cores (Inizan 1980a, 1980b, 1988). While these finds provide evidence for a southward migration of PPNB-related groups as far as Qatar, very few additional sites with similar artefact forms are known from the northern part of the Arabian Peninsula outside Qatar (cf. Edens 2001:140, Masry 1997, Zarins 1992:46p.). The southernmost site which shows a relation to PPNB assemblages is Jebel Daba south of the Jabrin Oasis in central Saudi Arabia (Masry 1997). Further south, artefact assemblages which resemble PPNB artefact forms are not documented.

Between 16,000 and 12,500 cal BC, hunter-gatherer groups exploited diverse parts of the Syrian Desert. These groups belong to a wider typo-technological tradition referred to as ‘Geometric Kebaran’ (for definition and discussion of terminology, see Bar-Yosef 1981, GoringMorris 1995, Byrd 1998). They occupied the Mediterranean coastal plain and woodland, but also the semi-arid steppe and desert (Bar-Yosef & Meadow 1995:54). The settlements in the desert areas were usually found close to water sources, such as perennial springs, seasonal ponds or lakes, and drainage confluences. Concentrations of settlement occur in special ecological situations, such as the El Kowm and Palmyra Oases in Syria and the Azraq Basin in Jordan. These sites are predominantly small and ephemeral, indicating frequent moves of the people in a potentially year-round cycle (cf. Liebermann 1993). During the early Natufian (12,500–11,500 cal BC) the general settlement pattern differs little from that of the preceding period. The main focus of settlement activities remained the Mediterranean Levant, while the more arid areas were characterised by a low population density, small group size, and dispersed and fluctuating occupation.

As demonstrated above, the northern fringe of the Arabian Peninsula was almost permanently inhabited by human population groups since the Last Glacial Maximum. Fluctuations in the population density and settlement pattern may be related to climatic changes, but the spread of the PPNB/PPNC into the arid areas to the south and east has also been related to a shift from the prevailing hunting to a mobile herding economy (Köhler-Rollefson 1992, Byrd 1992).

However, this situation changed during the late Natufian (11,500–10,000 cal BC) when sites appear to have been almost abandoned in the arid and semi-arid regions (Akkermans & Schwartz 2003:28) as the result of deteriorating

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CHAPTER 1 2003:255). Therefore, it is likely that the inhabitants of Wadi Wutayya immigrated after the climatic amelioration in this area, either from the north-west or, more likely, from the south-west. The latter would indicate a Late Pleistocene hunter-gatherer population in southern Arabia that had begun to expand due to more favourable climatic conditions (ibid.).

With a regional focus towards central and southern Arabia, this picture changes significantly. Evidence for Late Pleistocene and Early Holocene settlements in this area is meagre and restricted to just a few find complexes identified during the last decade. Although this might be due to the limitations of the present archaeological knowledge, traces of Late Pleistocene/Early Holocene human settlements remain underrepresented with regard to the growing number of archaeological sites investigated in Arabia. It has only be recently suggested by J. Rose (2006) that during periods of hyperarid climatic conditions the Arabian Peninsula became depopulated by human groups (tabula rasa events during OIS 2, OIS 4 and possibly OIS 6, Rose 2006:51). Whether this has to be taken as literally or not, a reduction of the population density during periods of severe climatic conditions is plausible. The latter model would fit well the sparse evidence for the presence of people in Arabia during the Late Pleistocene and Early Holocene, irrespective of whether these populations survived the LGM in Arabia or dispersed into southern Arabia after the phase of hyperaridity.

It has been demonstrated that the population density in central, southern and south-eastern Arabia was very low at the onset of the Holocene. Archaeological evidence for the presence of human population groups is restricted to a few environmentally favoured areas within the highlands of Yemen or the northern Omani coast. On the one hand, the patchy nature of these areas reduced the possibilities of communicating and exchanging ideas. Therefore, it also reduced the chances of successfully establishing innovations such as the domestication of animals. In addition geographic isolation forced local diversification and divergent cultural developments, which further reduced the possibilities of successfully establishing an innovation. On the other hand, there is strong evidence for the penetration of Neolithic groups into north-eastern and central Arabia from the north during the Early Holocene. This development might have influenced the populations living in the south. Therefore, the development towards independent domestication of animals in southern Arabia seems less likely than the adoption of an already established economy, which would allow for the successful exploitation of a wider variety of environments.

A first industry which might be related to the Late Pleistocene was identified in south-western Saudi Arabia by C. Edens (2001). Several surface collections from the edge of the escarpment of Jebel Tuwayq were characterised by the presence of bladelet cores, bladelets and backed bladelets. Because of technological and typological affinities to the Levantine Natufian, Edens tends to place these assemblages in the Late Pleistocene (Edens 2001:141). A single radiocarbon date obtained from a hearth at the site of Wadi Wutayya in the Capital Area of Oman indicates the presence of Late Palaeolithic hunter-gatherers on the south-eastern part of Arabia (Uerpmann & Uerpmann 2003:255). Only a few knapped stone artefacts that point to a flake-based industry were found associated with this fireplace (ibid. 61).

THE DISTRIBUTION OF THE NATURAL HABITATS OF SHEEP, GOAT AND CATTLE The second argument against an independent development of the Neolithic in southern Arabia relates to the natural distribution of the wild ancestors of the principal domesticates in Arabia during the Neolithic period. Although geographically adjacent, the majority of the Arabian Peninsula is located beyond the natural habitats of the wild ancestors of domesticated sheep, goat and cattle (Uerpmann & Uerpmann 2003:219p., Uerpmann 1989a:164, Uerpmann 1989b, Uerpmann 1987, Harrison 1968).

Other evidence for the presence of people in the southern part of the Arabian Peninsula at the beginning of the Holocene comes from the site of Khabarut 1 in Yemen (Amirkhanov 1996, 1997:63pp.). Here, several archaeological horizons were found in a stratified context. Below a radiocarbon dated humic horizon (layer 4) representing a terminus ante quem, several “cultural layers” with stone artefacts were discovered. Analogous to south-eastern Arabia, the blank production of these assemblages was again dominated by flakes (Amirkhanov 1996:138).

The earliest evidence for the domestication of sheep, goat and cattle around the margins of the Arabian Peninsula comes from different areas of the Fertile Crescent within the natural habitats of their wild forms. At the onset of the Holocene, the wild ancestor of goats (Capra aegagrus) could be found in a wide region covering the mountainous areas of the Levant, as well as the Zagros, Taurus and AntiTaurus Mountains. Wild goats may have inhabited southeast Arabia as well (Uerpmann 1989b, Uerpmann & Uerpmann 2000:43). The early domestication of goat is documented in the Zagros during the Early and Middle PPNB (Zeder 1999) and probably in the Anti-Taurus region of the Upper Euphrates and Tigris Basins during the Early PPNB (Peters et al. 1999, Peters et al. 2002:111). An

The origins of these human population groups remain unclear. Climatic data point to a phase of severe aridity over most of central and south-eastern Arabia during the Last Glacial Maximum, which turned this landmass into a relatively hostile environment. But it is possible that not all regions were uninhabitable to hunters-gatherers. The situation might especially be different for southern and southeastern Arabia, which may still have been favourable for humans during this period (Uerpmann & Uerpmann

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA

Fig. 3: Natural habitat of Bos taurus (after Uerpmann 1989b).

ning the broad valleys of the Zagros and Taurus Mountains, the Mesopotamian Plain, the Euphrates Basin and the Mediterranean Levant (Uerpmann 1989b). Its southern extent into the Arabian Peninsula is, however, controversial. Finds of cattle bones within Early Holocene lake sediments (McClure 1978) and archaeological sites in Yemen (Fedele 1988:35) may represent remains of domesticated exogenous or wild indigenous animals. The latter would enlarge their natural habitat remarkably. Clear evidence for the local domestication of cattle within the Levant comes from the middle Euphrates region during the Middle PPNB (Helmer et al. 2002, Peters et al. 1999) and possibly in the Mediterranean and Southern Levant, but then remarkably later during the Late PPNB/PPNC (Horowitz et al. 1999). As demonstrated, most parts of the Arabian Peninsula lies beyond the natural habitat of Capra, Ovis and Bos. Therefore, animal bones found in Early Holocene archaeological contexts located beyond their natural habitats serve as indicators against their local domestication in Arabia. Consequently, they had to disperse across the Arabian Peninsula as domesticates in the form of reproductively viable herds. This supports an origin of this specialised mobile herding economy from the inner fringes of the Fertile Crescent, that is, from areas adjacent to the original centres of domestication. Assuming the involvement of mobile pastoralism in the initial spread of domesticated animals from the northern part of the Levant to the south (Martin 1999), a similar mechanism can be postulated for the dispersion of mixed herds of goat, sheep and cattle across parts of the Arabian Peninsula.

Fig. 2: Natural habitat of a) Capra aegagrus and b) Ovis orientalis (after Uerpmann 1989b).

independent development of caprine herding in the Southern Levant is discussed for the Late PPNB (Horowitz et al. 1999, Peters et al. 1999). The early centres of domestication of the ancestor of domesticated sheep (Ovis orientalis) can be found in the Northern Levant during the Early PPNB (Peters et al. 1999). The occurrence of domesticated sheep in the Southern Levant during the Late PPNB is beyond the range of Ovis orientalis, and therefore results from a process of spatial diffusion (Horowitz et al. 1999, Martin 1999). Although Ovis orientalis was endemic to the Zagros region, domesticated sheep was imported to this area as well (Zeder 1999).

This emergence of a herding economy with sheep, goat and cattle as the dominant species might have represented a strategy of risk minimisation (Khazanov 1984:27). The keeping of mixed herds of sheep and goat is related to their

The extent of the natural habitats of the wild ancestor of domesticated cattle, Bos taurus, is less well known, span-

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CHAPTER 1 Dripstones indicate a different climatic regime for the Early Holocene both in the Levant and in southern Arabia. The best evidence for moister climatic conditions in the southern part of the Arabian Peninsula comes from speleothems in northern (Hoti Cave, dripstone H5: Burns et al. 1998, Neff 2001:44pp.) and southern Oman (Qunf Cave, dripstone Q5: Fleitmann et al. 2003a, 2003b). Both dripstones show corresponding ages with a confident age model. The δ18O isotopic signal of the dripstones shifts towards lower values around 8000 cal BC, indicating an increasing influence of the Indian Ocean Monsoon (IOM). A delay of approximately 500 years can be observed for the Hoti Cave, located about 700 km northeast of Qunf Cave. This delay corresponds well with the southern Arabian climatic regime driven by the IOM. During the LGM/Late Pleistocene (and again today) the inter-tropical convergence zone (ITCZ), which is the driving force behind the IOM, was located south of the Arabian landmass. A northward shift during the Early Holocene between 8000 and 4000 cal BC influenced the southern parts of Arabia earlier than the northern parts. A southward shift in the ITCZ is evident at the end of the Early Holocene, when the dripstone in northern Oman stopped growing at about 4000 cal BC. The speleothems in southern Oman continued to grow until 1000 cal BC. Supplementary evidence for this climate change comes from marine sediment cores in the western (Jung et al. 2004) and eastern Arabian Sea (Doose-Rolinski et al. 2001, Staubwasser et al. 2003).

complementary feeding behaviour and different climatic tolerance. While sheep prefer to graze herbaceous annuals and tolerate colder and wetter conditions, goats prefer to browse perennial plants and withstand heat and drought better (Harris 2002:73, Lancaster & Lancaster 1991). Cattle represent a third complementary element. They were better adapted to wooded and forested environments (Harris 2002:74). Two different hypotheses exist for the nature of the spread of domesticated animals into the steppic regions of the Southern Levant. Based on evidence from the PPNC site of ‘Ain Ghazal in southern Jordan, Köhler-Rollefson (1992) suggests the development of large-scale, mobile, caprine pastoralism in the Southern Levant as the basis of a subsistence economy. Byrd (1992) sees indications that preexisting hunter-gatherers selectively integrated domesticated animals into their economy to reduce the risk of diet shortage. Martin (1999:94p.) suggests an important influx of domesticated animals during the Early Late Neolithic (ELN) in southern Jordan (ibid.) dating to about 6830– 6270 cal BC. Rejecting both the nomadism and integration/adoption hypotheses to varying degrees, she introduces the idea of “herders who also hunt and trap, or hunter/ trappers who also have herd animals” (ibid.). Subsistence strategies aimed at acquiring and producing are not exclusive among mobile herders and result from fluctuations in herd sizes due to natural disasters, forcing the exploitation of all available resources:

Similar changes occurred in the Northern Levant, but are connected to different atmospheric mechanisms within the eastern Mediterranean zone. A dripstone sequence from Soreq Cave in Israel indicates high precipitation with rainfall of 675–950 mm/yr. between 8000 and 5000 cal BC, almost twice that of the present (Bar-Matthews et al. 1997:165).

“It is no coincidence that amongst many nomads a striving to increase their production base by direct utilization of the products of nature may be observed, meaning that hunting, gathering and even fishing are widespread amongst these nomads as supplementary forms of economic activity.” (Khazanov 1984:78)

Once such an economic system of herder-hunters was established to exploit the natural resources of the steppic areas in the Levant, it could easily spread across the Arabian Peninsula under the more favourable environmental conditions of the Early Holocene (cf. Zarins 1990:54).

Evidence for moister climatic conditions with higher rainfall and increased surface runoff at the north-western part of the Arabian Peninsula between 7200 and 5200 cal BC comes from marine sediment cores taken from the northern Red Sea (Arz et al. 2003). This is explained by enhanced rainfall and a southward extension of precipitation from Mediterranean sources (Arz et al. 2003:121).

5 ENVIRONMENTAL CONDITIONS AS A PREREQUISITE FOR THE NEOLITHIC DISPERSAL

Bringing the climatic evidence from both northern and southern Arabia together, climatic conditions in general facilitated the Neolithic dispersal from the Levant towards southern Arabia via the inner landmass of the Arabian Peninsula between 8000 and 5000 cal BC. But during this 3000-year period, evidence exists for at least one rapid climatic change (RCC) event between 7000 and 6000 cal BC (Mayewski et al. 2004:248pp.). During this RCC that assumedly affected the dispersal of herders across Arabia, a cooling event occurred in the North Atlantic around 6200 cal BC (Alley et al. 1997) which induced more frequent polar, north-westerly (winter) outbreaks in the eastern Mediterranean Sea. At lower latitudes in the Northern Hemisphere, this event marks a period of increased aridity

Under present environmental conditions, the spread of mobile pastoralists from the Levant over the Arabian Peninsula is impossible due to sparse vegetation and the absence of surface water sources in most parts of the landmass. If one accepts a Levantine origin for the mobile herding economy on the Arabian Peninsula, it is obvious that remarkable changes in the environment must have taken place since then. Evidence for these changes comes from a wide range of data, including speleothems, lake sediments, pollen, phytoliths and faunal remains.

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA A compilation of dates from Holocene palaeolakes and palaeosols in southern Arabia (Parker et al. 2006) shows a strong correlation between the development of lakes and soils and the palaeoclimatic record deduced from dripstones (Yemeni lake and soil data vs. Q5 δ18O). The lakes mainly existed during the Early Holocene between 9000 and 5500 cal BC, when δ18O values of the dripstones indicate the strongest IOM influence. As a general trend palaeolakes seem to predate the development of palaeosol horizons. This result may be partly related to dating problems caused by the “hard water effect”, which makes 14C dates older than they should be (cf. Radies et al. 2005:113p.). Similar Early Holocene lake deposits were found in northern Arabia in the Nafud and Nafud ‘Asir areas (Schulz & Whitney 1986) which conform to the present dune relief and were dated between 8400 and 5400 BP uncal. In this area the lake deposits were stratified with interbedded aeolian sands indicating the presence of fleeting water bodies (ibid. 180) that were dependent upon the highly fluctuating patterns of precipitation. In general, the presence of palaeolakes results from meteorological conditions in which annual precipitation exceeds potential annual evaporation, enabling surface run-off. This availability of potable water for humans and animals can be seen as a prerequisite for a mobile herding economy within the interior of the Arabian Peninsula. Palaeobotanical studies in south-eastern and south-western Arabia indicate major changes in the vegetation density during the Holocene, but not in the composition of species. Combined pollen and phytolith analysis at a palaeolake in the UAE (Parker et al. 2004) indicate an increase in woodland elements between 6300 and 3900 cal BC. The scrub woodland was composed mainly of Acacia and Prosopis, representing still today the highest proportion of sparse trees in this area (Ghazanfar 1998). After 3900 cal BC woodland density declined and a more open landscape developed with a predominance of tall grasses (Parker et al. 2004:673). In contrast to south-eastern Arabia, a Holocene pollen record from al-Hawa (Ramlat al-Sab’atayn, Yemen) did not show a remarkable increase in the woodland cover, although Acacia and Commiphora were present (Lézine et al. 1998, Lézine et al. 2007). The authors suggest a remnant of desert-type vegetation with a dominance of herbaceous taxa at the time a lake developed between 10,000 and 5500 cal BC (Lézine et al. 2007:245). These differences might be related to different influences of the IOM, which seemed stronger in south-western Arabia, but less influential in the north-eastern shadow of the Yemeni highland, where north-west trade winds continued to dominate during the Early Holocene (Lézine et al. 1998:296).

Fig. 4: Oxygen isotopic signals from dripstones: Soreq cave (Bar Matthews et al. 2003), Hoti cave (Neff 2001) and Qunf cave (Fleitmann et al. 2003a)

midway through the Early Holocene phase of moister climatic conditions. This event is also clearly visible in the speleothem record in southern Arabia, where higher δ18O values indicate a weakening of the Indian Summer Monsoon. The general trend towards moister climatic conditions during the Early and Middle Holocene affected both water availability and vegetation cover. Hydrologic response can be found in the development of lake deposits and palaeosols in the interior of the southern Arabian Peninsula (McClure 1976, McClure 1978, Schulz & Whitney 1986, Lézine et al. 1998, Parker et al. 2004, Radies et al. 2005, Wilkinson 2005, Lézine et al. 2007).

In the northern part of the Arabian Peninsula the pollen spectra from palaeolakes in the Nafud and Nafud ‘Asir are dominated by grasses, shrubs and herbs, and a few trees, a botanical spectrum that resembles the present and, by analogy, indicates a semi-desert of grasses and some shrubs.

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CHAPTER 1 But based on evidence for the presence of swamps in this area during the Early Holocene, Schulz and Whitney (1986:181) argue for a denser herb cover.

Therefore, it is not plausible to assume a hunter-gatherer economy on the basis of the wild forms of sheep, goat and cattle in Arabia and their subsequent local domestication.

A similar situation in which only minor changes within the composition of species occurs is exhibited by the faunal data from other sites. At al-Buhais 18 the same spectrum of wild animal species that are adapted to the desert environment today also occurred during the 5th millennium cal BC (Uerpmann et al. 2000:231).

In contrary, sites without evidence of domesticated sheep, goat and cattle can be seen at first glance as indicators of a hunting-based economy. But because hunting could be a subsistence strategy supplemental to a herding economy, the absence of domesticates may not represent compelling evidence for a hunting-based economy.

In summary during the Early Holocene parts of the Arabian Peninsula were covered by denser vegetation with a higher portion of woodland than today. Higher precipitation encouraged the development of palaeolakes fed by rainfall and/or higher surface run-off. These changes in environmental conditions enabled the dispersion of mobile pastoralists who departed from the Levant and spread over most areas of the Arabian Peninsula.

Clear evidence for a mixed herding economy including sheep, goat and cattle comes from the ‘Ubeid-related site of H3 (cellular building phase) in Kuwait (Carter & Crawford 2001), the Neolithic graveyard of al-Buhais 18 in the UAE (Uerpmann & Uerpmann 2000) and the site of Jebel Qutran (GQi) in Yemen (Bökönyi 1990). Although represented by only three sites and distributed over a wide geographic area, radiocarbon dates support that this economy was well established in the 5th millennium cal BC. Additional support for this view comes from a bigger sample of sites on which cattle bones occur together with unspecified sheep/goat remains. Not only do these sites cover almost all parts and ecologic regions of the Arabian Peninsula, but they also expand the time range for the presence of a pastoral economy from the 6th to the 4th millennium cal BC.

6 THE ADVENT OF A HERDING ECONOMY IN ARABIA The archaeozoological evidence for the spread of Neolithic mobile herders over Arabia is meagre. In contrast to the high number of Early Holocene archaeological sites on the southern part of the Arabian Peninsula where stone artefacts were found, only a few of the sites yielded faunal remains. But the lack of faunal remains does not point to the general absence of animals at these sites, but rather to taphonomical and post depositional processes.

Fewer sites give evidence for a restricted spectrum of domesticated species, for example, where either sheep and goat occur without cattle, or goat and cattle occur without sheep. Because the sites with evidence for sheep and goat without remains of cattle are all located on the coast of the Arabian Gulf and the Gulf of Oman, ecological reasons for these restrictions appear likely. The same scenario may explain the absence of sheep in ‘Ain Qannas. These sites generally correspond to the picture emerging from the other sites mentioned above and provide evidence for the existence of a mixed pastoral economy that was supplemented by marine resources along the coast.

A compilation of Early and Middle Holocene sites in southern Arabia where animal bones were found (Table 1) supports the hypothesis that the majority of them confirm the presence of domesticated animals. At sites where the status of domesticated animals is unclear due to poor bone preservation, a positive status can be assumed when the geographic location of the site lies outside the natural habitat of the species. The only species for which this procedure might be questionable is cattle, but only because the limitations of their natural habitat are less well understood. Their distribution might stretch as far south as the ‘Asir or even into the highlands of Yemen (Uerpmann & Uerpmann 2003:220).

A different view emerges from south-west Arabia. The sites which yielded animal remains predominantly show evidence for cattle, sometimes together with the remains of wild animals. Domesticated sheep and goat are widely absent from these assemblages. Although not confirmed in all cases, data from some of these sites strongly indicate that the cattle were domesticated. This is explicitly stated for the sites of ash-Shumah and Surud-1 and queried at the site of Jahahbah 1. The radiocarbon dates from ash-Shumah suggest the presence of domesticated cattle in the early 6th millennium cal BC, a date that is suggestive for an early local domestication of cattle (Cattani & Bökönyi 2002:50). If both the determination of the cattle remains as domesticates and the 14C dates are confirmed as valid, this may point to a different development in south-western Arabia.

The presence of sheep and goat at sites on the Arabian Peninsula beyond their natural habitat provides strong evidence for their domestication outside Arabia in the Levant. Their subsequent dispersal by human groups cannot be proved due to a lack of archaeozoological information. This assumption is also likely regarding cattle. The presence of sheep, goat and cattle bones together within the same archaeological context is interpreted as further evidence for their domesticated status and Levantine origin. All three taxa can be kept together in a herd, but their natural habitats show a strong separation with the only overlap in the Anti-Taurus region (Uerpmann 1987).

During the 4th millennium a change to a mixed herding economy can be confirmed for south-western Arabia at the

31

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA

Fig. 5: Spatial distribution and composition of Early and Middle Holocene archaeozoological samples in central and southern Arabia.

bia during the Early Holocene. Even the proposal for a subsistence strategy based on cattle breeding alone (Kallweit 2003:61) ignores the evidence for sheep and goat at many of the sites. This subsistence strategy may have been restricted to the highlands of Yemen during the 6th and 5th millennia cal BC, but does not represent a valid model for the entire Arabian Peninsula during the Middle Holocene.

inland sites of Wadi al-Thayyilah (WTHiii) in the main Neolithic horizon, al-Akiya 5 and the coastal site of Surud1, which then resembles the general view of a pastoral economy on the Arabian Peninsula during this time. A third group of sites provides no visible evidence for the presence of domesticated animals, although wild animal remains were found. Predominantly located in the interior of the Arabian Peninsula, these sites can be seen as special activity/hunting sites supplementing the economy of mobile pastoralists, or simply sites where no slaughtering of domesticated animals took place. While no radiocarbon dates are available for these faunal assemblages, their association with stone artefact assemblages belonging to the techno-complex of the Arabian Bifacial Tradition suggest a date in the 5th millennium cal BC.

For all other areas of Arabia, a mixed herding economy based on sheep, goat and cattle can be hypothesised as the prevailing subsistence strategy from at least the mid-6th millennium cal BC onwards. These herders managed to use a wide range of environmental resources in addition to their flocks that served as “walking food insurance”. This strategy becomes especially clear at the coastal sites, where in comparison to the substantial amount of marine resources (seashells and fish bones), bones from domesticated animals are underrepresented. One has to recall that just a handful of individual bones belonging to a domesticated animal represents not only one individual, but rather,

With regard to the sparse archaeozoological information, there is almost no argument for assuming that the hunting of wild animals was the exclusive subsistence base in Ara-

32

CHAPTER 1 Site level or layer Buhais 18 (BHS 18)

Country

H3 cellular building phase

Kuwait

Jabal Qutran (GQi)

Yemen

Dosariyah

Saudi Arabia Oman

Ras al-Hamra 5 (RH 5)

WTHiii / main Neolithic horizon associated with Tayylah palaeosoil al-Akiya 5 (Ak-5) Surdud-1 (SRD-1)

Lab No.

Dating uncal BP

UAE

GU-10450 GU-10447 GU-10448

6135±50 (ashy sed.) 4570±40 (ashy sed.) 4110±40 (ashy sed.)

Dating cal BC1 5200-42003

5215-4945 3496-3101 2872-2504

aceramic neolithic

I-5786 GX-2818 Bln-3395 Bln-3149 Bln-3399 Bln-3404 Bln-3153

6135±120 (mar.) 6900±330 (mar.) 6060±60 (ashy sed.) 5480±60 (ch.) 5130±60 (ch) 4990±50 (ch.) 4730±60 (ch)

Yemen

4737-41434 5903-45194 5207-4800 4457-4176 4046-3777 3942-3658 3638-3372 6000-30005

Wild ungulates2

Domesticates

Source

Equus africanus, Camelus sp., Oryx leucoryx, Capra sp. Gazella sp.

sheep, goat, cattle

Uerpmann & Uerpmann 2000:43pp.

goat, sheep, cattle

Carter & Crawford 2001:3p.

sheep, goat , cattle

Bökönyi 1990

sheep/goat, cattle

Masry 1997:113

sheep/goat, cattle

Uerpmann & Uerpmann 2003:244, Uerpmann 2003:79

sheep/goat (domest.?), cattle (domest.?)

Fedele 1988:35

equidae

sheep/goat, cattle sheep/goat (domest.?), cattle

Kallweit 1996:42 Tosi 1986b:415

present

goat, sheep

Uerpmann 1987, Masry 1997

Equus africanus, Gazella sp., Hemitragus jayakari Equus africanus

goat, sheep

Uerpmann & Uerpmann 2003:210

goat, sheep, dog

Uerpmann & Uerpmann 2003:210 Uerpmann & Uerpmann 2003:244

Bos primigenius, Equus sp., Gazella sp., Capra ibex present Equus africanus, Gazella gazella, Hemitragus jayakari

Yemen Yemen

Bln-4724 GX-13782 Beta-23580 Beta-23579

4950±47 (ch.) 6325±90 (mar) 5100±90 (mar.) 5010±80 (mar.)

3912-3643 4947-44746 6 3614-3102 3499-30006

Abu Khamis

Saudi Arabia

GX-2820 GX-2819 UGa-315

Khor Milkh 1 (KM 1)

Oman

5660±250 (mar.) 5565±255 (ch.) 5750±65 (mar.) 5250±50 (mar. mix)

4458-33464 4999-3800 4223-38064 3515-30977

Khor Milkh 2 (KM 2) Ras al-Hamra 6 (RH 6)

Oman

4925±50 (mar. mix)

3097-26747

Hv-13196 Bln-4315 Bln-4316 Hv-13195

6075±80 (ashy sed.) 5970±80 (ch.) 5750±60 (ch.) 5615±60 (ashy sed.)

Gazella sp., Hemitragus jayakari

goat, sheep, dog

Sharorah

Saudi Arabia UAE

5214-4796 5197-4622 4722-4459 4582-4340 ABT

AA-52544 AA-52543 AA-52546 Hv-10001 Hv-13199 Hv-10004 Bln-3140 P-2739 P-2740 P-2741

6395±60 (ashy sed.) 6220±45 (ch.) 5830±45 (ch.) 6910±105 (mar.) 6645±105 (mar.) 5230±65 (ashy sed.) 4760±100 (ch.) 5140±200 (ch.) 4320±200 (ch.) 4050±50 (ch.)

5479-5228 5303-5055 4790-4554 5434-49097 5183-46017 4245-3824 3771-3343 4365-3520 3623-2459 2858-2469 ABT

Gazella sp.

sheep/goat (domest.?)

Gazella sp.

goat, sheep/goat

Uerpmann & Uerpmann 2003:244

Equus africanus

sheep/goat

Uerpmann & Uerpmann 2003:244 Edens 1982:119

7060±445 (ch.) 6655±320 (ch.) 6885±325 (ch.) 7770±95 (mar.)

7027-5054 6212-4855 6443-5083 6385-59806

Gazella sp., equidae Equus africanus

goat (domest.?)

GX-2821 GX-2823 GX-2824 GX-13781

goat, cattle

Uerpmann 1987, Masry 1997:108p.

cattle

OS-16935 OS-16950

6080±55 (ch.) 6070±40 (ch.)

cattle (domest.?)

Cattani & Bökönyi 2002:45p. McCorriston et al. 2002:75

Beta-23582 Beta-23581

7500±80 (mar.) 6870±100 (mar.)

5207-4845 5202-4844 older 6000-30005 6068-57116 5533-50906

cattle (domest.?)

Tosi 1986b:408

5466-4988

cattle (domest.?)

Kallweit 2001:245

Dalma 11 (DA 11)

Oman

Ras al-Hamra 10 (RH 10)

Oman

Ras al-Hamra 4 (RH 4)

Oman

Janub alMutabthat Ain Qannas levels 4-14

Saudi Arabia Saudi Arabia

ash-Shumah (ASH) Khuzma asShumlya WTHiii / older Neolithic horizon Gahabah-1 (JHB 1)

Yemen

MK-2, Sada

Yemen

6250±90 (ch.)

Rub al Khali playas: Mundafan basin area Jiledah

Saudi Arabia

Holocene

Yemen Yemen Yemen

Saudi Arabia

Ramlat Sabatayn (HARii)

Saudi Arabia

Shaqqat el Khariyta C Khor 2 (M et D)

Saudi Arabia Qatar

ABT

MC-2020 MC-2019

6560±120 (mar.) 6290±100 (sed.)

5222-4593 5473-5021

1 Calib Rev. 5.0.1., 2 Sigma range 2 Identification according to the authors 3 foll. Uerpmann et al. 2000 4 Marine calibration, R 180±35 (Southon et al. 2002)

sheep/goat?

Equus africanus, Gazella sp. present Bos primigenius Bos primigenius, Equus africanus, equidae Bubalus antiquus/Bos primigenius Bos sp., Gazella sp., capridae, equidae Gazella sp., Equus (? cf. asinus), Capra sp. Equus sp., Gazella sp., Capra sp. (? cf. ibex) Gazella sp. Gazella sp.

Smith & Maranjian 1962:21p. Popescou 2003:53

Fedele 1988:35

McClure 1978:262 Edens 1982:119

Fedele, report in Di Mario 1989:142p. Zeuner 1954:135 Inizan 1980b:59p.

5 According to dating of a similar palaeosoil in the Dhamar region (Wilkinson et al. 1997, Wilkinson 2005) 6 Marine calibration, R 110±38 (Southon et al. 2002) 7 Marine calibration, R 297±51 (Southon et al. 2002)

Table 1: Early and Middle Holocene archaeozoological samples in central and southern Arabia.

This combined herding/hunting economy finds its origin at the inner margins of the Fertile Crescent. During the Middle and Late PPNB, the Southern Levant shows a general delay in the emergence of new artefact forms compared to the Northern Levant (Gopher 1994:252p.) and in the introduction of domesticated sheep. This delay points to a southward diffusion of innovations from the Northern Levant. This southward expansion might not have stopped at the margins of the Arabian Peninsula, but could also have

an entire, reproductively viable herd. It is very unlikely that a single animal made its way from the Levant to southern Arabia5. Therefore, it is justifiable to speak of ‘herders, who also hunt’ instead of hunters who also herded animals.

5 For

minimum herd sizes of historic and present mobile herders, cf. Khazanov 1984:30pp.

33

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA lithisation in Arabia. While strong interrelations between the Neolithic Levant and Arabia implicate interdependent developments, a lack of interaction might promote the autochthonous origin of domesticates in Arabia.

reached its north-western part as well (Ingraham et al. 1981:66pp., Fujii 2006a, 2006b). During the Late PPNB and PPNC, a mobile herding economy became established at the margin of the Mediterranean Southern Levant and seemed to successively penetrate the Arabian Peninsula.

However, the archaeological material evidence in fact supports the view of strong relations between the Levant and northern Arabia, not only due to their spatial connection. During the Early Holocene, a southward trend in the dispersion of the Neolithic with domesticated animals within the Levant is evident. This dispersal also penetrated into the northern part of the Arabian Peninsula.

Although there is no archaeozoological evidence for the presence of domesticates in connection with this dispersal, strong parallels to Levantine assemblages can be demonstrated in the samples of stone artefacts (cf. Chapter 4). Considering the generally lower population density in Arabia during the Early Holocene, it is much more likely that these artefact assemblages are the material remains of human population groups that migrated from the Levant, instead of originating with acculturated, indigenous groups.

This dispersal is reflected in the general structuring of the Arabian Prehistory. There is a general trend towards a bipartition of Early Holocene cultural complexes in a chronological sense. Artefact assemblages belonging to the earlier complex show distinct geographic differences that indicate regional developments. In northern and northeastern Arabia strong typological and technological similarities between Arabian blade-dominated artefact assemblages and Levantine PPNB/PPNC inventories show dependent developments during this time. These similarities point to an active dispersal of Levantine Neolithic groups over the northern part of the Arabian Peninsula. For the corresponding cultural complexes, the term ‘Northern Arabian Early Neolithic’ is proposed here, in consideration of the prevailing subsistence economy as the prime attribute.

7 SUMMARY: THE DISPERSAL OF THE NEOLITHIC In this chapter it has been attempted to demonstrate the complex history of research in Arabia and its far-reaching implications for the present perception of the prehistory of this region. Scholars have traditionally perceived Arabia as an area lying on the periphery of the known civilisations with nothing to offer, but much to receive. This view was based both on a lack of knowledge due to restricted access into the area that was caused by the political situation and on the rarity of monumental prehistoric remains.

In contrast, Levantine influences are less well verifiable for the southern part of Arabia, where technological examinations of artefact assemblages point to indigenous developments or eastern African influences. Because the presence of domesticated animals in the economy can be widely excluded, the term ‘Southern Arabian Late Palaeolithic’ is introduced here for these population groups.

Research in the Stone Age periods started at the beginning of the 20th century, but until the 1980s it was dominated by reconnaissance surveys without a research agenda. The presence of different complexes of stone artefacts was documented, but information about their chronological position and interrelation remained scarce due to the absence of stratified sites. Chronological classifications were carried out based on typological correlates.

This geographic distinction blurs during the later phase of the Early Holocene, when a largely homogenous cultural complex appears over a vast territory: the Arabian Bifacial Tradition. Because this term is based on the predominantly bifacial character of stone implements and does not consider economic characteristics, the corresponding artefact assemblages will be subsumed as ‘Middle Neolithic’.

This situation changed significantly from the 1980’s onwards, when systematic research into the Stone Age prehistory of Arabia started. Traditional classification schemes were disproved with the introduction of radiocarbon dating, and new research foci were established. Regarding the perception of the Arabian Peninsula, a reverse effect can be noted during the last decades. There is a trend towards the negation of external influences in prehistoric Arabia, both by Arabian and foreign scholars. This can be seen as a response to the long-lasting undervaluation of the prehistory of this region, but it is again a subjective appraisal. The present view on the prehistory of the Arabian Peninsula mirrors more the history of research than its own history.

As of yet, there are no known transitional inventories that would give information about the formation of the Middle Neolithic cultural complexes in Arabia. Looking at technological and typological traits of the stone artefacts alone, a tentative derivation of the Middle Neolithic from a southern Arabian Early Holocene background seems possible. But the associated, prevailing subsistence strategy points in another direction. There is substantial evidence that the forebears of the Middle Neolithic were herders who also hunted. The corresponding herding animals were sheep, goat and cattle, which were originally domesticated in the Levant. Therefore the Arabian Middle Neolithic incorporated two different traditions. The lithic tradition points to

This development is reflected in the discourse concerning the relationship of artefact assemblages found in Qatar. While their Levantine similarities were at first highlighted, they were later neglected. This denial of Levantine relationships has direct implications on the course of the Neo-

34

CHAPTER 1 dition, the simulation will help to explain the distribution of sites and the areas of interaction with southern Arabian hunter-gatherer cultural complexes. Finally, the simulation will allow us to hypothesise about the emergence of the Arabian Middle Neolithic.

stronger southern Arabian provenance, while the subsistence strategy finds its roots at the northern margins of the Arabian Peninsula in the region adjacent to the Levant. The formation period of the Arabian Middle Neolithic closely matches the time interval of the RCC event between 7000 and 6500 cal BC. Therefore an interrelationship between this time of climatic deterioration and the formation of the Middle Neolithic can be hypothesised. That there existed a structural difference between the earlier and later cultural complexes is evident in the spatial patterning of their occurrence. While differences in the assemblages during the Early Neolithic can be traced back to the fact that they resulted from external influences and local developments, the diversity within the Middle Neolithic results from adaptations to local environmental conditions and diversification. Arguments for the origin of the mobile herding economy in the Levant are twofold. First there is only marginal evidence for the presence of human population groups in Arabia at the beginning of the Holocene. Based on climatic evidence, these groups had to retreat to environmentally favoured areas during the Last Glacial Maximum. Geographical isolation reduced the chances for communication and interaction, and therefore, minimized the possibility for a successful establishment of innovations. The second argument against an autochthonous development of the Neolithic in Arabia concerns the distribution of the wild ancestors of sheep, goat and cattle, which formed the basis of the mixed herding economy documented during the later part of the Early Holocene. The early centres of their domestication were located within the zone of their natural distribution, in a broad arc spanning from the Zagros and Taurus mountain chains to the southern Mediterranean Levant. On the contrary, most of the Arabian Peninsula existed outside of the natural habitat for sheep and goat. Thus, a local domestication can be excluded. The dispersal of domesticated animals from the Levant during the Early Holocene involved the movement of human groups originating in the Levant, since domesticated animals were clearly not able to spread over the Arabian Peninsula without human assistance. Local exchange of animals and the knowledge of domestication by indigenous groups provide poor hypotheses, because there is no evidence for substantial population groups in northern Arabia during the Early Holocene. In the dispersal of the Neolithic across Arabia, a strong spatial component is inherent. One has to expect an expansion characterised by environmental factors. As it will be demonstrated in the following chapters, the spread of Neolithic mobile herders from the Levant depended on environmental preconditions. If this hypothesis proves to be right, a simulation of the dispersal, dependent upon environmental conditions, will yield results that can be used as a control against the archaeological evidence. The results of this simulation will make it possible to claim a Levantine origin for the Northern Arabian Early Neolithic. In ad-

35

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA

36

CHAPTER 2

CHAPTER 2

“Computer simulation is a well-known method for studying complex systems not amenable to experimental or theoretical investigation.” (Young 2002:138)

THE DISPERSAL OF THE NEOLITHIC - MODELS AND SIMULATIONS finite number of parameters, which can be explored in more detail.

If we consider the dispersal of the Neolithic over the Arabian Peninsula as a spatial phenomenon, we should be able to investigate the routes over which this spreading occurred. The following chapter describes the development of a conceptual model for the Neolithic dispersal which will later be transformed into a simulation of spreading routes. Both the model and the simulation are determined by two antithetical attitudes: the freedom of humans to make decisions and the environmental setting6 that conditions human decisions. This interplay between the freedom of human choice and the environmental setting can be visualised as a wave propagating through water. As long as no barrier exists, it continues without end, but if it hits a barrier, it will be reflected and refracted.

“…in model building we create an idealised representation of reality in order to demonstrate certain of its properties. Models are made necessary by the complexity of reality... Models convey not the whole truth but a useful and comprehensible part of it.” (Haggett 1965:19)

Model theory can be understood as directly related to universal system theory founded in the 1940s by the biologist L. von Bertalanffy (1968). System theory emphasises that systems are open to and interact with their environments and each other, and can acquire new properties through this. It focuses on the arrangement of the different parts of a system, which connect into a whole, and the relations among them. A system is defined by specific organisational patterns, rather than by the characteristics of the individual elements comprising it. Such systems can be reproduced by models, which then represent a structural adjustment of the original system. Those models which demonstrate global structural similarities to the original system were referred to as isomorphs. The isomorphism of models generates the formal basis for the simulation of real-world phenomena, since it allows the transfer of data from one scientific realm to another. Further on, model building allows for the selection of factors considered as important to the phenomenon under investigation. This selection is a subjective one; it is only obliged to fit realworld observations as closely as possible.

Fig. 6: Reflection and refraction of waves.

The same assumption applies to the spread of the Neolithic, which took place as a spatial process within a defined environment. As long as no environmental restrictions existed, a uniform dispersion can be assumed. But if substantial margins did exist, they should have influenced the potential spreading routes.

In the following discussion, an empirical model for the spread of the Neolithic over the Arabian Peninsula will be developed. It is based on considerations concerning human behaviour in an environmentally restricted geographic space. The main emphasis of the model is placed on the dependence between human population groups and the local environmental conditions that serve as the backdrop on which humans interacted. In contrast, the impact of human agency and social dynamics in regard to the spread of Neolithic herders over Arabia is considered as minor in comparison to the restrictions caused by the environment. Therefore these dynamics are limited in the model to minor operations. In a consecutive step, this conceptual model is transformed into a simulation that can be run on a computer.

1 A MODEL FOR THE DISPERSAL OF NEOLITHIC HERDERS 1.1 WHAT ARE MODELS? Model building is a common scientific procedure to reduce the empirically perceivable complexity of reality. The infinite diversity of circumstances in scientifically investigated phenomena forces simplification and the reduction to a

6 On this general level environmental conditions are not necessarily

restricted to physical environmental factors, but can also include the social environment of people or a group of people.

37

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA

1.2 CURRENT MODELS FOR HUMAN DISPERSALS

ply describing the phenomenon. Scientific approaches deriving from social sciences placed their main emphasis on questions concerning the personal interaction of different individuals or groups of individuals culminating in the dichotomy of colonisation and acculturation (Uerpmann 1979:131pp., Zvelebil 1986a, 1986b, Müller 1993:34pp., Whittle 1996:40pp.). This dichotomy mainly originates in the geographic focus of this kind of research, which was the Neolithisation of Europe. From a Near Eastern perspective, farmers ‘migrated’ from the Near East and ‘colonised’ Europe; farming was ‘introduced’, while Mesolithic hunter-gatherers were ‘absorbed’. In contrast, from a European hunter-gatherer perspective, farming emerged through ‘transition’ from the Mesolithic hunter-gatherer economy to the Neolithic economy, or was ‘adopted’ by local foragers (Zvelebil 1986b:175). In these cases, colonisation and diffusion were often used as explanations of cultural change.

THE SPREAD OF THE NEOLITHIC It was first V.G. Childe in 1928 who proposed the Near East as the original centre of the Neolithic in the Old World. This suggestion was confirmed during extensive fieldwork in the Near East after World War II (Braidwood & Braidwood 1950, Kenyon 1960, Mellaart 1958, 1962). Based on the wide geographic range of Neolithic cultural occurrences observed in Europe and Asia, questions arose concerning the mechanisms of its dispersal. Different approaches to answer this question can be distinguished on the basis of model theory. At the beginning of research on the spread of the Neolithic, empiric models predominated, while during the last decades, formal models became more important in scientific discourse. In these diverse approaches different terminology is used to describe the process of the spread of the Neolithic, and often it is only poorly defined (Clark 1994:306). Migration, dispersal and colonisation imply the physical dislocation of humans together with their material culture, while diffusion might point to the spread of an innovation without the dislocation of people. The concept of demic expansion/diffusion represents a special case based on the reproduction rate and individual mobility.

While generally unpopular as an explanatory concept during the rise of New Archaeology, the topic of colonisation, migration, dispersal and diffusion became redefined as a more biogeographically based process during the 1980s (Rockman 2003:8). This latter approach moves from the level of individual interaction to consider dispersal as a process that involves an entire population on a meta-level. The most influential work regarding the dispersal of the Neolithic into Europe was carried out by A.J. Ammerman and L.L. Cavalli-Sforza (1973, 1984), who proposed a pure demic expansion model as an explanatory concept for the spread of the Neolithic. Similar to Edmonson (1961), the authors first estimated spreading rate was based on the radiocarbon dates of the earliest Neolithic occurrences in Europe. This approach yielded a travel velocity of about 1 km per year (Ammerman & Cavalli-Sforza 1984:58). In a second step, the demic expansion model, introduced as the ‘Wave of Advance’ model, is proposed to explain this empirically observed spreading rate. In this model, the spread of farming over Europe is not seen as the result of cultural diffusion (that is, without invoking the movement or geographic displacement of people). Rather, it is viewed as a demic diffusion in which it is not the idea of farming that spreads, but the farmers themselves who move with their culture. This model is based on two parameters only: population growth and individual migratory activity. Both factors together are used to compute the spreading rate at which a population ‘wave’ propagates into a new territory. In this approach, the quality of geographic space as a factor influencing the spreading rate and spreading routes is not considered, and a normal (Gaussian or Brownian) type of motion is assumed for describing the migratory activity (Ammerman & Cavalli-Sforza 1984:76pp., 111). The mathematical model applied can be traced back to R.A. Fisher (1937) and was later adapted by J. Skellam (1973) to represent the spread of a population multiplying logistically and migrating at a constant rate. Based on the initial population growth rate a and the (average) rate of migra-

Early investigations into the dispersal of the Neolithic during the 1950s and 1960s are clearly influenced by empirical qualitative approaches originating in geographic concepts of spatial diffusion. They show a direct reference to those geographic regions where early Neolithic sites were known. One example of this approach can be found in the work of M.S. Edmonson (1961). Based on relative or absolute chronologies and the Euclidian distance between sites and regions with early Neolithic occurrences, spreading rates for selected innovations (projectile points, ground stone axes, pottery, domesticated plants, domesticated animals and alphabetic writing), were computed for different regions. As a result, Edmonson proposes a spreading rate for the Neolithic of about 1.15 miles (1.85 km) per year. In such an approach, the dispersion of the Neolithic is considered as following straight trajectories connecting regions where Neolithic occurrences were documented. Environmental configurations between the sites are considered only for the land-sea boundaries of continents in determining the Euclidian distance. Other environmental factors were not taken into account as potential parameters that influenced communication and hence, spreading rate (Edmonson 1961:72). This omission was already criticised by several reviewers of this article already at its date of publication (cf. reviews of Becker 1961, Posnansky 1961). Later approaches concentrate on the mechanism of how the dispersion of the Neolithic took place rather than sim-

38

CHAPTER 2 tion m, the dispersal velocity v can be calculated applying the term

“Perhaps the most simplified version of the agricultural frontier occurs in Ammerman and Cavalli-Sforza’s (1973, 1984) ‘Wave of Advance’ model, where this complex phenomenon is reduced to the notion of a uniform front of colonists sweeping across Europe in the manner of a German Panzer divisions.” (Zvelebil 1986a:10p.)

v = 2 × am (Ammerman & Cavalli-Sforza 1984:68). This relation forms the basis of the classical ‘Wave of Advance’ model of the Neolithic transition in Europe.

This criticism has been seized recently by a study of Davison et al. (2006:641p.), which explores the role of environmental factors in the spread of the Neolithic into Europe. The general approach of Davison et al. is to resample the ‘Wave of Advance’ model using the FisherSkellam equation to model population dynamics. But in contrast to the classical ‘Wave of Advance’ model, in this study the equation is supplemented with an advection term for major river valleys and the sea coast, which modifies the speed and direction of the dispersal (Davison et al. 2006:647). In addition, the effect of differences in the carrying capacity in space, one parameter of the Fisher-Skellam equation, is considered through the new parameters of “local altitude” and “geographic latitude”. The results of this modelling procedure are isochron maps that display the modelled advent of the Neolithic in a specific region.

The ‘Wave of Advance’ model proposed in the tradition of Ammermann and Cavalli-Sforza was later expanded and adapted to explain other dispersals in human prehistory (Cavalli-Sforza et al. 1993, Cavalli-Sforza 2002, Fort 2003, Pinhasi et al. 2005). The ‘Wave of Advance’ was also used to model biological range expansions (OrtegaCejas et al. 2004) and the spread of viruses in growing plaques (Fort & Méndez 2002). In 1999, the model was reevaluated and modified by Fort and Méndez (1999a, 1999b), who introduced a time delay into the original equation. They ended up with a new result that fit the archaeological evidence even closer: the classical equation for the ‘Wave of Advance’ model resulted in a predicted spreading rate of 1.41 km/yr, while the modified equation predicted a spreading rate between 0.8 and 1.2 km/yr (Fort & Mendez 1999a:869).

In contrast to the classical ‘Wave of Advance’ model, this incorporation of local environmental conditions leads to a different result: the propagation is remarkably slower at higher latitude, where the carrying capacity is reduced. The inclusion of coastlines and river valleys further modifies this image. As soon as the Danube river valley is reached, the population wave moves rapidly along the river (Davison et al. 2006:648). These differences in the results of modelling place emphasis on the important role of local environmental conditions when applied within the ‘Wave of Advance’ model. Nevertheless, the results obtained from this model are only limited in their sensitivity to environmental constraints. The results represent an approximation on a continental scale, but they do not apply to regional differences.

The latest attempt to support the ‘Wave of Advance’ model with empirical data has been carried out by Pinhasi et al. (2005). Analysing the spatiotemporal occurrence of the Neolithic in Europe, the Near East and Arabia with the help of radiocarbon dates and locations from 735 archaeological sites, the authors calculate a steady spreading rate of the Neolithic ranging from 0.6 to 1.3 km/yr. The fact that these empirical diffusion rates fit well with the predictions of the improved ‘Wave of Advance’ model (Fort & Méndez 1999a, 1999b) is seen as a supporting argument for the model. For the present study it is important to point out that 30 Arabian sites have been considered in the latter analysis. Although not explicitly noted, the inclusion of the Arabian sites indicates at least two implicit assumptions: first, a Levantine origin of the Arabian Neolithic; and second, the proposal of the same process of demic diffusion for the Neolithisation of the Arabian Peninsula as for Europe. However, the latter assumptions can hardly be supported due to the specific character of the ‘Wave of Advance’ model. In fact, Pinhasi et al. mention the sensitivity of their model towards the inclusion of the Arabian sites in their study (Pinhasi et al. 2005:2226). Yet instead of excluding the data in the face of this mismatch, they remain included because the resulting dispersal speed is similar to the one obtained for the other (European) sites used in the study (Pinhasi et al. 2005:2226).

In general, the ‘Wave of Advance’ model implies a continuous random movement driven by steady population growth immediately behind the steep and closed wave front. It was this implication in particular which led to disagreement among scholars, because the model does not fit the picture that emerges from archaeological evidence in any region of Europe. One example is the Neolithic dispersion into Greece, which could be better explained by a modified demic diffusion model that is no longer numerical or mathematical (formal), but rather descriptive (informal). Van Andel and Runnels (1995) point to the fact that small numbers of people arriving in a large, suitable region had much time before another move into another area became necessary. Thus, the dispersion of the Neolithic could be better described by a series of (time-) discrete steps. Within this model, established as the ‘leapfrog’ model, the length of each step and the time intervals between them were influenced by the population growth in each parent area (van Andel & Runnels 1995:497). In contrast to the ‘Wave of Advance’ model, this model explicit-

The importance of the ‘Wave of Advance’ model can be seen in the fact that it can explain the empirically observed spreading rate of the Neolithic into Europe at a satisfying accuracy rather than simply describing it. On the other hand, there is substantial criticism concerning the simplistic assumptions the model implies:

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA tal conditions and spatial dispersal patterns was self-evident. It has been assumed that the cycles of population expansion and contraction provide the historical basis for instantaneous patterns of biological distribution, and that the dispersal of animals and ‘pre-industrial man’ could be compared (Diamond 1977:249). With this approach, biogeography has been used as a framework for the understanding of the spatial distribution of species or human groups.

ly includes environmental conditions as a factor influencing routes of dispersal, which can be seen as a succession of discrete spreading events. Apart from these different approaches, all current models of the spread of the Neolithic assume more or less explicitly the dispersal of Neolithic people who were predominantly farmers. Such a subsistence strategy promotes the establishment of sedentary communities in which spatial mobility played only a minor role. In addition, these models describe the Neolithic dispersal into environments suitable for sedentary agricultural communities. Here, environmental conditions might provide some corridors of communication and dispersal, but did not play the determining role in the spread.

One early example of this approach is the study of the peopling of Australia carried out by Birdsell (1957). He tries to estimate the time required for a population to expand across a former barrier into an unoccupied area. The basis for this calculation is the assumption that no migration occurs until the carrying capacity of a given area is reached. The model itself is spatially explicit, with an assessment of topographic barriers, climatic change and points of possible entry. The actual estimation of the spread is based on the calculation of genetic distances, and the quality of space is incorporated in a wider, descriptive, empirical model.

These assumptions clearly contradict the proposed dispersal of the Neolithic over the Arabian Peninsula in several respects. First, environmental constraints must have been considered. Even under more favourable climatic conditions, the local environment should have had a major impact on the possibilities of dispersal into Arabia and on potential dispersal routes. Second, the Neolithisation of Arabia did not involve sedentary farmers, but rather mobile herding communities. For sedentary groups, continuous exploration of new territories dependent on population growth is plausible. For mobile groups, however, such a scenario seems questionable. Instead, spatial dispersal as a direct result of the mobile way of living is proposed.

During the 1990s, formal models have been widely applied to explain human dispersal. The spatial scale of these investigations reaches from global to continent-wide explorations. Young and Bettinger (1995) apply differential equations to integrate population growth rate, carrying capacity and a diffusion constant (indicating mobility) into a model that is used to explain the global human expansion during the Late Pleistocene. Logistic growth behaviour and random-walk spatial motion form the basis of this model and are applied on a grid cell of 3° by 3° with impermeable boundaries at the land-water interface. For an application of their model to the ‘Out of Africa’ theory, population growth rate and mobility are connected to geographic space with high mobility and growth rates in tropical and subtropical regions as opposed to higher latitudes. The latter is justified by a supposed pre-adaptation of early humans to tropical and subtropical environmental conditions (Young & Bettinger 1995:90). To adjust the model to fit empirical archaeological observations, they assume varying values for the input parameters.

GENERAL MODELS OF DISPERSAL IN PREHISTORIC ARCHAEOLOGY As demonstrated above, current models for the spread of the Neolithic from the Near East cannot be readily applied to the dispersal of Neolithic mobile herders over the Arabian Peninsula because these models implicitly assume both the dispersal of predominantly farming communities and the spread into a widely uniform and suitable environment. The following discussion will explore general models of human dispersal and their application to Pleistocene archaeology. The main emphasis will be placed on models describing the spread of Pleistocene hunter-gatherers into unoccupied areas. I will show that some of the assumptions in these models are appropriate to develop an understanding of the Neolithic dispersal over Arabia and stand in contrast to established models for the spread of the Neolithic. Further on, it will be demonstrate how the qualities and characteristics of space in these models are widely neglected in their restricting influence on the dispersal process.

During the last decade Steele and colleagues have explored the Fisher-Skellam differential equation (Steele et al. 1996, 1998, Hazelwood & Steele 2004) as a model for the peopling of America. It was an explicit goal of this research to evaluate the effects of spatial habitation variation and distribution of geographical barriers. To do so, both time and space were made discrete. A two dimensional lattice with a cell size of 50 km by 50 km, in which each cell has specific fixed values for the habitat terms, and an updated cell-specific value for the human population size has been applied. To integrate changing environmental conditions and therefore differences in the habitats in the model, the broad-scale vegetation cover of North America has been reconstructed for four consecutive time periods. Because the Fisher-Skellam equation expects the carrying ca-

Empirical models dominated the scientific discourse until the 1990s, when formal models began to develop. The empirical models often adopted a biological perspective: the understanding of how and why animals migrate can help to understand the processes of human dispersal. Because the biological approaches are closely tied to environmental studies, an interdependence between general environmen-

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CHAPTER 2 in which species expand include major topographic irregularities like mountain ranges or large bodies of water, it is highly questionable to calculate a rate of spread as though the environment were uniform. As a result of their analyses of the dispersal of different animal species, the authors conclude that the Fisher-Skellam model does not yield successful predictions when long-range movements of species occur (Andow et al. 1990:183).

pacity as one input value, the reconstruction of the vegetation has been recalculated on the basis of known hunter-gatherer population densities in these specific habitats. The resulting spatial heterogeneous carrying capacity surfaces did not affect the wave width and velocity, but the varying population densities at points in space are determined in some way in an unpredictable manner. For the simulation of the Paleoindian dispersal, these four specific surfaces were switched after a simulation period of 500 or 1000 years depending on the time the surfaces represented. The modelling results themselves were only partly confirmed by archaeological evidence that indicates a much faster human dispersal over America than the model output suggests. This discrepancy is discussed in terms of the mode of the dispersal and the characteristics of the FisherSkellam equation: The assumption of high population growth and low migration rates (as it is done for the dispersal of Neolithic farmers into Europe) causes a steep and slow travelling wave, which can be detected through radiocarbon dates obtained from archaeological sites. In contrast, for the peopling of America by mobile huntergatherer groups, higher mobility in relation to a lower population growth rate has to be assumed. This forces a shallow and fast travelling wave, which can hardly be detected by radiocarbon dates (Hazelwood & Steele 2004:677p.). Therefore the application of the Fisher-Skellam equation as a model for the dispersal of population groups with high mobility and low reproduction rates is debatable.

Different attempts have been made to detach from the disadvantages of the Fisher-Skellam equation. With the help of a stochastic simulation Moore (2001) tries to increase the number of variables within a demographic model to evaluate different a priori models of human colonisation of unoccupied regions for their viability. In addition to four demographic variables (sex ratio at birth, distribution of sibships, maternal risk of giving birth, risk of death) he incorporates three cultural variables (marriage choice, polygyny, marriage pool) to the model. This study marks an improvement to the above-mentioned models because it considers a wider range of variables, although its application is restricted to ‘artificial world’ phenomena. It neither incorporates pre-existing human population groups nor the quality of geographic space. Nevertheless, two interesting results of this investigation should be mentioned. A viable colonising pattern with respect to the above-mentioned variables is the ‘string of pearls’ model in which bands are arrayed along a stream or coast line (Moore 2001:405). In such a pattern there is almost no requirement for developing new technology to continue the migration. Groups move forward through a familiar range of ecological opportunities without making adaptations. In contrast, Moore’s ‘outpost’ or ‘small beachhead’ model shows the least viability due to problems in establishing a sustainable marital and demographic regime (Moore 2001:406).

In a more generic way the Fisher-Skellam equation has been applied by Eswaran (2002) as a model of the spread of anatomically modern humans out of Africa. He legitimates the application of the ‘Wave of Advance’ model with the assumption that the movement out of Africa was not a migration of single population groups but a continuous expansion of modern human populations by small random movements, hybridisation and natural selection. In contrast to the above mentioned approach by Steele and colleagues, Eswaran neglects the influence of a diverse geographic space and uses the Fisher-Skellam equation in a one-dimensional array. This disregard of spatial diversity has to be criticised because during the dispersal out of Africa a number of different ecosystems had to be crossed by modern humans, which would have influenced the rate and direction of dispersal.

Young (2002) has developed a completely different model to simulate human migration with a lattice of points distributed according to simple probability rules. These simulations apply an agent-based (particle) approach, where due to the actions of individual agents, complex collective patterns emerge. Certain demographic parameters were assigned to these agents, including birth, death and migration rates. Motion within the simulation is controlled by a probability function, which is used for the simulation of manyparticle systems in physics. The model includes the possibility to consider birth, death, crowding, competition and migration. Therefore, specific problems related to human migration can be assessed: the migration into empty continents, or the effect of competition and migration.

A critical evaluation of the original Fisher-Skellam equation can be found in Andow et al. (1990), who discuss the application of this equation to model the spread of invading organisms in general. They point to two different characteristics of the Fisher-Skellam approach. First, that the patterns of spread observed at the population level do not depend on the intricate details of how individual organisms move, but rather can be deduced from certain statistical properties of ensembles of organisms. Therefore the application of a model describing the whole population is justified. Second, the application of this model in complex and diverse habitats is complicated by environmental heterogeneity causing a non-radial dispersal. Therefore, if habitats

Another model following the principles of a cellular automaton has been applied by Mithen and Reed (2002) to simulate the Plio-Pleistocene hominid dispersal from Africa in respect to environmental and ecological factors on a global scale. The implementation of these factors is seen as essential by the authors, because: “Literature is increasingly full of proposals about environmental barriers (deserts, mountains, and plains), glacial/interglacial cy-

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA pluvial lakes. These parameters are then interpreted in terms of movement corridors used to colonise America. The whole study is carried out under the general assumption that people would likely have taken easier rather than more strenuous routes when moving across the landscape. Ice sheets and mountain ranges were interpreted as geographic barriers, while shorelines, plains and river margins have been seen as favourable for dispersal. However, the results of this study were in some respect unsatisfactory:

cles, sea-crossing, land bridges and adaptive specializations, but lacks the means to evaluate their individual and combined impacts on hominid dispersal.” (Mithen & Reed 2002:433)

To overcome these constraints, Mithen and Reed develop a simulation that integrates both changing climatic conditions and sea level fluctuations into eleven different climatic zones that vary in accordance with their climatic conditions and environmental restrictions. The environmental restrictions refer to altitude barriers which limit the probability of colonisation, and a preference for coastal routes that exert a positive influence on rates of colonisation. Environmental conditions are represented in a grid of 7406 triangular cells covering the entire surface of the earth, where each cell covers approximately 45,000 km2. Up to six types of hominid populations, varying in their environmental and dietary preferences have been simulated. At each time-step the population of a given cell has several possibilities for actions on a probabilistic basis: they can change their characteristics in terms of ecological preference, colonise an adjacent cell, or become extinct. Dispersal itself has been incorporated into the model by means of the occupation of adjacent cells based on random selection without regard for the influence of prevailing environmental conditions. These environmental conditions become only essential during the next step in the simulation array, when they are responsible for the extinction probability (Mithen & Reed 2002:439). While these simulations take a wide variety of environmental parameters into account, its spatial resolution remains rather coarse. Further on, the general model uses a wide range of parameters, which often have to be assumed (ibid. 443).

“The resulting solutions…, however, are sometimes appreciably different than expected from traditional approaches emphasizing the importance of coastlines, river valleys, or lake margins; least-cost solutions can involve at least some overland (i.e., upslope) travel.” (Anderson & Gillam 2002:48)

Taking the difficulties of weighting the different environmental data, as well as the assumed starting and destination points of the spreading routes into account, these unexpected results can be explained by methodological problems. A too simplified approach has been chosen to model possible dispersal routes. The valuation of topography, ice sheets and lakes as determining factors cannot be verified. Nor do known archaeological sites represent valid destination points in a least-cost path analysis, because they do not necessarily correspond to the material remains of the founder generation. A more sophisticated study has been carried out recently by Field and Lahr (2005) using the least-cost path approach to assess potential dispersal routes for modern humans form East Africa to Australia during Oxygen Isotopic Stage 4 (OIS 4). A cost-of-passage map has been calculated on the basis of information about present mobile hunter-gatherer groups which were familiar with or subsisted on coastal resources. The map was based on the assumption that these groups show needs and behaviour comparable to the human groups dispersing out of Africa (Field & Lahr 2005:7). In addition to slope, which has been seen as the most important topographic variable influencing possible dispersal routes, barriers such as deserts, streams and coastlines were included in the cost-of-passage map. To overcome the deterministic character of the least-cost path approach, a ‘wandering’ method of route determination has been designed in which a 60 km search radius was placed around the starting point on the cost surface. Each route out of Africa consists of a culmination of 60 km path segments. Following each calculation within this distance, the search radius was moved to the newest endpoint. The next path segment of the route was then generated from that point onwards (Field & Lahr 2005:10). This procedure results in a least-cost path which is, according to the cost-of-passage map, closely bound to coastlines, while inland areas are widely ignored. While the emerging picture might correspond to some more general considerations concerning the human spread out of Africa, from a methodological point of view, this approach is questionable: input parameters have been chosen assuming the importance of coastal areas. The output of this model is mirrored in this assumption: the most important corridors

A last group of models that were applied in the study of human dispersal uses the least-cost approach to assess possible movement corridors. This approach uses cost-ofpassage or friction maps (Conolly & Lake 2006:215) to sum up costs of travelling from one point in space to another. A cost-path analysis calculates in a second step the least-cost path, which means the way between two given points which results in the least effort. This kind of analysis is based on the assumption that humans behave in the way of an economic man who seeks to attain a specific goal with the least possible cost. In contrast to all of the aforementioned models, to apply least-cost analyses, not only must the points of origin of a route be known, but the destination points must be assumed as well. Therefore, this approach is strictly deterministic in terms of the calculation of dispersal routes. Two different studies will be presented here to demonstrate assets and drawbacks of this method. Anderson and Gillam (2000) try to detect dispersal routes, dispersal rates and reasons for the initial population dispersal into the Americas during the end of the Pleistocene with respect to physiogeography, demography and artefact distribution. They carry out a GIS-based, least-cost analysis using continental scale elevation data together with information on the late glacial location of ice sheets and

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CHAPTER 2

1.3 EXPLANATORY CONCEPTS FOR THE DISPERSAL OF THE NEOLITHIC OVER THE ARABIAN PENINSULA

of the spread are coastal plains. This effect is strengthened due to the assumption that areas with minimal slope were preferred ways for dispersal. Because the study accounts for a lower sea level during OIS 4, continental shelf is accessible for the dispersal, an area that is predominantly flat. Thus, the study can be seen as a classical circular statement, one which is not qualified to assess possible routes of dispersal.

Evidence for the spread of the Neolithic over the Arabian Peninsula is based on the observation of the distribution of archaeological materials, including archaeozoological remains and cultural artefacts in both space and time. At a specific point in space, objects can be found which are related to similar objects found at other locations, but stemming from different points in time.

This section has provided an overview of existing models for the dispersal of human population groups. It has demonstrated the wide range of different approaches that have been followed during the last decades. The most elaborate studies use models adapted from the fields of bioecology and biogeography. The main advantage of these models is their ability to predict rather than explain archaeological evidence. Therefore, they can be tested against empirical data. Most of these models use partial differential equations to calculate spreading rates on the basis of demographic parameters, but there are substantial difficulties in incorporating the quality of geographic space within this framework. Additionally, these models assume a spread into adjacent regions only when the carrying capacity is reached. The latter might be a valid model for analysing population groups with only limited mobility. But to assess possible routes of dispersal for highly mobile herders in a diverse and marginal environment, this approach might be not valid. Therefore, a new model needs to be developed to account for the special characteristics of the dispersal of highly mobile population groups in marginal environments. In contrast, the application of agent-based models is currently restricted to ‘artificial world’ phenomena, meaning they provide a framework to answer general or more theoretical problems.

Two basic concepts can be used to explain this dislocation of objects: the first involves the physical displacement of people together with their material environment (migration, invasion), while the second relates to the spread of specific items due to communication and interaction (diffusion of an innovation). Both concepts have been used in archaeological research, but the idea of migration and invasion has found a much wider application.

MIGRATION For over a century between 1860 and 1960, mobility between regions has been seen as the main force for cultural change within a specific region. It was one of the paradigms in culture-history, that invasion and migration formed the basis of explanations (Chapman 1997:12). From the 1960s onwards, invasion and migration as explanatory concepts have been substantially criticised by followers of the “New Archaeology”, who emphasise the importance of internal social differentiation, population growth or environmental change, rather than ‘cultural diffusion’. It became obvious, that invasion and migration could not be applied as explanatory concepts. Rather, both invasion and migration must be explained by other independent factors.

The last approach that has been explored uses a common functionality within GIS to calculate least-cost paths between two given points on the basis of a cost-of-passage map. The main advantage of this approach is its explicit spatial character: it uses exclusively the characteristics of geographic space to calculate the optimal way between two points. But at the same time, this is its biggest drawback. This model is strictly deterministic: all variables influencing possible dispersal routes have to be included in the cost-of-passage map. In addition, both start and end points of a dispersal must be known, a requirement that archaeological data can hardly be expected to provide.

This claim has been partly fulfilled by sociologists and geographers who started to describe migration as the product of an interplay between ‘push’ factors, which are perceived negative conditions in the home region, and ‘pull’ factors, which are perceived positive conditions in the destination region (Lee 1966, Lewis 1982). During the last decades a tendency to revive the concept of migration and invasion can be observed among the agendas of archaeological research based on the use of complementary evidence from linguistics and history to support the proposition that migration can actually explain cultural phenomena (Chapman 1997:13).

Because of the drawbacks of the models to assess possible routes of dispersal currently used in archaeology, none of these approaches can be seen as suitable for the analysis of the dispersal of mobile herders over the Arabian Peninsula. Therefore, it is the main objective of this study to develop a new model for the assessment of dispersal routes of human groups dependent on the interplay between local environmental conditions and simple rules of human behaviour.

Concerning the Neolithisation of the Arabian Peninsula, one point in particular calls into question the conceptual framework of migration dependent on ‘push’ and ‘pull’ factors as a valid model for the dispersal of Levantine mobile herders. Pull factors, which have been identified as essential for migration, include a substantial flow of information:

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA The second requirement for spatial diffusion of ideas is communication, which is the process by which innovations are transmitted from a source to a receiver (ibid. 1971:23). It is mostly density-dependent: the more frequently communication occurs, the higher the probability of innovation acceptance. For prehistoric times, direct personal communication has to be assumed as the only possible communication channel. Therewith population density might have had an important influence on the diffusion of innovations: the higher the population density, the more frequent are personal communications.

“…it is quite clear that the probability that x will migrate to y at time t is partially determined by x’s level of knowledge about place y; this in turn is largely determined by the prior history of migration between x and y.” (Anthony 1997:23p.)

Therefore, it has been assumed that migration proceeds normally in directed streams toward known targets. Information about a limited number of attractive routes and destinations constitutes a necessary prerequisite (Anthony 1997:24). This is hardly the case for the Arabian Peninsula at the time the initial dispersal of Neolithic herders, when the distribution of ressources in Arabia can be considered as widely unknown for Levantine population groups.

Time is another factor that is considered in innovation diffusion research. It takes some time to pass innovations between individuals, and the acceptance of an innovation also needs time (ibid. 1971:24p.). By relating the time aspect of innovation diffusion with space it becomes clear that a substantial difference in time can be expected depending upon where an innovation appears. The last aspect of innovation diffusion which has to be considered is the social system in which the innovation disperses. While some forms of social organisation and population group size are beneficial for the adoption of innovations, others are not (Eisenhauer 1999:222, 229, Mithen 1996:217).

Within the framework of migration as the physical displacement of population groups, demic diffusion represents a special case of relocation. If the carrying capacity of a specific region is reached, the population ‘spreads’ into adjacent regions. As discussed above, the application of the demic diffusion model is restricted to populations with restricted mobility and low population growth. Although there is no reliable information available about the population dynamics of Neolithic mobile herders, it is highly suggestive that mobility is a dominant feature of a mobile herding strategy. Therefore, the demic diffusion model cannot be adopted for the Neolithisation of the Arabian Peninsula.

One major field of research is the investigation of the spatial dispersal of innovations. Parts of this research, fundamentally influenced by the ideas of the geographer Torsten Hägerstrand, has been applied in this work to develop a model for the dispersal of Neolithic mobile herders over the Arabian Peninsula. Two important points of the concept of innovation diffusion favour this framework for the analysis of the dispersal routes of Neolithic mobile herders. First, it obviates the nomination of push and pull factors. Second, it considers explicitly the spatial configuration of environmental conditions.

INNOVATION DIFFUSION A second explanatory concept for spatial displacement of ideas, concepts and material culture derives from the field of social science. The driving force behind dislocation is not seen in the physical movement of people, but in the transmission of goods and ideas within a social system, so that the spatial distribution of goods and innovations is a consequence of communication.

I am aware that some specific characteristics of the diffusion of innovations sensu Hägerstrand, such as the negation of the active movement of people, do not fit the proposed process of spatial dispersal of the Neolithic over the Arabian Peninsula, as I will demonstrate below. But other aspects of the conceptual framework of innovation diffusion, such as the consideration of the physical environment and distribution of populations, make it suitable for the development of a conceptual model for the dispersal of Neolithic mobile herders.

Within this approach, the characteristics of the innovation, communication channels, time and social system from which the innovation disperses comprise elements that need to be considered: “Crucial elements in the diffusion of new ideas are (1) the innovation (2) which is communicated through certain channels (3) over time (4) among the members of a social system.” (Rogers & Shoemakers 1971:18)

The innovation can be an idea, practice or object perceived as new by an individual. This new idea need not simply be new knowledge, it might already be known by an individual for some time. What makes it new is the decision to use it. This decision is affected by the degree to which this innovation is perceived as better than the idea it supersedes (relative advantage), the consistency of this new idea with existing values and past experiences (compatibility), its complexity, testability and observability (Rogers & Shoemaker 1971:18p.).

To demonstrate the benefits of the results of innovation diffusion research to the model for the dispersal of Neolithic mobile herders, first Torsten Hägerstrand’s ideas about “Innovation Diffusion as a Spatial Process” (1953) will be reviewed. Then I will transfer and modify several conceptual aspects of this work into a model for the spread of the Neolithic over the Arabian Peninsula.

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CHAPTER 2

1.4 INNOVATION DIFFUSION AS A SPATIAL PROCESS

relationship between private information flow and geographical distance (‘neighbourhood effect’): “On the average, the density of the contacts included in a single person’s private information field must decrease very rapidly with increasing distance.” (Hägerstrand 1967:235)

Torsten Hägerstrand was a Swedish geographer working at the University of Lund who published several articles and books about the spatial spread of innovations during the 1950s. The aim of these studies was to systematically analyse the distributional changes of cultural elements and their formalised description.

As a result, he drew the conclusion that the probability of a new adoption of an innovation is highest in the vicinity of an earlier one and decreases with increasing distance. He used these observations to construct a ‘mean information field’ (MIF), a 5 by 5 unit lattice of cells (representing 25 by 25 km), which indicates the probability of contacts within space. According to the abovementioned results, the probability of contact decreases towards the outer cells of this lattice and is assumed to be zero beyond a distance of 12 km to 18 km (Hägerstrand 1967:244).

Hägerstrand inductively developed a four-stage model in which he tried to systematise information about the spatiotemporal organisation of ‘innovation waves’ (Hägerstrand 1952). Using isarithmic maps of the diffusion of various innovations in Sweden, he constructed a series of crossprofiles that suggested certain repeating patterns in space. Hence he posited the possibility of a formal analysis, in contrast to mere case descriptions of innovation diffusion processes. One of these patterns is the radial dissemination of an innovation outward from its initial agglomeration. This process can be accompanied by the rise of secondary agglomerations (Hägerstrand 1967:134).

This mean information field has been applied for a number of simulations for the spatial dispersal of an innovation in a two-dimensional space (Model IIb, Hägerstrand 1967:253pp.). The starting point for the simulation runs was the actual spatial location of the original adopters of an innovation, as well as the spatial location of potential adopters. Then in each iteration of the model, every former adopter was allowed to contact one other person, adopter or non-adopter. To achieve this, the mean information field was placed over each existing adopter in turn, so that the adopter was located in the central cell. A random number was used to determine the cell of the mean information field in which the contact happens. The probability for a given cell of the mean information field decreases towards its periphery according to the abovementioned rules. Therefore, the probability that a potential adopter is selected in the direct neighbourhood of the original adopter is higher than for one located at a greater distance.

In his dissertation “Innovation Diffusion as a Spatial Process” (published 1953 in Swedish, republished 1967 in English with a postscript by A. Pred) he developed four stochastic models to describe the spatial innovation diffusion processes on a general level. To establish these models, Hägerstrand analysed the spatial distribution of several technical and social innovations in southern Sweden (Hägerstrand 1967:15), which originated outside of the area where they were studied. Hägerstrand was not interested in the initial appearance of an innovation, but on subsequent events: “How does the adaptation of an innovation become widespread…?” (Hägerstrand 1967:5)

Although his model predicts several empirically observable patterns (ibid. 256pp.), Hägerstrand further refined it to account for the personal resistance of innovation acceptance (Model IIIb, ibid. 268pp.) . The resulting spatial patterns of this procedure are similar to the ones obtained by model IIb, but model IIIb is preferred by Hägerstrand (ibid. 273p.) due to its concept of resistance which, for him, seems to better emulate the irregularities of reality.

To follow this question, Hägerstrand explored the possibilities of stochastic models in which he saw several advantages: “With the aid of heuristic models, attempts are made to simulate those aspects of social life with which we are concerned. While reality is comprised of an immeasurable number of interacting phenomena, “life” in the subsequent models can proceed only under just those conditions we wish to test.” (Hägerstrand 1967:135)

It was less the results of Hägerstrand’s dissertation, but rather his mode of operation and the application of stochastic models as a tool to investigate spatial distributions, that so remarkably influenced innovation diffusion research during the following decades:

A second advantage of such a procedure lies in the following: “Chance replaces that residue of factors which we are uninterested in or cannot take into account.” (Hägerstrand 1967:135)

“Hägerstrand’s (1952, 1953) papers have formed the basis of most geographical model building efforts over the last twenty years” (Haggett et al. 1977:233).

As a result of the analysis of the case studies, Hägerstrand (1967:163p.) isolated private information, in the form of face-to-face conversation, as the main variable responsible for the diffusion of innovations within a society. In a consecutive step, Hägerstrand investigated the spatial characteristics of private information and found a strong inverse

While models that could be converted into simulations have been used for the exploration of the spatial distribution of material innovations in sociology and social sciences from the 1930s onwards, two characteristics of Hägerstrand’s models are outstanding. First, he develops a

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA servations. Within the study area, these boundaries were predominantly given by environmental constraints:

descriptive and inductive model of the spatial stages of innovation diffusion. Second, on the basis of this inductive model, he generates a series of stochastic simulation models which are probabilistic rather than deterministic. In this sense, the spatial patterns they generate are not inevitably identical from one run to the next, nor are they precise reproductions of reality. Although this kind of stochastic simulation technique had been applied earlier in physics and natural sciences, Hägerstrand was the first social scientist to use them extensively and consequently opened a new field of research:

“Some of the long lakes seem to form absolutely deadending barriers” (Hägerstrand 1965a:57).

Deep forests and fens represented other environmental situations which had a remarkable influence on settlement patterns and communication networks (Hägerstrand 1965a:57). The consideration of these environmental limitations resulted in more realistic results of the simulation runs (ibid. 66).

“To be precise, the weightiest ramifications of the models ultimately derive from their combination of random and non-random elements. Many ingredients of individual human behaviour are causally so complex that their aggregate spatial expression is usually randomly determined within certain constraints (stochastically determined), even though the decisions behind this behaviour are not randomly motivated” (Pred 1967:307).

Hägerstrand’s formulations about the characteristics of innovation diffusion formed the basis for successive studies that focused either on the dissection of static distributions, the projection of future distributions or the analysis of the past genesis of distributions (cf. Pred 1967:310pp.). Other scholars became engaged in specific aspects of Hägerstrand’s methodology, such as the influence of barriers (Yuill 1965) and corridors (Levison et al. 1973) with regard to the stochastic model, or the possibility of assessing the goodness-of-fit of Hägerstrand’s models to reality (Cliff & Ord 1973). Finally one characteristic of Hägerstrand’s stochastic models, which has been widely criticised, should not be concealed: these models are – almost by definition – oversimplifications.

Two other beneficial aspects of model building became clearly visible in Hägerstrand’s work. First, the modelbuilding technique itself generates new knowledge, with a means for gaining insight through experimentation. Second, because the insight gained from a discovery of a combination of random and non-random elements is very likely to be heuristic, it can point to both further empirical research and critical analysis of problems relating to the particular real-world observation under consideration (Pred 1967:308).

To conclude this discussion of Hägerstrand’s work, it is worth summarising the main features of the spatial diffusion of innovations that he proposed: (1) There is no interest in the initial emergence of a specific innovation, but only on its subsequent spatial dispersal. (2) There exists a local (spatial) concentration of initial acceptance. (3) An innovation spreads radially from the initial centre of acceptance. (4) Innovation diffusion depends on the frequency of personal communication. Therefore, innovation acceptance decreases with increasing distance. (5) Spatial patterns in innovation acceptance show a relation to the spatial distribution of a population. It is more likely that an innovation will be accepted in the direct neighbourhood of previous innovation acceptance than at places far away. (6) The spatial distribution of populations and communication networks are influenced by the geographical configuration of space.

In Hägerstrand’s models of spatial innovation diffusion, the neighbourhood effect plays a crucial role in the dispersal of an innovation. The probability of the adoption of an innovation is highest in the vicinity of an earlier one and decreases with increasing distance (Hägerstrand 1965b, cited in Brown & Cox 1971:552, Brown & Cox 1971:552pp.). The way an innovation disperses is responsible for this effect, that is, through personal communication. This assumption of an inverse interdependence between spatial distance and innovation acceptance requires two other implicit assumptions: potential adopters are equally distributed in space; and the density of adopters in space is high enough for frequent communication. Examining actual population distributions in space, these requirements are barely fulfilled, a fact that inspired Hägerstrand himself to improve upon his original model. Significant differences exist in the spatial distribution of population groups (settlements) within geographic space, which in turn influence the frequency of communication. In addition, geographical features such as lakes or mountain ranges represent physical barriers to communication (Hägerstrand 1965a:57). Thus, the spatial configuration of environmental characteristics significantly influences the spatial diffusion of innovations.

1.5 INNOVATION DIFFUSION OR POPULATION MOVEMENTS? As demonstrated, there exist two basic concepts in the fields of archaeology, sociology and geography to explain the dislocation of material objects: either the physical displacement of people (migration, invasion), or the spread of specific items due to communication and social interaction (diffusion of an innovation).

In his later studies, Hägerstrand (1965a:56p.) includes barriers of communication and uneven population distribution into his original diffusion model. These additions resulted in spatial patterns that were more similar to empirical ob-

46

CHAPTER 2 persal of Levantine herders. Nevertheless, it is appropriate to investigate possible push factors that could have had affected the dispersal.

Although the concept of spatial diffusion of an innovation has been widely preferred as a general explanatory concept during the last decades in the social sciences, archaeological and palaeo-climatological evidence in Arabia argues against diffusion as a valid mechanism. The proof for the presence of people on the landmass of the Arabian Peninsula at the end of the Pleistocene and the beginning of the Holocene is – at least in comparison to the later Middle Holocene – remarkably sparse. As demonstrated above the frequency of communication is one of the most important factors influencing the spatial spread of an innovation. This sparse evidence constitutes a strong argument against innovation diffusion as the mechanism for the spread of the Neolithic. A second argument against it is that the diffusion of an innovation is more likely within a single social system (Rogers & Shoemaker 1971:28). Because it is not plausible and archaeologically unprovable that human populations in southern Arabia and Levantine Neolithic groups belonged to one cultural or social system, this postulation also fails.

Push forces inducing population movements can be differentiated into external and internal factors. External factors stimulating populations to disperse include the emergence of hostile human population groups or changing environmental conditions. Internal forces can be similarly differentiated into socially or naturally related ones: parts of a population might be forced to leave the original territory due to social rules; the extension of the territory may be induced by changing economic behaviour; or a growing population may be forced to extend its territory due to increasing resource strength. Köhler-Rollefson (1992:13p.) proposes an argument for the latter in conjunction with an increasing dependence of human population groups on caprine herding during the Levantine PPNB. The human population density of relatively dry areas at the eastern and southern fringes of the Levant would have expanded substantially due to the introduction of domesticates, causing an increase in the carrying capacity of this area. With this new subsistence base, human populations could also prosper. As a result, the caprine populations had to grow accordingly to sustain these populations originally dependent on crop cultivation and hunting. This feedback process inevitably results in a clash between the spatial demands of goat pasturage and crop cultivation. As a possible solution, Köhler-Rollefson suggests the development of a change in economic behaviour, through the initiation of a mobile herding economy accompanied by the exploitation of a wider territory.

In contrast, archaeological evidence supports that migration of Levantine population groups over Arabia was the mechanism by which the dispersal of the Neolithic took place. This evidence is based on two different aspects of human actions: the herding of animals and the production of stone tools. The fact that sheep, goat and cattle had to be brought into Arabia as domesticates allows for an implicit conclusion about the herders: they must have accompanied the animal herds. Because of the substantial amount of knowledge that the herding of animals requires, it is hardly plausible that this knowledge was transferred to the sparse populations of roving groups of late Pleistocene hunter-gatherers in Arabia. The second argument is based on finds of stone artefact in Saudi Arabia and Qatar. Assemblages closely resemble Levantine artefacts both in terms of technology and typology. Although similar stone tool types can result from imitation, this can hardly be assumed about stone technology, which relies upon close personal interaction (Tostevin 2007). Therefore, it is much more likely that both kinds of material remains belong to the same human population group to which both a mobile herding economy and stone technology were original. These were Levantine mobile herders who began exploring the steppic regions around the inner margins of the Fertile Crescent at the end of the Levantine PPNB. Extending this exploitation around the northern margins of Arabia in space, a displacement of human population groups took place over the Arabian Peninsula.

During the Levantine PPNB, remarkable changes in the settlement pattern can be observed. Many Middle and Late PPNB sites were abandoned in the last half of the 7th millennium BC. At this time, a shift is observed. The large agricultural villages in the Mediterranean zone and the Jordan valley, the previous settlement foci during the Early and Middle PPNB, move toward the more arid areas east of the Jordan valley (Kuijt & Goring-Morris 2002:404). While only a few Late PPNB settlements are known west of the Jordan rift, a substantial number of settlements established during the LPPNB have recently been found east of the Jordan valley. Although the causes for this shift are not conclusively known, the change has been tentatively related to deteriorating climatic conditions affecting agricultural yields, human overexploitation or both. These factors resulted in major changes in the settlement patterns and a variety of new subsistence strategies based on regional and local adaptations (Gopher & Gophna 1993:307, Weninger et al. 2006:103).Population movement due to climatic deterioration has been suggested since the 1970s as a possible explanation for the abandonment of settlements in the Levant. Gopher & Gophna (1993:304) propose that the corresponding populations moved to more northerly parts of the Levant where humidity was higher.

1.6 POSSIBLE CAUSES OF POPULATION MOVEMENT The proposal that the mechanism for the spread of the Neolithic over the Arabian Peninsula was an extension of range land into formerly unexplored areas obviates the possibility of looking for pull factors that promoted the dis-

47

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA Several scenarios can be developed from this assumption, ranging from an equal spatial distribution of resources to a spatially concentrated distribution. If resources are equally distributed in space, there is no necessity for a spatial concentration of human activities. Every need can be fulfilled everywhere. Such a scenario suggests an equal distribution of human activities in space associated with an even population density. In such a scenario, the dispersal of humans and their material culture in space follows the first of Hägerstrand’s postulations. It is only determined by distance from the initial centre, so that more distant regions will be reached after those in the vicinity of the original centre. The contrary can be assumed in areas where the essential resources are spatially concentrated. In this case, human activities have to be closely bound to these resources (cf. Binford 1980:7). Therefore, any dispersal must be spatially geared to these resources, and the population density should be highest in the direct vicinity of these resources. Examples of such a situation are localised occurrences of water sources in arid environments. For mobile populations these points in space are places where people met each other, for example, at watering holes. For sedentary population groups these points are closely bound to their economic activities, for example, at oases.

It follows that during the Levantine Middle and Late PPNB noticeable changes in subsistence strategies and settlement patterns occurred. These changes have been related to population growth and shifts in the subsistence strategies as possible internal factors, with climatic change as an external factor. All of these factors point to degradation of the environment, which could at least be bypassed through migration. Thus, a possible push factor for the dispersal of the Neolithic over Arabia is posited here. This idea can be exemplified by the spread of the Neolithic into Europe. During recent years, the idea of changing climatic conditions as the prime mover for the spread of the Neolithic has been enhanced by new palaeoclimatic research. Around 6200 cal BC, several polar, marine and terrestrial climate proxies indicate a short-term change from warm-humid to cold-dry, lasting about 200 years, and back again. This episode marks not only the transition from the aceramic to the ceramic Neolithic, but the emergence of the Neolithic in south-eastern Europe as well (Weninger et al. 2006:75). It has been argued that this climatic event forced the abandonment of Neolithic settlements in Cyprus and Anatolia, where water supply depended heavily on annual floods during spring. At the same time the foundation of numerous new settlements is documented in south-eastern Europe and western Asia, indicating a fast and purposeful spread of the Neolithic in this area that was induced by a single climatic event (Weninger et al. 2006:104).

In regions with a concentrated spatial distribution of resources, an interdependence between the location of resources and the spatial dispersal of populations must be assumed, with two factors playing a crucial role. First is the distance between the resources, as it is more likely that a dispersal first cover the spatially closest attractive area. Second is the strength of the attractiveness, as the more attractive (in quality and/or quantity) a resource, the higher the probability that it attracts a higher number of people, and consequently forces higher population density. Further on, it is more likely that a dispersal will cover areas with highly attractive resources than locations where resources are less attractive. In such a scenario, the consideration of the spatial configuration and quality of resources is an imperative for modelling the dispersal.

1.7 ENVIRONMENTAL CONDITIONS AND POPULATION DENSITY AS A PREREQUISITE FOR SPATIAL DISPERSALS The term ‘environmental conditions’, as used here, follows a holistic approach. It is defined as the overall appearance of nature in a given area, including the spatial configuration of physical geographic features such as climate, geology, topography, hydrology and soils, as well as the occurrence of plants and animals. ‘Favourable environmental conditions’ refers to circumstances which benefit human activities and satisfy human needs. Consequently, these areas are characterised by a high resource density where the overall carrying capacity is high. In contrast, ‘unfavourable environmental conditions’ refers to situations where nature does not support human activities, the carrying capacity is low, resources are sparsely distributed and (basic) needs can barely be satisfied.

The second way the configuration of space affects the spatial dispersal is the distribution of barriers, which can be either physical, psychological or both. Physical barriers include oceans, large streams, lakes and mountain ridges, all geographical features which cost much physical effort to cross. However, the nuances between physical barriers and the distribution of resources can sometimes be blurred. For example, while deserts represent areas with an extremely localised distribution of (water) resources, they also function as barriers due to their physical spatial extent. Psychological barriers might play a role similar to physical barriers, in that dispersal into specific areas might be discouraged by ‘social barriers’.

At first, the distribution of human population groups in space is a function of the attractiveness of a given area with respect to human activities. This attractiveness can be caused by the occurrence of a special material resource, or can find its basis in a special social or spiritual configuration. The latter will be widely neglected here, because, as it will be demonstrated below, in marginal environments human activities are bound closely to material resources.

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CHAPTER 2

1.8 FREEDOM OF HUMAN CHOICE VERSUS ENVIRONMENTAL DETERMINISM

Therefore, it is postulated here that human beings are more restricted and thereby further impacted by environmental conditions when the environment cannot fulfil their basic requirements. This can be demonstrated by means of a simplistic example. Imagine a man in the desert; he may be culturally free in his decision either to go left (where a spring is located beyond the next dune crest) or to go right (where there is nothing). Nevertheless, if he turns right, he will die and thereby disappear.

The spatial arrangement of resources and barriers plays a crucial role in determining human dispersals. The idea of an interdependence between environmental conditions and human behaviour or cultural changes is long-lasting in archaeology. It can be traced back to R. Pumpelly (1908) and V.G. Childe (1928) at the beginning of the 20th century, but has been successfully applied to a number of archaeological problems until today7. Followers of the ‘New Archaeology’ have extensively used environmental conditions as explanatory frameworks for human behaviour, where humans are seen as beholden to a determining environment. One of its most prominent representatives is L.R. Binford (2001), one of the earliest ‘New Archaeologists’. Other scholars take environmental influences on human behaviour into account, but place more emphasis on cultural factors (cf. Bender 1978, Hayden 1990).

With regard to the dispersal of the Neolithic over the Arabian Peninsula, environmental conditions should have had an important limiting influence on the freedom of human choice. Today, Arabia is part of the Old World dry belt, a region spanning from the coast of the Atlantic Ocean, across North Africa and Arabia, into Central Asia. This area, located within the subtropical climate belt, is characterised by extended and poor desert environments with a substantial water deficit. Here, transpiration exceeds precipitation by a considerable factor. This deficit of water exerts a negative influence on the vegetation that provides pasture for animals and food for humans. Because basic resources are thinly and irregularly distributed across space, there is a high interdependence between natural resources and human behaviour with special adaptations to this environment. One such behavioural adaptation is nomadism, an increase in mobility based on an economy of domesticated animals (cf. Salzman 2001:397).

Harsh critique on environmental determinism in general, in addition to other characteristics of the ‘New Archaeology’, came from a group of scholars centred around I. Hodder starting in the mid-1980s. The critics tried to formulate alternative conceptions of archaeological interpretation, ‘Post-Processual Archaeology’ – which, in its most polemic form, rejects any substantial environmental influence on human behaviour (Hodder 1985). Following the ‘PostProcessual’ perspective, humans should be considered as active beings who negotiate social rules and create and transform their own social structure. From this point of view, external influences are neglected, and social change is solely historically dependent (Hodder 1985:2). Although both positions are widely contradicting, several scholars who felt constrained by the ‘New Archaeology’ tried mediating between ‘New’ and ‘Post-Processual Archaeology’ (Eggert 1998:299). This appears unsurprising considering the fact that humans should be considered as both: natural and cultural beings.

But even during the phase of moister climatic conditions during the Early Holocene, the environment in Arabia could hardly be considered as rich – as palaeoclimatic proxies and archaeozoological remains document. Thus the freedom of human decisions must always be considered as restricted by environmental conditions. The action of human groups was bound to those regions of the Arabian Peninsula where the spatial configuration of environmental factors was favoured. Therefore, any investigation of the spread of the Neolithic over Arabia has to consider the distribution of natural resources and physical barriers. A second factor was the freedom of human decision – cultural choices made against the background of the environment.

Bringing both views together (and thinking positively about ‘New Archaeology’), I propose physical environmental conditions as the framework in which human beings culturally (inter-) act, while the environment forms the arena in which humans act. Such a view allows a differentiated perception of the physical environment. In regions with abundant and equally distributed resources, referred to as ‘rich’ or ‘favourable’ environments, humans are less restricted in their actions by environmental conditions. The stage on which they can (inter-) act is thus broad. In contrast, if resources are restricted or highly concentrated, ‘poor’ or ‘unfavourable’ environmental conditions force and restrict humans in their actions, with their stage becoming narrower.

1.9 DESCRIPTION OF THE PROPOSED MODEL In the following, a model for the dispersal of the Neolithic over the Arabian Peninsula will be described. This model integrates the different approaches from the fields of spatial innovation diffusion, ecology and archaeology. The model allows for the influence of local environmental conditions as a prerequisite for spatial dispersal, but also considers some aspects of human behavioural responses to these environmental conditions. First and foremost, it aims at an examination of possible routes of this dispersal. Therefore, population dynamics will be assessed only in a basic manner. This model will not allow to assess either the absolute time the dispersal needed, nor the number of peo-

7 For a synopsis of Near Eastern archaeology, see Wright Jr. (1993);

for a present case study, see Weiss (2000) and criticism by Coombes & Barber (2005) and Staubwasser & Weiss (2006).

49

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA food resources, with an increase in the average distance per residential move in areas where resources tend to be more spatially segregated (Kelly 1995:128).

ple involved in that process. Such research questions demand more sophisticated models with a high number of well established parameters, a requirement that cannot be fulfilled at the present stage of research.

As a second spatial variable, the foraging distance, meaning the area explored around a given camp site, is progressively expanded during the stay at one location. At the beginning, the immediate vicinity of a newly established base camp will be explored, but later on, the gathering distance increases until a threshold is reached when caloric return of daily foraging trips is lower than the caloric efforts (Kelly 1995:132pp.).

HUMAN BEHAVIOUR The dispersal of Neolithic mobile herders from the Levant over the Arabian Peninsula is a spatial phenomenon, so the main focus in the following consideration lies in the spatial behaviour of human groups. Two main factors influence human spatial behaviour and have to be assessed as responses to local environmental conditions: the frequency of displacement and its intensity, which translate into distance covered (Kelly 1995:120p.). Additional variables which should be assessed are population dynamics, the response to physical boundaries and the impact of social factors. A detailed estimation of these individual variables is not possible because of a lack of modern analogues. Therefore, I will present several general considerations about the spatial behaviour of human population groups in response to prevailing environmental conditions.

Another dependency can be observed between population density and environmental conditions: “The population density of hunter-gatherers is a reflection of the amount of resource yield given certain resource choices and levels of food consumption.” (Hassan 1981:7)

Following Hassan (1975:28), the population density of hunter-gatherer groups is a function of: (1) resource potentials; (2) food-extractive potentials; and, (3) consumption level. Assuming that resource potential is the sine qua non for the other factors, a clear interdependence between population density and environmental conditions exists.

A general dependence between human mobility patterns and environmental variables has been widely recognised for hunter-gatherer groups on a global scale (Binford 1980, Hayden 1981, Lightfoot 1983, Kelly 1995). In this respect, “… nomadism increases in relation to the increasing scarcity, limited diversity, and greater unpredictability of resources” (Hayden 1981:378). In arid areas, human mobility is restricted by the almost daily need for water. The location of water is seen as more critical than other foraging considerations in determining residential moves. Kelly (1995:122 Fig. 4-4) demonstrates a strong correlation between the number of residential moves of huntergatherer groups and the primary biomass as a measure of the gross abundance and distribution of food for population groups living in desert environments (Hill Pandaram, Ngadadjara, Hadza, ≠Kade, Kua, G/wi, Aranda and Ju/ ’hoansi). In environments with higher biomass – which results from the availability of water – Kelly documents substantially more residential moves per year. Thus, in moister areas where climatic conditions are more favourable, the tethering effect to water sources is weakened and residential mobility increases as a result.

The application of these trends in mobility and population dynamics established among hunter-gatherer groups to mobile herders might be vulnerable to criticism. Nevertheless, there exists some degree of legitimation for this. Firstly, weak corresponding data for present day or historic nomads point in a similar direction. Secondly, it can be assumed that Neolithic mobile herders with a dependence on alternative subsistence strategies (hunting and fishing) were much closer to hunter-gatherers in their general environmental dependence than present day nomads that depend predominantly on marked exchange and agriculture (Khazanov 1984:82p.). Data about mobility and demographic patterns among present and historic nomads relative to environmental conditions are scarce. Khazanov (1984:71) stresses the fact that there is a positive correlation between the numbers of nomads and fodder resources they have at their disposal (in a given area) due to a reliance of livestock on grazing:

“Where water sources are localized in deserts, we could expect foraging efficiency to be sacrificed in favour of remaining close to a water source.” (Kelly 1995:126p.)

“Without grass there is no livestock, without livestock no food.” (Mongol proverb cited foll. Khazanov 1984:71)

While this can be considered as a general trend, it is much more difficult to establish explicitly a similar correlation between environmental resources and mobility patterns for pastoral migrations. The driving force behind pastoral migration is the need for suitable pasture for the livestock (Khazanov 1984:37p.). Inter-seasonal cyclic migration between pastures is determined mainly by natural and climatic conditions which dictate which pastures can be utilised at specific times of the year. In contrast, in-season migration depends more on the size of the given herd, than on the food and water it demands. Accordingly, when comparing

It follows that, on the one hand, increased mobility can only be achieved if the distribution of water sources allows greater movement. On the other hand, population groups have to respond with a spatial redistribution in relation to locally available resources when environmental conditions fluctuate (Lightfoot 1983:191). Therewith, increased (residential) mobility is also a response to hostile environmental conditions if resource availability allows for this. It is further suggested that the average distance between residential locations is closely related to the distribution of

50

CHAPTER 2 in a specific area with favourable environmental conditions and thus a high carrying capacity, the number of descendants is increased, the population grows, and thus, the population density increases. At the same time, the maximum spreading width is lowered: there is no need to invest in the spatial exploitation of a broader area. In contrast, when an area with unfavourable conditions and a reduced carrying capacity becomes populated, the number of descendants is reduced leading to a reduction in population density. In addition, the maximum spreading width is increased because it is assumed that a wider area has to be explored.

present nomads and hunter-gatherers, similar overall patterns of migration distance and frequency can be assumed, with longer and more frequent movements in marginal environments where natural resources are more sparsely distributed – as long as the distance between resources is within the range of the maximum migration distance. As a consequence, three mobility trends and one population density trend can be derived with respect to environmental conditions: (1) Unfavourable conditions with sparse resources lead to more frequent moves if the spatial distribution of water sources allows for this. (2) An uneven spatial distribution of resources in a generally unfavourable environment increases the average distance of moves. (3) The duration of stays in a given area decreases the resource availability and thus forces an extension of the area under exploitation. (4) The population density is lowered in unfavourable environments.

Nevertheless, both variables cannot be reduced to a single one if one regards the spread of the mobile herding economy as a spatial process. The maximum dispersal distance is only a theoretical value. When following the idea that it is much more likely for a dispersal to occur close to the already populated area, an uneven distribution of descendants closer to the former centre and a consequently uneven distribution of population density have to be considered. This model can be improved by incorporating increased mobility with respect to the duration of a stay in a given area. As demonstrated above, this process is driven by the degradation of local environmental conditions. Human response to the reduction of the carrying capacity through time can be considered as already described. The more that environmental conditions degrade, the wider the maximum spreading width becomes. In addition the number of descendants is lowered, so that the population density at a given place is further reduced.

To simplify these trends in human behaviour for an investigation of possible dispersal routes of Neolithic herders in marginal environments, they have been reduced to the following two variables (1) population growth and (2) dispersal distance. In this context, population growth does not point to an actual number of descendants in terms of people. Rather, it represents an abstraction which will account for the trend in both population density and frequency of moves, and thus the mobility. The same is the case for the maximum spreading width. This variable will represent the general trend that the distance of movements depends on environmental conditions rather than the actual mobility of single humans or single human groups. There exists a simple interdependence between population growth and the maximum dispersal distance in relation to the population density. The latter can be modified through either the spreading width (that is, a change in the area covered) or though an adjustment of the number of descendants (that is, the direct change in the density of a given area). The relationship is quadratic, so that achieving the same population density requires the number of descendants to be squared when increasing the dispersal width (Table 2). Maximum Dispersal Width

Area Covered

1

3.14

2 3

Population Density

Constant population Density

In this model, physical boundaries will be depicted in the following way. Physical boundaries are geographic features that can be crossed only with substantial effort. Therefore, they act in the same way as unfavourable environments in the model by forcing a fast crossing. This translates into a high maximum spreading width and a reduction in the number of descendants. Exceptions are represented by areas where natural conditions are assumed as too poor (i.e. having too low of a carrying capacity or too ‘high’ physical boundaries) to permit human habitation. These areas do not allow for any consecutive dispersals. The model further assumes the existence of an initial area, or centre of origin in space and time, from which dispersal started. Based on the archaeological evidence, this assumed area is located in the southern part of the Levant (see chapter 1). Conceptually following the spatial innovation diffusion approach, the dispersal started within this centre and continued to the adjacent spatial periphery.

Number of Entities

0.318

0.318

1

12.57

0.08

0.318

4

28.27

0.035

0.318

9

4

50.27

0.02

0.318

16

5

78.54

0.012

0.318

25

ENVIRONMENTAL CONDITIONS

Table 2: Relationship between dispersal width, area covered and population density.

The dispersal of the Neolithic over the Arabian Peninsula has to be understood as dependent on the local environmental conditions that form the background of this process. The abundance of natural resources determines the

Both population growth and spreading width will be chosen in regard to the following model assumptions. Arriving

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA (5) Local environmental conditions affect human spatial behaviour. Unfavourable environmental conditions promote fast movement and low population density, while favourable environmental conditions support a higher population density and slower movements.

population density in a given area. Favourable environmental conditions support a higher population density, and it takes comparatively longer to degrade it. Therefore, areas with a high resource density and environmental characteristics that are suitable for human habitation are more likely to have been affected by the process of the dispersal of the Neolithic than areas within marginal environmental settings.

By definition, this model oversimplifies the actual processes relevant to the emergence of Neolithic mobile herders in Arabia. But this weakness is also its strength. It is possible to convert the rules on which the proposed model depends into spatially explicit simulations. With the help of these simulations, possible dispersal routes can be computed and compared to the archaeological evidence. If the independent archaeological evidence supports the outcome of the simulations, it would provide strong feedback on the proposed model and indicate that the dispersal of the Neolithic over the Arabian Peninsula has to be considered as an environmentally dependent process.

The latter assumption presupposes that a specific region can be reached by population groups. The easier the given area with favourable conditions can be accessed, the more likely its utilisation by human groups and the more intensive its participation in supra-regional interaction. For the model it is assumed that areas with favourable environmental conditions which are not dissected by insurmountable areas of unfavourable conditions represent the most likely routes for the dispersal of Neolithic mobile herders. Consequently, two characteristics of environmental conditions have to be assessed for their influence on the dispersal of mobile herders. With the first variable, the favourability of a given area is responsible for the general possibility of human habitation. The more resources that are available, the longer a possible stay will be. Therefore, on the one hand, favourable environmental conditions will slow the spatial dispersal process due to reduced mobility. On the other hand, it will increase the population density, which will have a positive influence on the probability of a further dispersal. Through time, local environmental conditions will degrade, forcing a change in the spatial behaviour. While the population density decreases, the possible movement radius will increase (see section on ‘Human behaviour’ above). The second variable is the distribution of favourable areas in space. For an optimal integration of favourable areas into the process of dispersal, they should be spatially connected and not separated by natural barriers. Therefore a model for the dispersal of Neolithic herders over the Arabian Peninsula has to consider both human actions and local environmental conditions. The dependencies are mutual: not only do environmental conditions influence human behaviour, but human actions alter the environment as well.

2 TRANSFORMING THE MODEL INTO A SIMULATION To examine possible dispersal routes of the Neolithic over the Arabian Peninsula, the proposed conceptual model has been transformed into a computer simulation. Each run of this simulation will result in data sets that represent the parameters of the original model. If the parameters chosen for the model are representative of the process, it can be concluded that the simulation output at least partially resembles the original process.

2.1 WHAT ARE SIMULATIONS? The development of a computer simulation generally includes the following steps (cf. Young 2002:138p.): (1) generation of a simplified mathematical representation of the system under study (2) implementation of the representation in a computer programming language (3) running the computer program for a range of parameter settings and using graphics to display the observable system (4) comparing the results of the simulations with empirical data from the system under study (5) changing the simulation parameters and iterating steps 1-4 until an agreement between simulation and empirical data is obtained. If the empirical data satisfactorily agree with the simulation output, the chosen model has ‘solved’ some of the problems of the system under study. It is important to note that such an agreement does not confirm that the model and simulation are correct, but serves as a minimal condition for a successful explanation, which can be used as a starting point for further research:

The proposed model for an investigation of possible dispersal routes of Neolithic herders from the Levant is based on the following general rules: (1) The dispersal of the Neolithic herding economy started in an explicit initial area. Based on archaeological evidence, this area is assumed to be located in the southern part of the Levant during the Late PPNB. (2) The dispersal starts within this centre and continues to the adjacent spatial periphery. (3) The possibility of the occurrence of Neolithic mobile herders is highest in the direct neighbourhood of precedent Neolithisation. It is more likely that ‘roaming herding groups’ are populating nearby places than places far away. (4) Environmental conditions deteriorate in a given area with respect to the presence of human populations.

“The objective [of a simulation] is not to offer final explanations but to stimulate further study and debate.” (Young 2002:139)

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CHAPTER 2 These platforms offer the languages in which the specific simulation must be coded. Normally imperative languages will be used for this kind of coding, where

In the social sciences the prevailing view about simulations stands in harsh contrast to the understanding of simulation in physics or engineering, where it is expected that the results of a simulation will be directly usable to predict new hypotheses. These distinctions can be ascribed to differences in the level of understanding of basic processes and principles (Aldenderfer 1981:18). There are far fewer competing paradigms in physics than in the social sciences, where basic principles are more poorly understood. The social sciences merely seek to answer the question of whether underlying quantifiable principles in human behaviour exist. Simulation models become necessary when mathematical models do not deliver exact solutions. When an exact solution exists, the dynamics of the system under study can be explored without simulations, but this rarely occurs in real-world systems. If simulations are necessary, a computer can help to calculate the dynamics of the system from some given initial conditions (Rossiter 2003/ 4:8). At present, two different approaches prevail in computer simulations, the continuum model and the particle approach. The continuum model introduces partial differential equations for the space-time evolution. While the main advantage of these models is their ability to represent large populations over large space-time regions, they do not treat very low population densities accurately. In contrast, the particle approach (agent based models) allows for a detailed assessment of individuals. It is useful in the study of how human migration behaviour at the individual level leads to observable collective patterns. Parameters such as motion rules and growing rates can be directly assigned to these individuals. The simulation program then allows the population distribution to evolve in space and time. Very often, the motion itself is controlled by a probability function.

“…the language defines both what needs doing and exactly how it should be done in terms of low level programming concepts such as loops and variable assignments.” (Rossiter 2003/4:15)

The fact that the dispersal of people or ideas has an inherently strong spatial component suggests the choice of a Geographic Information System (GIS) as the simulation platform for such a research agenda. GIS was developed to manipulate, integrate, and visualise spatial data. The basic tasks of GIS can be described with the following five functions: (1) data acquisition, (2) spatial data management, (3) database management, (4) data visualisation, and (5) spatial analysis (Conolly & Lake 2006:5). Thus, simulation is not the generic field for GIS: spatial models produced in GIS are normally static. Nevertheless, with both the general structure of how data are handled and the existence of a random number generator, as well as the possibility for coding, GIS provides essential functionalities for spatial simulations. In addition, the analysis and processing of input and output data occurs using the same software, thus minimising the danger of information loss resulting from data conversion between different systems. On a general level, GIS stores data in two-dimensional data layers which are determined in their absolute and relative spatial location, i.e., they are geo-referenced. Attributive information is assigned to this spatial information, therewith “…GIS describe[s] the world in terms of attributes and locations” (Conolly & Lake 2006:4). Two different principal data models have been used in GIS to link attributes and locations, either the raster or the vector data format.

With every computer simulation the running of computer code can be viewed as a ‘virtual experiment’, an experiment on the virtual representation of a system (Rossiter 2003/4:8p.). A simulation generates empirical data of its own which can be further analysed inductively. In contrast to real-world data from measurements, data resulting from virtual experiments arise from a computationally defined set of rules. First and foremost, simulation results are only valid in the context of their own simulation model. The virtual data should only be used to understand and explain how the conceptual model the simulation is based on produced such a result. Therefore, simulations should only be applied if it is not immediately clear what the simulation results might be.

The raster data model proposes a smooth and continuous space over which some attributes vary. Every location has a single attribute value with respect to the spatial resolution of a raster grid. The lower the resolution of the raster, the bigger the area represented by a single value. Therefore, a specific raster can only be applied at a specific spatial scale. A concrete example of a raster data set that provides a discrete approximation of a continuous field is a digital elevation model (DEM), where the height above sea level is given for a set of raster cells arranged in a regular grid. Since the raster data model handles information through a set of predetermined locations in space, it can be considered to fit closely with the philosophical absolute concept of space. Thus, places close to one another tend to have similar characteristics (Tobler 1970:236).

2.2 GEOGRAPHIC INFORMATION SYSTEMS AS SIMULATION ENVIRONMENTS In its most comprehensive form, a computer aided simulation consists of the simulation ‘engine’, a data source and appropriate tools for the analysis of input and output data. Because most computer simulations have some features in common, various simulation platforms have been developed which provide the basic software infrastructure.

The alternative vector data model, also known as the entity data model, proposes a set of distinct entities (points, lines and polygons) which have a location and which are associated with attributes. In contrast to the raster data model, the vector model is normally associated with data that are not

53

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA cells in the raster map. The algorithm begins at the starting point and successively sums up the costs of reaching neighbouring raster cells. It cumulatively models the cost of reaching any point in the landscape from the starting point. It should become clear that the conceptual model postulates that every area is accessible. Only the amount of time or energy invested differs. There are several possible workarounds, such as representing barriers as areas having very high friction values, but these do not alter the concept. Conolly and Lake (2006:152) explicitly state that the cost surface algorithms do not inherently model movement or dispersion, but instead model time or energy to move from one starting point to other locations.

continuous in space, such as the location and extent of cities or archaeological sites (Conolly & Lake 2006:5). The vector data model allows for the possibility that a substantial number of spatial locations have no attribute values, and spatial information is organised in discrete entities. In the simulation of the dispersal routes of Neolithic mobile herders, the characteristics of these two data models with the two concepts of space and its representation can be incorporated. The raster model is used to represent a natural or social environment, while the vector data model is used to represent entities such as groups or individuals, acting on this environmental layer.

2.3 DETERMINISTIC VERSUS STOCHASTIC SPATIALLY EXPLICIT MODELS FOR THE SIMULATION OF DISPERSAL

Least-cost analyses require at least three layers of input data: the point of origin, the destination point or points, and the cost-of-passage map. This condition can be met when both departure and destination points are known, for example when predicting raw material procurement routes (Barge & Chataigner 2003) or replicating known pathways (Bell & Lock 2000). Additionally, the least-cost path model presupposes knowledge of the whole landscape with regard to movement constraints. This is necessary due to the application of the accumulated cost surface algorithm that sums up the costs from the starting point across the entire surface.

Two basic conceptual models for the exploration of dispersal within a landscape can be distinguished: deterministic and stochastic models. While the deterministic model is common in geography and archaeology for considering accessibility and paths of movement, stochastic models are predominantly used in ecology. Deterministic models have been applied to analyse the accessibility of different locations within a landscape and the potential for traversing it. Accessibility can be expressed as a function of distance or time (Higgs et al. 1967), or energetic expenditure (Foley 1977). Its classic application in archaeology is the site catchment analysis.

In contrast to these justifiable applications of deterministic models with known origin and end points, dispersal refers to the spreading of species into formerly unoccupied areas in ecological terms. Here, the quality of space with regard to the overall costs between the point of dispersal origin and destination point(s) are not known. This makes the application of the least-cost path analysis inappropriate for an assessment of dispersal routes. In addition, the least-cost path analysis requires explicit destination points, ones which can hardly exist when the dispersal into unoccupied areas initiates. Nevertheless, two different workarounds have been applied in studies during the last years: the selection of archaeological sites as potential destination points (Anderson & Gillam 2000), and the calculation of dispersal routes through least-cost path analysis in spatially discrete segments of the whole route (Field & Lahr 2005). As already discussed in the section 1.2. of this chapter, the least-cost path analysis produced partial results which did not correspond to the expected paths of migration in both studies. These results can be seen as the consequence of applying an inappropriate method.

With GIS, accessibility can be easily analysed using accumulated cost surfaces that represent the cost of moving from a specific point in space to all other areas under consideration. These moving costs are accumulated by a function that sums up the values of a ‘cost-of-passage’ or ‘friction’ map and represent the potentials and constraints of movement through a landscape. In principal, it is possible to employ costs that represent environmental constraints and cultural influences, such as attraction or repulsion from significant places. Cost-of-passage maps express the costs of traversing each individual spatial location and, thus, entirely determine the results of the analysis. Because these costs are assumed to be spatially continuous, the cost-of-passage maps are commonly generated as raster maps. Usually these cost-of-passage maps have been created from topography (slope, topographic roughness) and land-cover, both of which predominantly determine the cost of walking across a landscape. To transfer these attributes in travelling time or energy expenditure, empirical data have been used to establish formulas for corresponding calculations (van Leusen 1999, Wheatley & Gillings 2002:154pp., Conolly & Lake 2006:215pp.). From these cost-of-passage maps, the accumulated cost surfaces are calculated by applying a spreading algorithm designed to minimise the accumulated moving costs from a specific starting point to the other

The contrasting stochastic conceptual model is predominantly applied in ecology to simulate population movements. This model assumes that patterns of population dispersal can be deduced from the statistical properties of the population as a whole. The philosophy underlying the application of the stochastic model is that the general patterns of dispersal do not depend on the intricate details of how individual organisms move, even if it is known that single individuals show complex behaviour relying on environmental cues (Steele et al. 1998:302, Andow et al.

54

CHAPTER 2

2.4 THE SIGNIFICANCE OF GEOGRAPHIC SPACE IN DISPERSAL SIMULATIONS

1990:178). Instead of considering the detailed behaviour of individual movement, the stochastic model employs a random dispersal to replace this variable on the population scale. The application of such a simple random dispersal pattern to describe the movement of populations can be criticised as ‘simplistic’. However, it compares simulations of animal dispersals on a population level with realworld observations and demonstrates the potential applications of this model in ecology (Andow et al. 1990). With GIS, simple random movements in two-dimensional space can be simulated through the generation of random x and y coordinates within a given area. The random point emerges by the combination of these two coordinates (Jenness 2005:16), while the linear connection of consecutively calculated, random points results in a random movement.

Human migration behaviour depends on both the Euclidian distance and the potentials and constraints of geographic space. Therefore, any simulation of human dispersal should consider local environmental conditions. Nevertheless, almost all dispersal simulations in archaeology ignore the significance of geographic space. In its original form the popular ‘Wave of Advance’ model neglects any heterogeneity of the environment or the existence of boundaries such as coastlines (Ammermann & Cavalli-Sforza 1973). Thus, the classical ‘Wave of Advance’ underplays the influence of the quality of space on human dispersal. Even in subsequent research this limitation has been only partially challenged. The general problem of a uniform dispersal surface often remained:

During the last two decades, increasingly complex derivations of the random walk model have been developed to describe animal movement and dispersal. These models, known as correlated random walk models, depend on the three following parameters: number of steps, step size and distribution or random turning angles. In contrast to pure random walks, the previous direction of movement influences the direction of the next step, making a backward movement less likely (Byers 2001).

“It is reasonable to expect that the global dispersal of modern humans was influenced by habitat variation in space and time; but many simple simulation models average such variation into a single, homogenous surface across which the dispersal process is modelled.” (Steele et al. 1998:286)

This problem might be at least partly caused by restrictions in the application of differential equations with regard to spatially explicit phenomena, such as the process link between environmental data in its spatial representation and the numerical solution for the Fisher-Skellam equation. This limitation has been partly challenged through the application of additional terms allowing for spatial explicitness.

Compared to the accumulated cost surface and least-cost path analysis, random movement simulations have the advantage of incorporating a random component that neglects the details of individual behaviour. This variable makes this concept superior to the deterministic models that explicitly assume that all parameters determining spatial dislocation are included in the friction surface. This requirement can scarcely be fulfilled in archaeology, because most parameters are poorly known on both the individual and population level. Stochastic models in principle allow for individual behaviour on the conceptual level, but ‘replace’ it with the random component. This generalisation from the individual to the population level allows for a better understanding of the complete process under consideration:

Although the importance of the diversity of geographic space for human dispersal has long been recognised, its explicit implementation in formal model-based simulations has been achieved only in restricted cases. Four case studies will be presented to demonstrate how the characteristics of space have been considered in simulations of human dispersal. In these, a clear trend towards incorporating a greater number of factors influencing human dispersal and a higher spatial resolution exists.

“If these simple [stochastic] models can explain and describe observed population-level patterns while neglecting the detail of individual behaviour, then the fact that organisms violate some of the theory’s assumptions is irrelevant at the macroscopic level of description. Indeed, the philosophy behind the use of these models is that they allow us to focus on the key processes underlying patterns, and to ignore noise.” (Andow et al. 1990:178)

Case study 1 In their 1984 monograph, Ammermann and Cavalli-Sforza present their simulations of the spread of farming from the Levant into Europe. They use a regular square grid with a grid cell size of 150 by 150 km (22,500 km2) for their analysis of the Fisher-Skellam differential equation solutions allowing for interaction between farmers and hunter-gatherers. For the representation of geographic space between the Levant and Northern Europe, they arrange 816 grid cells in a rectangular lattice of 34 columns and 24 rows. The only geographic features considered in the model are marine areas that are left unoccupied during the simulations (Ammermann & Cavalli-Sforza 1984:119).

For its application to archaeology, the ‘noise’, which is replaced by the random component during the simulation process, has two different origins. First and foremost is the unknown of individual behaviour. But second comes that which can be subsumed under the term ‘critical assessment of sources’: only a small part of the past is accessible in the present (cf. Eggert 2001:100).

Case study 2 Applying a modified variant of the Fisher-Skellam equation, Steele et al. (1996:224, 1998:289) use the raster data

55

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA model with a grid cell size of 50 by 50 km (250 km2) for the representation of the human carrying capacity in North and Central America. With this model, not only is the spatial resolution of the simulation much higher, but an additional factor is integrated: the physical boundaries of the American continent and the carrying capacity.

gregation and abstraction, artificial entities interact with discrete and spatially explicit local environmental conditions. Such an approach allows for a dichotomy to be maintained between a data set containing environmental information and a formal representation of individuals that interact with these environmental conditions on a local scale. As a consequence it becomes possible to generate a complex ‘environment’ independent of the actual simulations, allowing multiple environmental factors to be considered. Thus, the diversity of space can be represented in a more sophisticated manner than with the classical differential equation approach that allows only a specified and restricted number of factors.

Case study 3 A different simulation design has been used by Mithen and Reed to simulate early hominid dispersal out of Africa. They establish a grid of 7,406 triangular cells each with a size of 45,000 km2, arranged into 14 hexagons and seven pentagons, that cover the entire globe except for the Americas (Mithen & Reed 2002:436). Although they apply a low spatial resolution in comparison to other simulations, the number of grid cells is comparatively high and they consider a larger part of the earth surface. In contrast to other simulations, grid cell values do not only alter the results of the dispersal, as occurred in the differential equation model investigated by Steele et al., but the grid cells spatially represent a set of different parameters, including the presence of hominids, colonisation probability, environmental conditions and environmental barriers as defined by altitude. The simulation design is based on the principle of cellular automata (ibid.437) and differs remarkably from other dispersal simulations.

2.5 SIMULATION DESIGN One focus of this study is to develop a conceptual model for the dispersal of the Neolithic over the Arabian Peninsula, which can be transferred into a simulation. This simulation should be capable of producing empirical data that can be further explored for an inductive analysis of possible dispersal routes. Thus, the simulation has to be considered as a tool which provides the basis for advanced examinations. Because the informal conceptual model for the dispersal of the Neolithic over the Arabian Peninsula proposes a process of human-environment interaction, an individual-based simulation design has been chosen to explicitly allow for the simulation of such interactions.

Case study 4 In contrast to the above mentioned simulations, Davison et al. (2006) do not use a grid with a constant metrical cell size to simulate the dispersal of agriculture into Europe. Instead, they base their model on the graticule, dividing the earth’s surface through parallels and meridians. They consider deviations in the dispersal rates inferred from planar projected models where they involve global length scales in the simulations (ibid. 644). Applying a grid with a resolution of 1/12°, they achieve a resulting metrical resolution of 9.27 km along the meridian, and between 2.4 and 8.4 km along the parallel with respect to geographic position (ibid. 646). The grid cell size ranges from about 22 km2 to 78 km2. Applying a differential equation related to the Fisher-Skellam model Davison et al. employ grid diffusivity and carrying capacity to calculate an increase in diffusion velocity along river valleys and sea coasts and a decrease in the carrying capacity at higher altitudes (ibid. 647). Thus, they improve the original differential equation and add an additional variable.

The simulation design is based on two different elements: ‘individuals’ represent local communities and a virtual spreading surface represents environmental potentials and constraints to dispersal. Both elements of the simulation interact in a circular array, producing one new data set for every execution of the array, which in turn is used for further analyses. The spreading surfaces are generated from a variety of actual data sets representing environmental conditions on the Arabian Peninsula. Both the data sets and their processing will be described in the following chapter. The general simulation design and simulation results in artificial, i.e. constructed environments will be presented in the following to demonstrate the strengh of this approach. The conceptual model underlying the simulation focuses on three main characteristics of the dispersal of the Neolithic over the Arabian Peninsula: the initial location of the dispersal (point of departure), dispersal distance and the number of descendants with respect to local environmental conditions. Applying an individual-based approach, this informal model is transferred into a simulation in a GIS environment in the following way.

These recent investigations clearly demonstrate attempts to include the constraints of geographic space in human dispersal simulations. At the same time, they make some limitations of the numerical approach obvious: the equations become complex and unmanageable when spatially explicit variables are introduced.

The simulation is based on the interaction of a point shapefile, representing randomly wandering groups, and a raster data file, representing local environmental conditions that force the movement of human groups. A shapefile is a digital vector format specific to GIS that stores geometric lo-

For this reason, another approach to consider the heterogeneity of space in a spatially explicit model is suggested here. This approach can best be described as an individualbased (particle approach) simulation. With a level of ag-

56

CHAPTER 2 the higher the spreading distance in accordance with assumed higher pressure for migration. The actual spreading distance of the consecutive point(s) is determined by a random algorithm that determines the spatial location of the consecutive point(s) within the radius of the maximum spreading distance. Because the simulation should allow for a higher probability that consecutive points are located close to their initial points, a numerical transformation on the random coordinates has been applied; and (3) The simulation allows for a dynamic change of the raster surface by considering a degradation of local environmental conditions caused by the presence of human population groups. Every point in each generation can decrease the underlying raster value at the specific location. The behaviour of the point during consecutive executions of the array follows the rules mentioned above. This means that the number of descendants and the spreading distance change through the simulations. If the grid value drops below a user-defined threshold, the point will stop producing descendants in the following generations due to the degradation of the local conditions until the threshold of survivability has been reached.

cation and associated attribute information. The model was implemented using the programming language Avenue in an ArcView 3.x GIS environment. The reasons for using Avenue instead of another programming language applicable in other GIS environments are the easy integration of GIS-specific processes and the possibility to quickly test and modify any of the parameters. Implementing this model in an ArcView 3.x environment also allows for a subsequent analysis of the distributions of the modelled points without any further import/export procedures. Disadvantages are the somewhat slow performance on big datasets and a limitation to about 32,500 interactions between a vector shapefile and an underlying grid dataset. However, this problem can be overcome by splitting the calculations into several steps. The implementation of the model in ArcView 3.x is schematically shown in Figure 8. It starts with an initial point (or several initial points) stored in a point shapefile. There is a repeating dynamic interaction between the point and the underlying raster dataset that represents the local conditions: (1) The number of descendants of each starting and consecutive point in each generation depends on the value of the underlying raster at this specific location. The higher the raster value, that is, the better the local conditions are, the greater the number of descendants in the next generation. If the raster value is below a threshold, no consecutive points will be generated; (2) The maximum spreading distance defining how far a new generation will go is determined with respect to the underlying raster surface. As with the number of descendants, there exists a comparable coherence, but in inverse proportion. The lower the raster value at a specific point,

Every simulation run depends on several simulation parameters, with some of them provided by the user, while others are calculated automatically by the program (Table 3). In the first step, the user identifies the point shapefile that defines the initial points of the dispersal simulation and the grid file that stores the information of the virtual spreading surface. The user specifies the number of generations, so that the simulation understands how many iterations to perform. A new point shapefile is then created to store the geometric information for every generated point during the dispersal simulation. Additionally, the attribute

Fig. 7: Implementation of the conceptual dispersal model into a GIS environment.

57

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA table for each generated point is permanently updated with the following information: a unique identification, the value of the underlying raster file, the first generation number in which the point was created, the last generation number (the number of the generation in which the point disappeared) and finally, the identification of the “parent” point. These values allow for an interpretation of the results afterwards.

code that both the number of generated points and the maximum spreading width are conditionally determined by the values of the spreading surface. In the example above, only three values of the spreading surface are considered: below 40, between 40 and 80, and above 80. But this procedure can be extended up to 101 conditional terms relative to the values of the spreading surface, which must be reclassified for the simulation into values between 0 and 100.

Additional simulation parameters to be determined include the number of consecutive points and the maximum spreading width. Both parameters are calculated with respect to the underlying grid surface value and the grid value threshold, which is an absolute barrier. An initial or generated point falling in a grid cell whose value is below the threshold will not generate consecutive points.

Moreover, a defined spacing between newly generated points within one generation can be determined. The spacing controls the clustering of the consecutive points around the initial point. This parameter also affects the spatial alignment of the randomly generated points.

Simulation Parameter Initial distribution of starting points

User input necessary yes

The last user-defined parameter allows for an exploitation and degradation of local environmental conditions. When this parameter is set to zero, no degradation will take place. Thus, once a point has been generated in such a location, it produces descendants in every consecutive generation until the entire simulation stops. In contrast, when the value is set above zero, the value of the corresponding grid cell is reduced by this specific value during the execution of every simulation run.

Calculated automatically no

Initial situation of local conditions

yes

no

Maximum number of generations

yes

no

Number of descendants for each parent point relative to local environmental conditions

yes

no

Maximum spreading distance

yes

no

Spreading distance with respect to local environmental conditions

no

yes

Spacing between new points

yes

no

Survivability threshold

yes

no

Spatial point distribution of new generations

no

yes

Exploitation value of local conditions

yes

no

Degradation of local conditions during time

no

yes

Development of the point shapefile during time

no

yes

According to these user-defined parameters, the simulation generates the defined number of consecutive points relative to the underlying grid values. Considering the minimum distance constraint, these points are then randomly distributed around the parent point in a circular manner within the maximum spreading width. Thus, the simulation is responsible for the distribution of the consecutive points in space relative to the local values of the underlying virtual spreading surface. Additionally, the simulation procedure automatically calculates the degradation of local environmental conditions and organises the storage of the data.

Table 3: Simulation parameters.

Two specific aspects of the simulation design are essential for the simulation results: the way in which the random point distributions will be produced within the simulation routine, and the effect of the user-defined minimum distance between generated points. Random point distributions in the ArcView 3.x environment are calculated using a random number request (‘Number.MakeRandom(min,max)’). Since the random number request becomes unstable when Nmin or Nmax are negative or exceed 231-1 on a Windows © system, the request is restricted to the range from 0 to 230 for the simulation (cf. Huber 1999). To generate uniform random point distributions for both x and y coordinates, a random number is picked within this range and then transferred to the space that a maximum spreading distance defines in the x and y directions. This procedure results in a uniform random point distribution within a rectangle, or, if x=y, to a random point distribution within a square.

The number of consecutive points and the maximum spreading width are set with respect to the local values of the spreading surface. A reference spreading width is determined during the set-up routine of a single simulation run. Its specification relative to the spreading surface values is hard-coded in the following way: if (theChildren. (80)) then theChildValue = 3 newDistance = theDistance * 0.5

‘theChildren.’ refers to the value of the spreading surface at the place the “parent” point is located, ‘theChildValue’ determines the number of newly generated points during each simulation step and ‘newDistance’ is the maximum spreading width calculated relative to the reference spreading width ‘theDistance’. It is obvious in this section of the

If the desired output of the random points is circular, those points that do not lie within the circle are discarded. As-

58

CHAPTER 2 suming that a predefined number of random points lie within the circle, this procedure is repeated until the circle is filled with the predefined number of random points. A simple vector shift then places the resulting random point distribution around the origin. The Avenue code applied to this procedure is as follows:

To disseminate and control the cluster around the origin, an auxiliary ‘minimum distance’ routine has been implemented in the simulation. The routine controls the user-defined minimum distance between newly created points. It makes a noticeable impact on both the cluster and the general point distribution (SD Experiment 3). If the defined minimum distance compared to the maximum spreading width is relatively low, there is a tendency towards a sim-

theX = thePoint.getX theY = thePoint.getY thecircle = Circle.Make( theX@theY, newDistance) XRandom = Number.MakeRandom(0, nBig)/nBig * 2*newDistance) +(theX-newDistance) YRandom = Number.MakeRandom(0, nBig)/nBig * 2*newDistance) +(theY-newDistance) theRandomPoint = Point.Make(XRandom, YRandom) if (theCircle.intersects (theRandomPoint) = true)

‘thePoint’ means the point of origin, ‘nBig’=230, and ‘newDistance’ equals the maximum spreading width. The result of the calculation is a circular random point distribution within a given distance of the origin (Fig. 9a, cf. Simulation Design (SD) Experiment 1 on CD). To achieve a random point distribution with a cluster of points near the origin, a sine/cosine formula together with the random number request has been introduced. During the transfer from rectangular to polar coordinates, the uniformity of the random point distribution is lost and a tendency for strong clustering around the origin occurs. This transformation of the uniform random point distribution into a clustered point distribution is a modification of the Box-Muller transformation of uniform into Gaussian distributed random numbers (Box & Muller 1958). The original Box-Muller transformation produces points with a Gaussian distribution with a zero mean and a standard deviation of one around the original centre. Thus, the probability that points are generated in the centre of the distribution is very high, while the probability that areas further away have to be considered is low (Fig. 9b). Because such a strongly clustered point distribution is not intended for the simulation, the Box-Muller transformation has been modified. This modification produces a random point distribution with a clustering in the centre, but a comparatively uniform distribution of points towards the periphery (Fig. 9c, cf. SD Experiment 2). In Avenue code, the modified Box-Muller transformation is implemented in the following routine which accounts for both the maximum spreading width and the clustering of the points: theX = thePoint.getx theY = thePoint.getY Random1 = Number.MakeRandom(0, nBig)/nBig * (2*number.getpi) Random2 = Number.MakeRandom(0, nBig)/nBig * (newDistance)

Fig. 8: Random point distribution within a circle applying a) the Avenue random request, b) the Box-Muller transformation, and c) a modified variant of the Box-Muller transformation for the transformation of rectangular into polar coordinates. Number of points = 200.

XRandom = theX + (Random2*(Random1.cos)) YRandom = theY + (Random2*(Random1.sin)) theRandomPoint = Point.Make(XRandom, YRandom)

59

THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA

Fig. 9: Circular spatial arrangement of random points with respect to increasing minimum distances between points. This increase results in a change from a random to dispersed point distribution expressed in increasing values of R from the Nearest Neighbour Analysis. For further analysis and explaination cf. Simulation Design Experiment 3. Number of points = 200.

tion is not possible due to the random component implemented in the spreading algorithm for the descendants of each generation.

ple random point distribution. The cluster decentralises, but the points are still randomly distributed. This random point distribution disappears when the minimum distance or the number of predefined random points is increased. Now that the space for the distribution of random points is reduced, the points start to arrange themselves in a regular triangular lattice.

2.6 THE SIMULATION OF DISPERSAL IN ARTIFICIAL ENVIRONMENTS Simulations in artificial, constructed environments have been carried out to demonstrate the simulation behaviour in simplified spatial configurations. This allows for a better understanding of the real-world simulations: Only a restricted number of simulation parameters have to be changed, and the simulation results are directly comparable. Additionally, these manageable simulations point to the much clearer advantages and disadvantages of this kind of simulation than the more complex and comprehensive simulations of real-world situations.

The behaviour of the clustered random point distribution can be easily demonstrated using profiles through the corresponding point density plots or a Nearest Neighbour Analysis (cf. Conolly & Lake 2006:165, analysis performed using Spatial Statistics Tools in ArcGIS © 9.0). While the density profiles show a decrease in the point density within the centre of the point distribution, the Average Nearest Neighbour statistics indicate a shift from a random point distribution (R=0.97 for a distribution with a minimum distance of 0, cf. SD Experiment 3.1) to a dispersed point distribution (R=1.55 for a distribution with a minimum distance of 1 map unit and a dispersal radius of 10 map units, cf. SD Experiment 3.5). Because such behaviour is not desired in the simulation, the minimum distance function should be applied with care.

THE CONTRIBUTION OF CHANGING SIMULATION PARAMETERS TO THE SIMULATION RESULTS For the following simulations, a uniform spreading surface consisting of 21 by 21 grid cells and one point of origin is applied for the purpose of exploring the influence of the different simulations parameters on the simulation results. For the different experiments, the number of consecutive simulation iterations, changing maximum dispersal dis-

Another characteristic of the simulations using a random number generator is important to mention: the calculations will never produce the same results for multiple trials using the same parameters. An exact reproduction of a simula-

60

CHAPTER 2 Five simulation runs (SP Experiment 2.1-2.5) carried out with this set-up point to an aberration in the expected number of points generated. In all simulation runs, the number of calculated points is noticeably lower than the expected number (Table 4). This discrepancy is explained through consecutive points falling outside the dispersal surface. Those points are lost for subsequent calculations. This simulation behaviour represents an undesirable ‘edge effect’: about half of the newly generated consecutive points will fall outside the spreading surface and disappear from the simulation. The edges of the spreading surface show simulation behaviour that is similar to an absorbing barrier (cf. Yuill 1965), one which absorbs consecutive points but does not affect the transmitting point in its behaviour. In the following dispersal simulations, this unwanted effect has been avoided by applying a spreading surface that covers an area greater than the particular area under investigation.

tances and reduction of the values of the dispersal surface have been changed. The simplest simulation set-up (Simulation Parameter (SP) Experiment 1) includes one point of origin and a specified number of consecutive points (N=2187) that are generated simultaneously within a maximum spreading distance (10 map units) that allows for all points falling within the spreading surface. This set-up generates a predefined number of points within the specified spreading distance and a strong clustering of points around the initial point.

Fig. 10: Spatial pattern produced by a simultaneous calculation of randomly distributed points (SP Experiment 1).

This first simulation can be modified so that not all points are generated during one consecutive step, but rather within several iterations (SP Experiment 2). While the maximum spreading distance (10 map units) remains constant, the number of consecutive points per generation is reduced to N=2, while the number of iterations is set to eight. In theory, this should result in 2187 consecutive points during one simulation run with an exponentially growing number of points.

Generation

Ideal number of points

1

1

1

1

1

1

1

2

3

3

3

3

3

3

SP Exp. 2.1

SP Exp. 2.2

SP Exp. 2.3

SP Exp. 2.4

SP Exp. 2.5

3

9

9

8

9

7

9

4

27

25

22

23

20

24

5

81

67

57

62

48

65

6

243

183

153

151

136

168

7

729

479

397

394

352

430

8

2187

1222

1062

1002

905

1098

Table 4: Comparison between ideal number of consecutive points calculated per generation and actual numbers obtained during simulation runs of SP Experiment 2.

In the comparison of point distributions from SP Experiments 1 and 2, a comparatively weak clustering of the consecutive points around the initial point is conspicuous in the runs of SP Experiment 2. This point distribution can be explained by two different factors. First, the centred point distribution model generates consecutive points with a higher probability around the parent point. Second, once a point is created, it continues to generate consecutive points during all further simulation steps (cf. SP Experiment 4). Another remarkable feature of the point distribution is the existence of secondary point clusters that result from random points generated during the first steps of the simulation run. The longer they exist, the more time they have to produce consecutive points in their neighbourhood. An additional characteristic can be demonstrated with these simulations. Both the resulting point distribution and the sum of all points generated during the five simulation runs differ noticeably as a result of the repeated execution of the random point request. When reducing the maximum spreading width to 5 map units but leaving all other parameters fixed (SP Experiment 3), the resulting point distribution shows a cluster around the point of origin, and the number of consecutive

Fig. 11: Spatial pattern produced by a consecutive calculation of randomly distributed points (SP Experiment 2.1).

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA secutive points. Once the threshold is exceeded, the respective grid cell acts as an absorbing barrier. Points already existing or falling within this area will not contribute to the simulation. The simulations ended when no further consecutive points could be generated.

points is closer to the expected value of N=2187 (N=2093, in comparison to the mean value from Experiment 2, N=1058). This is the result of only a few points being generated outside of the spreading surface. The decrease of the maximum dispersal distance for each individual point causes a reduction in the overall dispersal distance and an increase in point density within the ‘core area’ near the starting point. Due to the reduced dispersal distance, the border of the simulation surface is only marginally reached during eight consecutive generations. Therefore, the edge effect decreases.

Fig. 12: Simulation result SP Experiment 3.

The last two simulation parameters that influence the simulation results are the reduction of the values of the spreading surface and the threshold value that allows for a consecutive dispersal. The simulation allows for the introduction of a user-defined reduction value of the spreading surface, used in the event that a point is located in a given raster cell. The original value of the raster cell starts to decrease as soon as a point is located in it. When the threshold is reached, the point disappears from the simulation. The same simulation behaviour occurs when the original value of the dispersal surface is below the threshold. Then a point falling inside this raster cell is removed from the simulation. The conception behind this parameter is an actual degradation of local environmental conditions during the presence of human populations and an exclusion of habitats not suitable for human habitation.

Fig. 13: Simulation results obtained from simulation set-ups a) SP Experiment 4.1 and b) SP Experiment 5.1 indicating the influence of decreasing dispersal widths on the resulting point distributions.

The implementation of this active interaction between the generated random points and the spreading surface produces a ‘dispersal wave’ consisting of a circular point distribution dispersing from the initial starting point outward toward the periphery. This effect is more pronounced if the maximum spreading distance is lower compared to the spreading surface grid size (e.g., SP Experiment 5, where maximum spreading distance = 1.25 map units) while it is somewhat blurred when a wider dispersal distance is applied (e.g., SP Experiment 4, where maximum spreading distance = 5 map units). Exploring the number of active consecutive points during the simulation runs of SP Experiments 4 and 5, it becomes obvious that an increase in consecutive points occurs in both simulations until the edge of the spreading surface is reached, followed by a decrease in the point number (Fig. 15). Differences in the timing of the turning points of SP Experiments 4 and 5 directly result from the choice of different maximum dispersal distances.

The effects these two parameters have on the whole simulation will be examined with two experiments (SP Experiment 4 and 5). In both cases the spreading surface is the same 21 by 21 lattice as before, with a uniform initial value of 100 for each grid cell. During each consecutive step of the simulation, at each cell where a generated point is located, the cell value will be reduced by a value of 20. The threshold for the generation of consecutive points is 60. With this set-up, points falling in one specific cell of the grid can produce a maximum of three generations of points, while a point falling in the same grid cell during a consecutive iteration, by which the initial value of 100 is reduced to 80, will produce only two generations of con-

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CHAPTER 2

Fig. 14: Number of active points. Comparison between 3 runs of SP Experiment 4 and SP Experiment 5 which differ in the maximum spreading distance.

Fig. 15: Number of active points per generation divided by area obtained from circular buffers with a constant radius but area which increases by a power of 2.

THE INFLUENCE OF DIFFERENT ENVIRONMENT SET-UPS

Comparing the number of active points of SP Experiments 4 and 5 in respect to the area covered, it is clear that the increase in active points is followed directly by a decrease in Experiment 4, with a sharp turning point occurring at generation 10 (Fig. 16a). At this time, newly generated points start ot fall outside the dispersal surface. In contrast in SP Experiment 5 there is a substantial interval between generations 10 and 20 where the number of active points increase only as a result of the increasing area the circular point distribution is dispersing (Fig. 16b). With an increase in the radius from the point of origin, the space provided increases quadratically, as it does approximately the number of points. During this time interval, the simulation is stable and shows its intended uniform behaviour with an equilibrium of dispersing points relative to a uniform spreading surface. Without any dynamic modification of the spreading surface, the number of consecutive points would increase exponentially.

To understand the influence of different environmental setups in relation to the simulation results, different spatial configurations have been investigated consisting of a restricted number of patches with differing degrees of favourability for the spread of populations. For all experiments, one starting point has been applied on a grid of 21 by 21 cells. The simulation parameters follow the dispersal rules of the informal dispersal model developed in section 2.7, which equates to a reduction of consecutive points and a wider maximum spreading distance when local conditions are unfavourable. The simplest investigated environmental set-up is a homogenous plain (Experiment 1): environmental conditions are the same at all locations. During the simulation run, a dispersal wave develops that crosses the whole surface

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA fer and interpret this simulation result in terms of the most likely ways of dispersal, it is clear that most populations would seek the most favourable environment, while unfavourable areas would be entered only marginally during the dispersal process.

starting from the single initial point. Irregularities in the wave, observable through point clusters in the resulting dispersal point distribution, are caused by the random distribution of points. The general uniformity of the dispersal mirrors the characteristics of the spreading surface. Its homogenous shape allows for a uniform dispersal in all directions, the time a specific region is reached by the wandering point cloud is exclusively determined by its Euclidean distance from the starting point.

A third artificial spatial configuration which has been tested is a spatial bottleneck, where two areas of favourable environmental condition are connected by a rather narrow corridor (Experiment 3). With the same simulation parameters as before, a point cloud establishes itself around the starting point before entering the corridor. During the crossing of the bottleneck, the number of active points decreases remarkably. Most randomly generated points will fall outside the area above the defined threshold, where their “survival” and thus the generation of consecutive points is not possible. The dispersal rate accelerates in accordance with the conceptual model. Once this narrow channel is crossed, the wandering point cloud establishes itself again with a higher point density and more active points. This simulation behaviour closely corresponds to

A modification of the homogeneous plain is the inclined plain with a steady gradient from favourable to unfavourable conditions (Experiment 2). The dispersing point cloud is clearly determined in its shape from the spreading surface. Once areas with less favourable conditions are reached, the dispersal accelerates but thins out in agreement with the model dispersal rules. In contrast, the dispersal in the more favourable areas is slower. Again, the resulting point distribution reflects the spreading surface. Areas of favourable condition show a remarkably higher simulated point density than unfavourable areas. To trans-

Fig. 16: Simulation results exploring different artificial environmental scenarios. a) Plain surface (Exp. 1), b) ramp (Exp. 2), c) bottle neck (Exp. 3.1), and d) irregular patches (Exp. 4.1).

64

CHAPTER 2

Fig. 17: Number of active points with respect to a spatial bottleneck situation during two simulation runs (Experiments 3.1 and 3.2).

The last artificial environment investigated consists of a number of irregular patches representing different environmental conditions (Experiment 4). Again the dispersal starts in a comparatively well-suited area with an increase in the number of active points. During the consecutive steps of the simulation, spatially adjacent patches become involved in the dispersal process. Here, the simulation indicates remarkable differences in relation to the predefined environmental set-up. Comparatively favourable areas show a higher point density than unfavourable areas. In

the expected picture. Based on the random movement approach, when points fall in unfavourable areas in a spatially restricted simulation, a decrease in the overall point density is generated due to unsuccessful trials. The bottleneck situation can be easily identified in a plot that displays the number of active points during the simulation run. This spatial situation remarkably reduces the overall number of active points (Fig. 18).

Fig. 18: Number of active points during five runs of Experiment 4 exploring an artificial environment consisting of irregular patches. While the general pattern remains the same for all simulations there are clear differences within the single runs.

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA lated during several iterations, which spreads over the surface starting from one user-determined point. In every simulation the starting point and each of the consecutive points generate further points in their neighbourhood until a threshold is reached. The actual spreading width of consecutive points is determined by the value of the spreading surface and the random component. The emerging spatial and numerical point distribution is no longer influenced by any adjustment to the simulation, but created exclusively by the spatial configuration of the spreading surface.

cases where unfavourable areas become involved in the dispersal process, it takes place preferentially at the periphery, closely adjacent to more favourable areas. The number of active points during the simulation run is surprisingly constant, although the spatial distribution of the patches at the spreading surface is highly irregular (Fig. 19). This emerging picture corresponds to the intended simulation behaviour. The wandering point cloud disperses along a route suggested by the spatial arrangement of the patches where the most favourable environmental conditions occur. The general simulation behaviour is mostly influenced by these rather constant set-up. However, the behaviour of each simulation run is also affected by random occurrences in patches where less favourable environmental conditions predominate.

2.7 ANALYTICAL POSSIBILITIES FOR THE SIMULATION RESULTS The simulations described above contain both a spatial and temporal component. A point cloud wanders across the spreading surface with time. The emerging picture results from several, successive, time-discrete calculations. Several possibilities exist for analysing the simulation results. They can be differentiated by focusing on the resulting point distribution as a single entity, thereby neglecting the

The final results of all simulations within the artificial environmental set-ups are point distributions of higher density within more favourable areas. Unfavourable areas with values below a certain threshold have not been populated. This result is produced by a wandering point cloud, calcu-

Fig. 19: Simulation results and analyses. a) Point distribution with respect to dispersal surface values (’environment’), b) point density, and c) time of arrival (TOA).

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CHAPTER 2 temporal component, or by involving time-sensitive analyses. Because the main goal of the simulation is to calculate paths of dispersal on the basis of environmental conditions, the resulting point distribution becomes the primary focus of any subsequent analysis.

dering point cloud represents neither human individuals nor human population groups. Instead, the cloud represents an artificial entity governed by several rules deduced from real-world human behaviour to assess possible dispersal routes.

The simplest way to analyse potential dispersal routes is to inspect the simulation results visually. Considering a diverse environment consisting of several patches with different environmental conditions and a known starting point, the spatial distribution of the consecutive points generated during the whole simulation process gives a first impression of the routes. Areas reached by the wandering point cloud can be interpreted as places where dispersal took place, while areas free of generated points did not participate in the corresponding dispersal.

3 SUMMARY: USE AND ABUSE OF MODELS AND SIMULATIONS In this chapter, a model for the dispersal of mobile herders over the Arabian Peninsula has been developed. The starting point of this investigation was the archaeological evidence for this dispersal in both the Levant and the Arabian Peninsula, as discussed in chapter 1. It was proposed that this dispersal was influenced by environmental conditions. Although more favourable climatic conditions in Arabia during the early and middle Holocene brought forth the dispersal, the pathways taken were determined by the potentials and constraints of movement through a landscape on the basis of local environmental conditions. Thus, the dispersal is seen as an interplay between local environmental setting and human decisions. It could have been demonstrated that this understanding differs significantly from current dispersal models for the spread of the Neolithic. These models predominantly neglect the influence of the spatial configuration of environmental variables and tend to emphasise the importance of population dynamics.

This qualitative exploration can be quantified using point density plots. In addition to visualising the presence of points, these plots also show absolute density within a given area. The point density directly links to the assumptions of the dispersal model. More points will be generated in areas with more favourable conditions. Therefore one would expect that the point density is remarkably higher in these favourable areas. Thus, the point density plot mirrors at first the conditions of the dispersal surface, with one crucial difference: the point density can only increase in a specific area if the wandering point cloud reaches a region of favourable conditions. The probability that a specific area is covered by the dispersal depends in turn on its size and spatial remoteness.

Looking upon the dispersal of the Neolithic over the Arabian Peninsula as an environmentally dependent spatial process which includes population movements into formerly uninhabited areas, postulations from the fields of both geographic innovation diffusion and ecology have been applied to establish the model. The conceptual ideas are partly derived from Hägerstrand’s „Innovation diffusion as a spatial process“. But in contrast to Hägerstrand, the Neolithic dispersal across the Arabian Peninsula has not been considered as the diffusion of an innovation, but as the dispersal of both an innovation and its bearers.

The analysis of the temporal component of the simulations focuses on the question of whether a specific area became involved earlier or later in the dispersal process. As previously discussed, the simulation is not based on a population model, but accounts for the dispersal of populations with respect to environmental conditions. Thus, the consecutive iterations performed by the simulation have no relationship to any absolute time scale in years. Nonetheless, relative comparisons can be made between different simulation runs or different branches developing during one simulation. For this type of analysis, the spreading surface is gridded off into squares. Then, the generation at which a point falls within a specific square for the first time is assessed. This approach generalises the simulation results by placing emphasis on when a specific area is probably reached for the first time. In this study, it is discussed as ‘time of arrival’ analysis.

The configuration of space is of major importance to both the diffusion of an innovation and the spread of population groups. Physical or cultural barriers prevent dispersals, while areas with favourable environmental conditions support both the dispersal of populations and the diffusion of innovations. Following this approach, connected areas with a favourable environmental setting are considered as preferred pathways for dispersal, while spatially dissected regions or areas enclosed by barriers are considered less likely to have participated in the dispersal process.

Finally, the dispersals have been displayed as dynamic animations in which a succession of pictures allows for the visualisation of the spatial-temporal progression of the simulation. I want to emphasise that the presentation of the simulation process should demonstrate only the development of the resulting point distribution. It is the point distributions themselves that form the basis of the subsequent analysis of the possible dispersal routes through the exploration of point density and ‘time of arrival’ maps. The wan-

Based on this conceptual model, a simulation of the dispersal has been developed within a GIS environment. Within this simulation, environmental conditions are represented through a spreading surface. This surface integrates the spatial distribution of environmental conditions. During

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA the simulations, a wandering point cloud driven by explicit dispersal rules interacts with this surface. These dispersal rules determine both the maximum number of newly generated consecutive points (descendants) and their maximum spreading width. In contrast, the actual number of consecutive points and spreading width are determined by the spreading surface. Further on, the exact spatial location of the consecutive points is computed using a random algorithm. Thus, the simulation closely resembles a random movement of individuals or population groups, but is influenced by local environmental conditions. The emerging spatial and numerical point distribution is no longer influenced by any adjustment to the simulation, but created exclusively by the spatial configuration of the spreading surface. The application of simplified dispersal rules in contrast to more complex population dynamic models is justified through the focus of the simulation on dispersal routes. Within the simulation procedure, the implementation of a random algorithm replaces that part of rational human decisions that are not accessible through direct archaeological investigation. It has been further demonstrated in artificial environments that this simulation design produces the expected results for the dispersal of population groups under the aforementioned assumptions. The point cloud follows those regions of the spreading surface where more favourable environmental conditions are indicated. In contrast, unfavourable areas are only covered by the dispersal in areas adjacent to predominantly favourable conditions. If an area of favourable conditions is dissected by a barrier, the probability that this particular region becomes integrated into the dispersal is inversely proportional to the spatial extent and strength of this barrier. Does such a simulation result legitimate the efforts to establish a conceptual model, which is then transferred into a simulation? The main advantage of developing a simulation based on a conceptual model is that it offers the possibility of explaining, rather than describing, empirically observable archaeological patterns. In the conceptual model, I suggest a strong interdependence of the Neolithic dispersal routes upon local environmental conditions. The simulation design rigorously follows these model assumptions. Therefore, a subsequent comparison between the simulation results and the archaeological evidence can be used to reject the hypothesis of an environmentally driven process. If the simulated dispersal pattern does not fit the archaeological evidence, then factors other than local environmental conditions have to be held responsible for the dispersal. But if the patterns show a high degree of consistency, it can be expected that the most likely ways of the dispersal of the Neolithic over the Arabian Peninsula have been found. Such a test would not be possible without a simulation, which generates ‘empirical’ data of its own–a necessary prerequisite for a comparison with independent, empirical, archaeological data.

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CHAPTER 3

CHAPTER 3 SIMULATING PATHWAYS OF DISPERSAL OVER ARABIA resolution of the available data sets. Bringing these environmental parameters into a hierarchical order of mutual interdependence (cf. Schultz 2000:23p.), it becomes apparent that some parameters were controlled by more superior factors than others. These interdependences will be used to substitute parameters of the spreading surface for which no appropriate information is available. In this system, the highest order of independent parameters includes climate and geological structure. Both have a strong impact on topography, with all three together influencing hydrological conditions. These four factors in turn determine the prevailing soils, vegetation and fauna, which themselves act upon humans.

In this work the spread of the Neolithic over the Arabian Peninsula is considered as an environmentally dependent process. As argued in the previous chapters, the spatial dispersal of population groups and innovations is influenced by the distribution of resources, as well as physical barriers within a landscape. This is especially true for regions where resources are sparsely distributed and environmental conditions are generally unfavourable for human habitation and dispersal. The following chapter will begin with a description of the physical environment of Arabia with respect to its potential influence on a dispersal of Levantine Neolithic mobile herders. Then the statistical procedure to obtain spreading surfaces for the simulations of the dispersal from data sets characterising the environmental setting of Arabia will be described. After the description of the simulations under different environmental scenarios and in different initial situations, the chapter will finish with a discussion of the implications of the simulation results for the dispersal of the Neolithic over the Arabian Peninsula.

1 ENVIRONMENTAL CONDITIONS IN ARABIA AS AN IMPERATIVE FOR THE NEOLITHIC DISPERSAL Environmental conditions in Arabia during the Early Holocene formed the basis on which the dispersal of the Neolithic took place. Looking upon the environment as a system which is determined by the interplay of different environmental factors, these principal environmental components will be assessed individually for their impact on the Neolithic dispersal and subsequently combined them for the simulations. It is neither the task nor the intention to present a complete description of the physical setting of Arabia. Instead, the selection of environmental factors is determined by the expected impact of the environmental parameters for the Neolithic dispersal.

Fig. 20: Mutual interdependence among environmental factors after Schulz (2000:23p.). For the simulations of the Neolithic dispersal over the Arabian Peninsula, lower order factors have been partially replaced by higher order factors.

Although the book focuses on the Neolithic dispersal into Arabia, adjacent regions are included in the spatial extent of the spreading surface as well. This has been primarily done to minimise the influence of edge effects during the simulations. However, the impact of environmental conditions in the surrounding areas of Arabia should also be considered. Therefore, an area between 10° and 40° northern latitude and 30° to 60° eastern longitude was chosen for the simulations. With these spatial boundaries, the area under consideration includes the Arabian Peninsula, the easternmost parts of North Africa, the Levant, and the western margins of Southwest and Central Asia.

Environmental factors which will be considered include climatic conditions during the early Holocene as a necessary prerequisite for the Neolithic dispersal, in addition to topography, hydrology, pedology and vegetation. Although the wild fauna is also one parameter of the environment, it will not be assessed here due to the lack of valid datasets for the distribution of wild species during the early Holocene. The same is at least partially true for the vegetation, which will be only briefly described, but not incorporated into the model as a consequence of the low spatial

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA

1.1 CLIMATE

due to descending air and substantial insolation. Consequently, less than 10% of the total annual precipitation falls during summer. The only exceptions are the southern and south-western areas of Arabia, which are influenced by Tropical Maritime air from the south-west monsoon. These areas receive between 20 and 80% of their total annual precipitation during the summer months. At present, the influence of the Tropical Maritime air masses on the Arabian Peninsula is spatially limited by the Tropical Continental air mass that prevails over most of its land mass (Fisher & Membery 1998).

Climatic conditions set the framework for geomorphological processes, soil formation, vegetation development and land-use potentials (Schulz 2002:25). They are responsible for temperature patterns and the water balance in the landscape. Under present environmental conditions, the spread of Neolithic herders with flocks consisting of sheep, goat and cattle from the Levant across the Arabian Peninsula is impossible due to sparse vegetation and the absence of surface water in most parts of the land mass. But evidence for significant climatic change since early Holocene times comes from a wide range of data, including dripstones, lake sediments, pollen cores, phytoliths and faunal remains.

Thus, the climate of the Arabian Peninsula is determined by three different global climatic systems. While the central part of Arabia is located in the middle of a subtropical dry area principally influenced by Tropical Continental and Polar Continental air masses, its northern border is under the influence of Polar Maritime air masses during the winter months. In contrast, the southern part of Arabia is for part of the year under the influence of the Indian Ocean Summer Monsoon.

PRESENT CLIMATIC CONDITIONS At present, the Arabian land mass is part of the subtropical belt that covers North Africa, Arabia and parts of Central Asia along the Tropic of Cancer. Applying a simple model of atmospheric circulation, the aridity in this area is caused by a descending, and therefore dry, air mass of the Hadley cell (Wushiki 1997:4, Weischet 1995:255). On a regional scale, the climate of the Arabian land mass is dominated by the influence of Polar Continental and Polar Maritime (North Atlantic) air masses, which occur predominantly during the winter months, and Tropical Continental and Tropical Maritime (Monsoonal) air masses during the summer months (Fisher & Membery 1998:7pp.). Mean total annual precipitation shows a high degree of spatial variance, ranging from less than 50 mm/year in the hyperarid interior of the Peninsula up to more than 1000 mm/year in the south-western highlands of Yemen, with most areas of Arabia receiving between 50 and 150 mm of rainfall per year. Inter-annual variability of precipitation is generally high.

Climatic conditions in the Levant adjacent to the Arabian Peninsula in the northwest result from different atmospheric mechanisms within the eastern Mediterranean zone. Today, this region is characterised by an almost absence of precipitation during the summer months, when the global circulation of air masses shifts northward, and the Mediterranean is influenced by subtropical highs. During the winter months, the global circulation system shifts southward, so that the Levant is affected by Polar Maritime air masses forming cyclones that result in precipitation (Schultz 2000:316pp.). Because these air masses move from west to east, the western flanks of the Levantine mountain ranges receive significantly higher precipitation than the eastern flanks. Therefore, a steep gradient in the spatial distribution of precipitation decreasing from west to east can be observed in the Levant.

CLIMATIC CONDITIONS DURING THE EARLY AND MIDDLE HOLOCENE

The sources of precipitation in the different regions of Arabia correspond to the influence of the dominating air masses. Winter precipitation in most parts of Arabia is generated through the confluence of the Polar Continental air mass, originating over Central Asia, with incursions of low-level Tropical Maritime air from the Arabian Sea. The proportion of winter precipitation compared to annual precipitation varies over the different regions of Arabia. While accounting for 40-50% of the total annual precipitation in the north, this increases to 40-70% in the east and southeast, and 40-60% along the north-western coastal strip. Polar Maritime air masses also affect the Arabian Peninsula during the winter months, when mobile cyclones originating in the North Atlantic cross the Mediterranean from west to east and strike the northern part of Arabia with thunderstorms and torrential rain.

Compared to today, climate archives from the Early and Middle Holocene of the northern and southern part of the Arabian Peninsula indicate a change in the climatic regime towards increased precipitation for both the Levant and southern Arabia. Although simultaneous, this increase in rainfall has two different sources based on the location of the Arabian land mass with respect to global atmospheric circulation patterns. While an intensification of Mediterranean cyclones can be observed in northern Arabia (Arz et al. 2003, Vaks et al. 2006:397), the south benefited from an increased monsoonal influence (Fleitmann et al. 2003b). The best evidence for moister climatic conditions with a confident age model in the southern part of the Arabian Peninsula comes from speleothems investigated in northern and southern Oman and include dripstone H5 from Hoti

The summer climatic regime in Arabia is dominated by Tropical Continental air and thermal low pressure centres

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CHAPTER 3 drier conditions in Northeast Africa occurred around 6500 cal BC, while the second step started about 4000 cal BC and lasted until 1800 cal BC. The intermediate period between 6500 and 4000 cal BC is characterised by a series of rapid high-amplitude variations in the isotopic record, which indicate fluctuating climatic conditions during this time (Jung et al. 2004:33).

Cave in northern Oman (cf. Burns et al. 1998, Neff 2001) and dripstone Q5 from Qunf Cave in southern Oman (cf. Fleitmann et al. 2003a). Both dripstones show a corresponding change in their 18O isotope signatures with lower δ18O values during the time interval between 8000 and 4000 cal BC. This variation in the isotopic signal is explained by a northward shift in the southern Arabian climate regime driven by the Indian Ocean Summer Monsoon (Fleitmann et al. 2003b).

Similar significant climatic changes occurred in the Levant during the early and middle Holocene (Robinson 2006). A dripstone sequence from Soreq Cave in Israel indicates high precipitation between 8000 and 5000 cal BC (BarMatthews et al. 1997:165). For the Soreq speleothem it is suggested that low δ18O values correspond to periods of increased annual rainfall in the eastern Mediterranean (Bar-Matthews et al. 2000:148). Maximum rainfall on the western flanks of the Levantine mountain ridges during the Holocene occurs simultaneously with periods of sapropel formation in the eastern Mediterranean region between 6500 and 5000 cal BC (Bar-Matthews et al. 2000:149pp., Vaks et al. 2003:189). Additional evidence for a phase of moister climatic conditions during the early Holocene in the Levant comes from investigations on the isotopic composition of land snails. According to the molluscan data, the boundary of the Negev desert shifted about 20km south of its present position between 6500 and 6000 uncal BP (Goodfriend 1991:423).

During the Last Glacial Maximum/Terminal Pleistocene (and again today) the Inter Tropical Convergence Zone (ITCZ), the driving force behind the Indian Ocean Summer Monsoon, was located south of the Arabian land mass. A northward shift in the ITCZ occurred during the Early Holocene between 9000 and 4000 cal BC and was accompanied by a northward extension of the Monsoon belt. The growth of speleothem Q5 starts about 8300 cal BC, indicating a monsoonal intensification at about 17°N latitude during this time. Evidence for the extensive development of palaeolakes and botanical data both strongly suggest that this shift in the Summer Monsoon led to a substantial increase in precipitation. A shift of the ITCZ is again evident at the end of the early Holocene, but this time in the opposite direction, to the south. While the dripstone from northern Oman stopped growing about 4000 cal BC, the speleothems in southern Oman continued to grow until 1000 cal BC. Thus, the southern part of the Arabian Peninsula profited from the influence of the Indian Ocean Summer Monsoon for a longer period, with its extensions reaching the southernmost areas of Arabia even today.

Despite these changes in the amount and distribution of precipitation, temperatures in the eastern Mediterranean remained relatively constant. Investigations of the speleothems of Soreq Cave (Bar-Matthews & Ayalon 1997:163) and of the marine sediment core LC21 in the eastern Mediterranean (Rohling et al. 2002) indicate changes of about 2-3°C in mean annual temperature.

In contrast to the significant changes in the amount of precipitation in southern Arabia, records of air temperature indicate a different pattern. Based on reconstructions from the marine oxygen isotope record of the Arabian Sea (Murray & Prell 1992) and groundwater data from northern Oman (Weyhenmeyer et al. 2000:844) air temperatures during the early and middle Holocene were approximately 2°C lower than at present.

Evidence for moister climatic conditions between 7200 and 5200 cal BC with higher rainfall and increased surface runoff in the north-westernmost part of the Arabian Peninsula comes from marine sediment cores taken in the northern Red Sea (Arz et al. 2003). The increased humidity is explained by an enhancement and southward extension of rainfall from Mediterranean sources, which reduced the salinity of the sea water and increased the fluvial sediment supply. While this record corresponds well with reconstructed more humid conditions in the eastern Mediterranean region (cf. Soreq Cave speleothem), the termination of the humid phase in the Mediterranean occurs at about 2000 cal BC, significantly later than in the northern Red Sea. This region was humid only during the maximum wet phase, and thereafter, enhanced precipitation was restricted to the coastal areas that were orographically favoured (ibid. 120).

Evidence for the change of climatic conditions during the early Holocene in the south-western part of the Arabian Peninsula comes from a marine sediment core located in the Arabian Sea off the Somali coast (Core 905, Jung et al. 2004). Strontium isotopic measurements (87Sr/86Sr) on dust-borne sediments suggest generally more humid conditions between 8000 and 4000 cal BC followed by generally drier conditions during the late Holocene (Jung et al. 2004:33). Minima in the isotopic ratio of strontium represent periods of enhanced precipitation with intensive chemical weathering, while maxima correspond to periods when physical weathering dominates. A constant neodymium (143Nd/144Nd) isotopic signal in the same sequence points to a constant source of dust, which implies stability in the overall transport mechanism of the airborne particles during the Holocene. The Strontium isotopic record indicates a step-wise aridification of Northeast Africa and the adjacent part of southwest Arabia. The first step towards

Assembling the climatological evidence from Arabia and adjacent regions from between 7500 and 5000 cal BC, it is evident that climatic conditions made an extensive exchange possible between southern Arabia and the Levant within the interior of the Arabian Peninsula due to a south-

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA cent areas fall within the rain shadow. This influence of the Polar Maritime air masses can be found all along the coast of the Arabian Gulf as far south as the south-eastern tip of the Oman Peninsula, while its influence along the Red Sea is restricted to about 25°N latitude (ibid. 32). In contrast, the southernmost part of the Arabian Peninsula benefits from precipitation during the summer months, which is caused by the Indian Ocean Summer Monsoon. While summer precipitation is currently scarce north of 20°N latitude due to the effect of the Central Arabian high pressure area induced by a heating of the land mass, the highlands of south-western Arabia particularly benefit from monsoonal precipitation (ibid. 27).

ward shift of the Mediterranean precipitation system in the north and a northward shift of the Summer Monsoon system in the south. In this time frame of about 2500 years, the dispersal of the Neolithic over Arabia can be attributed to an advantageous situation in which the entire land mass of the Arabian Peninsula was influenced by two separate climatic regimes and benefited from those favourable conditions. The most important effects of higher precipitation are the increased availability of drinking water and the higher above-ground herbal biomass (Zhou et al. 2002:366) that served as fodder for the herding animals. Despite this growing evidence for a phase of moister climatic conditions on the Arabian Peninsula from a wide variety of climatic proxies, the calculation of a spatial climatic pattern from these data is complicated. A coherent spatial model for the variability of increased precipitation does not exist, nor is the quantification of this observed increased humidity possible. Yet both are necessary preconditions for the integration of climate into the simulations of the Neolithic dispersal over Arabia. It has been attempted to consider the influence of climatic patterns on the dispersal routes of Neolithic herders over the Arabian Peninsula by incorporating parameters for both precipitation and the number of ground frost days. While precipitation is responsible for the availability of herbal biomass in arid regions, the number of ground frost days limits the growth of vegetation, especially in mountainous areas.

In contrast to the present, palaeoclimatic research indicates a northward shift of both the ITCZ and the Indian Ocean summer monsoon belt. With this northward shift, higher precipitation should be expected over central Arabia, a result independently confirmed by palaeobotanic data (cf. section 1.5). Simultaneously an increase in Mediterranean winter precipitation and a southward expansion of the Polar Maritime air masses into the Southern Levant can be seen, as described above. The calculation of the assumed precipitation pattern during the early Holocene on the Arabian Peninsula is based on the present-day precipitation pattern. A gridded mean annual precipitation data set with a spatial resolution of 10´ was obtained from the Tyndall Centre for Climatic Change Research (http:// www.cru.uea.ac.uk/~timm/grid/CRU_CL_1_0.html, last accessed 04/12/06, for a description of the data see New et al. 2002). Data manipulation in ArcGIS included cropping to fit the research area, re-projecting the data into a Universal Transverse Mercator (UTM) coordinate system and subsequent interpolation to a spatial resolution of 10,000 m.

PRECIPITATION Sielmann (1971) has applied present climatic patterns of precipitation and temperature on a regional scale to answer archaeological research questions concerning the Neolithic of Central Europe. His approach is based on the consideration that spatial climatic patterns, such as drier versus more humid regions result from: a) the global circulation pattern; b) the distribution of land and sea; c) sea current; and, d) topography and relief. Thus, he incorporate factors which he considers to have been stable in Central Europe during the Holocene (Sielmann 1971:77). While his factors b), c) and d) can also be considered stable in Arabia, climate proxies indicate remarkable shifts in factor a) during the early Holocene.

This dataset represents the present amount and spatial distribution of rainfall and was subsequently multiplied with the spatially variable offset surface to consider changes in the precipitation pattern (For additional information on this offset surface cf. section Environmental Data Sets on CD). In the northern and southern part of the working area, an offset value of 2 has been applied to compensate for the increased monsoonal and Mediterranean precipitation. This offset surface doubles the amount of precipitation received in the north at 40°N and in the south at 10°N, while the present amount of precipitation remains unchanged between these two extremes. Additionally, a gradient is introduced to consider the decrease in Mediterranean precipitation and summer monsoon rainfall from west to east. This procedure results in a spatial data set that approximately reproduces the precipitation pattern during the Early Holocene. Although the application of a spatially variable offset function can consider only general trends in shifts of the precipitation pattern, these adjustments are more reliable approximations of the Early Holocene pattern of precipita-

In predominantly arid areas, the plant spectrum and the seasonality of flowering are largely influenced by the amount and seasonal distribution of rainfall (Fisher & Membery 1998:23). Today, the spatial precipitation pattern in Arabia indicates two zones with increased rainfall around the northern and southern margins of the Arabian Peninsula, while central Arabia receives the least precipitation. This precipitation pattern results from different air masses influencing the climatic conditions in Arabia. Around the northern fringes of the Arabian Peninsula, Polar Maritime air masses produce rainfall during the winter months. The highest amounts of precipitation can be found along the western slopes of the surrounding mountain ranges, while the eastern sides of the mountains and adja-

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Fig. 21: Precipitation pattern reconstructed for the early and middle Holocene.

The present spatial distribution of ground frost days closely reflects the topography of the research area, with more ground frost days in the mountainous regions in contrast to the lower lying areas. While the occurrence of ground frost in the southern part of the Arabian Peninsula is restricted to the Yemen highlands and the Hajar mountain range of the Oman Peninsula, substantial ground frost appears in the Levant along the Lebanon and Anti-Lebanon Mountain chains. An additional increase in the number of ground frost days can be observed both north and east of the study area. While this is predominantly caused by the high mountain chains of the Zagros and Taurus Mountains, intensive ground frost to the east is additionally induced by the strong continental climatic conditions present in the centre of the Eurasian land mass.

tion than the unmodified distribution of current precipitation.

GROUND FROST DAYS The second climatic parameter which has been considered in its influence on the dispersal of the Neolithic over the Arabian Peninsula is the number of days when ground frost appears. Although only a secondary factor in relation to plant growth in predominantly arid regions, it has to be considered as an important parameter restricting the plant growing period in the mountainous areas around the northern and north-eastern fringes of Arabia. In general, the occurrence of ground frost affects a die off of herbal and vegetative plant parts and thus reducing the availability of fodder for animals. In addition, the number of ground frost days can be considered as a factor limiting the accessibility of a specific region with regard to the necessity of sheltering for humans and animals.

Only minor differences exist between present day temperatures and mean temperatures during the Early Holocene (Murray & Prell 1992, Weyhenmeyer et al. 2000, Bar-Matthews & Ayalon 1997). Furthermore, topography and geographic latitude are closely interdependent. Therefore, the

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Fig. 22: Spatial pattern of present ground frost days per year.

by the fact that crossing steep terrain, normally associated with mountains, by foot causes more energetic expenditure compared to flat areas (Passmore & Durnin 1955, Soule & Goldman 1969). In addition, high mountain ranges and areas of high elevation show a restricted accessibility due to harsh climatic conditions, snow cover and sparse vegetation. Therefore, elevation constitutes one topographic factor that has been elected to include in the dispersal simulations.

number of ground frost days allows for the direct projection of the spatial distribution of present-day values to the situation during the early Holocene. Data for the spatial distribution of the number of ground frost days with a spatial resolution of 10´ has been obtained from the Tyndall Centre for Climatic Change Research (http://www.cru.uea.ac.uk/~timm/grid/ CRU_CL_1_0.html, last accessed 04/12/06, for a description of the data cf. New et al. 2002). Data manipulation in ArcGIS included cropping to fit the research area, re-projecting the data into a UTM coordinate system and subsequent interpolation to a spatial resolution of 10,000 m.

The other parameter related to topography that has been chosen is the sea coast. Coastal areas are generally favourable places for habitation and preferred transport routes. While habitation benefits from the high diversity of marine and terrestrial resources which are accessible along coastlines, transport routes are important when the possibility of seafaring is considered.

1.2 TOPOGRAPHY In most studies about Palaeolithic or Neolithic dispersals, the major, and often only, environmental parameter assessed in its influence on dispersal routes is elevation, that is, the presence of mountain ranges. This is widely justified

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Fig. 23: Main topographic features on the Arabian Peninsula.

MOUNTAIN RANGES

The formation of the Western Escarpment Mountains resulted from tectonic activities during the Tertiary lowering of the Red Sea coastal plain adjacent to the west of the Western Escarpment Mountains some 3000 m below the plain of the Arabian Shield. This mountain belt, running the full length of the peninsula, varies in width from 40 to 140 km (Chapman 1978:27p.). Due to its orientation along the long axis of the Arabian land mass, the Western Escarpment can be seen as a boundary separating the coastal plain of the Red Sea from the interior of Arabia. The inclination of the Arabian Shield promoted the development of steep escarpments and cuestas on the upturned edges of sedimentary beds which dip gently towards the east. The largest is the Tuwayq escarpment with a length of 800 km and a maximum elevation of 1500 m. On the other hand, the escarpments that form the eastern edge of the central plateau region represent only minor topographic barriers. These geomorphological structures served as important factors for dispersal because they caused an increase in the collection of water on their interior.

The geographic area under investigation is structured by significant mountain ranges. On the Arabian Peninsula, a long and narrow belt of mountains runs along the entire south-western border, while highlands dominate the southeastern part of Arabia. In addition, the high mountain ranges of the Taurus and Zagros form the northern border of the Peninsula. The presence of the mountain ranges surrounding the Arabian Peninsula is directly related to the geological history of the area. Located between Africa and Southwest Asia, the Arabian Peninsula consists mainly of a block of continental crust with a NNW-SSE orientation. As a consequence of uplifting processes in the area of the Red Sea and Gulf of Aden, the block dips slightly to the ENE. This inclination causes substantial mountain ranges along the south-western flank of the Arabian Peninsula which reach their highest elevation, 3760 m, in Yemen.

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Fig. 24: Elevation model of the Arabian Peninsula. Spatial resolution 1 km.

Beyond the mountain ranges, the Arabian Peninsula exhibits extensive plains which do not represent topographical barriers for the Neolithic dispersal: the Central Arabian Shield east of the Western Escarpment Mountains and at the northern and southern Arabian Deserts.

A third extensive mountain range exists on the south-eastern edge of the Arabian Peninsula. The Hajar Mountains are not part of the continental crust, but rather an area with its own geological history (Guba & Glennie 1998:40). Rising up to 3000 m, they form a spatially restricted, but significant barrier in this area.

As a source for the elevation data in the simulations the GTOPO30 digital elevation model (DEM) has been used. GTOPO30 is a free-source global DEM with a horizontal grid spacing of 30´´ (approximately 1 kilometer). It has been derived from several raster and vector sources of topographic information by the United States Geological Survey's Center for Earth Resources Observation and Science (EROS) in 1996 (USGS 2006: http:/ /edc.usgs.gov/products/elevation/gtopo30/ gtopo30.html). Topographic information for the area under consideration emanate from digital terrain elevation data and the digital chart of the world (USGS 2006: http://edc.usgs.gov/products/elevation/gtopo30/ source_img.html, last accessed 16/11/06).

The most extensive mountain ranges exist along the northern and north-eastern margins of the Arabian land mass and might have represented real obstacles to the Neolithic dispersal. After its detachment from the African plate during the Tertiary, Arabia drifted towards Southwest Asia. As a result of the collision between the Arabian and Asian plates, the Zagros Mountain range at the eastern flank of the Arabian block, and the Taurus Mountain range at its northern flank emerged. With elevations of up to 5000 m these mountain ranges are substantial barriers due to their harsh climatic conditions. As comparatively young mountains, they exhibit steep and craggy relief, further exacerbating their crossing.

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CHAPTER 3 be considered before the data-layer can be included in the spreading surface. There is worldwide evidence for changes in sea level during the Pleistocene glacial and interglacial periods. For the Last Glacial Maximum (LGM), a global sea level of 110 m below present has been demonstrated (Siddall et al. 2003). During this time, the Arabian Gulf dried out completely (Lambeck 1996:43, Teller et al. 2000:302pp.). After the LGM, global sea level rose to about -20 m at 7000 cal BC (Fairbanks 1989, Bard et al. 1990, Sidall et al. 2003). Since that time, sea level has fluctuated around its present level (Siddall et al. 2003:Fig.1).

The data processing of the GTOPO30 DEM was performed in ArcView3.2. The raw data have been recalculated to mask sea surfaces and then re-projected from the original geographic coordinate system into a projected UTM coordinate system. Subsequently, the data were re-sampled at a grid resolution of 1000 m. To include submarine elevations in the model, thereby allowing the lowering of sea-level without loss of topographic information, data from the GTOPO30 DEM have been combined with the lower resolution ETOPO5 gridded bathymetry data obtained from the National Geophysical Data Center (NGDC) (NGDC 2006: http:/ /www.ngdc.noaa.gov/mgg/global/relief/ETOPO5/, last accessed 16/11/06). ETOPO5 was generated from a digital data base of land and sea-floor elevations on a 5minute latitude/longitude grid in 1985. Data sources for the ocean areas come from the U.S. Naval Oceanographic Office (NGDC 2006: http:// www.ngdc.noaa.gov/mgg/global/relief/ETOPO5/ TOPO/ETOPO5/ETOPO5.txt, last accessed 16/11/06). The gridded data for the research area have been re-projected into a UTM coordinate system, interpolated to a 1000 m spatial resolution and subsequently combined with the GTOPO30 DEM in ArcGIS 3.2. This procedure resulted in an elevation data layer which shows both submarine and land surface elevation. Therefore, it can be applied for the calculation of elevation based on different sea-levels.

Not only has the sea level around the Arabian Peninsula been affected by the general rise across the globe. It has also been influenced by localised vertical tectonic movements and sediment infill along the coastlines. The latter is especially important for the Shatt al-Arab, where the Euphrates and Tigris rivers transported substantial sediment load into the Arabian Gulf (Larsen & Evans 1978, Cooke 1987, Sanlaville 1989, Aqrawi 2001, Pournelle 2003). The Arabian Gulf as a whole was flooded rapidly after the LGM (Lambeck 1996, Teller et al. 2000) with a transgression of more than 1000 km along its long axis occurring between 10,000 and 4000 cal BC. Due to local tectonic activities, this general picture becomes substantially blurred (Al-Asfour 1978, Vita-Finzi 1978, Dalongeville & Sanlaville 1987, Hellyer 2002). For the time of the proposed Neolithic dispersal into Arabia during the Early Holocene, the global curve indicates a sea level about 20m below present. But local explorations along the Arabian coast of the Arabian Gulf point to variations of several meters around the present sea level as early as 7000 cal BC (Dalongeville & Sanlaville 1987: 583 Fig.9). In contrast, investigations of the flooding history of the Arabian Gulf indicate that much of the southern part of the Gulf shore remained exposed until 6000 cal BC (8000 uncal BP). Areas such as the Great Pearl Bank between Qatar and Abu Dhabi did not become submerged until shortly after this time (Lambeck 1996:54). While these changes in sea level significantly impact the location of the shorelines in areas of low relief, coastal regions with high relief show remarkably less change.

SEA COASTS The Arabian Peninsula is surrounded by sea on three sides: the Mediterranean and Red Sea to the west, the Arabian Sea as part of the Indian Ocean to the south, and the Arabian Gulf to the east. In respect to the Neolithic dispersal, it is suspected that the sea might represent a substantial geographic barrier for groups of mobile herders with their herds. On the other hand, coastlines and adjacent offshore areas offer opportunities for human population groups with respect to mobility and subsistence. As indicated by the substantial Neolithic settlements on Cyprus, seafaring succeeded in transporting viable herds of domesticated animals as early as the PPNB (Peltenburg et al. 2000, 2001). With these finds, a dispersal of Levantine herders and their herds via the sea has to be considered.

For the dispersal simulations, small scale changes in the spatial location of the shoreline have been neglected with regard to changes in the global sea level. The reason for this is the spatial resolution of the applied dispersal surfaces. With a cell size of 10 by 10 km, minor fluctuations on coastlines cannot be readily examined.

The coastal areas offer a remarkable range of resources due to the juxtaposition of different environments. This special situation elevates the importance of seashores to habitation in general (Durante & Tosi 1977:137-141, Biagi et al. 1984:47p., Tosi 1986b:400, Biagi & Nisbet 2006), but especially during times of stress on terrestrial resources (Uerpmann & Uerpmann 2003:248pp.). Therefore the shoreline has been integrated into the spreading surface as an environmental data layer of its own importance.

The one exception is the estuary of the Euphrates. During the Early and Middle Holocene, the position of the Shatt al-Arab was influenced by two different mechanisms: first, the rise in global sea level, and second, the sediment load of the Euphrates and Tigris: While the rise in sea level caused a marine transgression in that area that pushed the shoreline inland, the sediment load of the rivers formed a prograding delta that pushed the shoreline offshore. Com-

Besides the value of sea shores to transport and subsistence, the changing spatial location of the shorelines must

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Fig. 25: Coastline of the Arabian Peninsula with a 10 km inland corridor.

Two different environmental data sets have been derived from this data set. An inland corridor at a distance of 10 km was created to allow for the exploitation of marine resources within approximately a day’s travel distance. In addition, the same reconstructed shoreline was buffered seaward with a distance of 30 km to obtain a second data layer that can be integrated into the spreading surface to allow for coastal navigation.

pared to the present shoreline, the first incursion of the sea into this area can be established around 6000 cal BC, when the delta was about 100km inland (Pournelle 2003:113p., ibid. Fig. 34). Because this spatial variation is well documented and remarkable in its extent, it has been included in the dispersal surface as an alteration of the present shoreline. For the calculation of the dispersal surface, the present location of the shoreline in the region has been applied as an approximation of the location of the coast during the early Holocene. The original data source comes from the ESRI world basemap files (http://www.esri.com/data/download/basemap/index.html, last accessed 20/11/2006). The sole adjustment to the present situation is the reconstruction of the shoreline for the time around 6000 cal BC following Pournelle (2003:Fig.34).

1.3 HYDROLOGY In arid and semi-arid environments, the productivity of the ecosystem is primarily limited by the availability of water (Fisher & Membery 1998:5, Schultz 2000:400). In these areas, water is accessible in three different forms: as precipitation, groundwater and allogenic rivers. In general, precipitation is rare in arid regions, while heavy rains occur locally at irregular intervals. Depending on pedological factors and vegetation cover, rainwater will be

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Fig. 26: Major permanent rivers along the fringes of Arabia. A 20 km corridor along the river courses has been calculated.

With respect to the Neolithic dispersal over Arabia the following layers of data with regard to the hydrological conditions have been incorporated for the calculation of the dispersal surface: major (allogenic) river courses, wetness in reference to local topography, and groundwater.

absorbed into the soil at varying rates. Especially in areas with higher relief and sparse vegetation cover, heavy runoff can be expected, together with minimal soil absorption (Wushiki 1997:8, Schultz 2002:228). The run-off flowing on the surface is then collected in drainage courses and gullies, which run together into wadis. Along these drainages, more water will be available for plants. Thus, higher biomass can be expected along drainage courses and also in areas with higher upslope areas that act as water collectors. The second source of water in arid regions exists where fossile groundwater is available near the surface, or where the geomorphological setting supports the sub-surface collection and storage of rain water. While the availability of fossile groundwater depends directly on the subsurface geological setting, recharge of recent groundwater also depends on the geomorphological and topographic situation. The third source of water in arid areas comes from allogenic rivers that derive their water from regions beyond the arid area where moister climatic conditions predominate.

RIVERS Today, no perennial rivers can be found in Arabia due to the prevailing arid climatic conditions. But even during the moister phase of the Early Holocene, no evidence for the existence of extensive year-round river systems exists. Exceptions might be smaller drainages that benefited from higher precipitation in the southern and northern parts of the Arabian Peninsula, but these will be considered below8. The only perennial rivers that have been considered for the present work are located at the northern fringes of the Arabian Peninsula, notably the Euphrates and Tigris rivers,

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THE NEOLITHIC DISPERSAL OVER THE ARABIAN PENINSULA the characteristics of arid and semi-arid regions that most precipitation does not infiltrate at the location it falls, but drain towards lower areas even where the surface inclination is slight (Schultz 2000:384p.). Thus, local topography and patterns of precipitation represent the most important determinants in the local distribution of surface water.

and the Nile river in adjacent North Africa (cf. Wushiki 1997:7). All these rivers draw their water from regions with more humid climatic conditions: the Nile in the tropics of Africa, and the Tigris and Euphrates in the western Mediterranean. Due to the extent of the area under consideration, additional minor tributaries have been considered for the spreading surface. In the Mediterranean Levant, these include the Jordan and Orontes Rivers, while along the foothills of the Taurus and Zagros Mountains, these include the Sakarya, the Kizil Irmak and Delice Irmak, the Murat, the Balikh and Khabur, and the Zab al-Kabir, Zab al-Asfal, Diyala and Karum.

Although there is evidence for a phase of moister climatic conditions in Arabia during the Early Holocene, it is not possible to derive quantitative and spatially explicit patterns of climatic parameters from these climate proxies. Due to its location between different climatic regimes (see section 1.1 this chapter), the Arabian Peninsula can be assumed to have variable climatic patterns with substantial differences between the seasons and high inter-annual variability.

To match the river courses with other topographic data during the calculation of the spreading surface, they have been derived from the composite GTOPO30/ ETOPO5 DEMs using the “Flow Direction” and “Flow Accumulation” hydrologic modelling procedures implemented in ArcINFO 8.3. Drainages with a calculated Strahler stream order 100 km2 derived from the GTOPO30 DEM.

ninsula and adjacent areas, basins occur in a variety of topographic situations, such as intra-dunal depressions within sand seas, river channels blocked by lava flows or structural basins developed during the faulting of mountain ranges.

agreement between calculated wetness and topography: The routine recognises the majority of the larger drainages in Arabia.

TOPOGRAPHIC BASINS

The location and extent of topographic basins has been derived from the combined GTOPO30/ETOPO5 DEM data set using the hydrologic modelling procedure implemented in ESRI’s ArcINFO 8.3. The maximum basin height has been limited to 1000 m. From the resulting vector dataset, only basins covering a calculated area >100 km2 were selected for further analysis to emphasise the importance of major basins as water-collecting, topographic features.

The last topographic factor to be assessed in its influence on the hydrological conditions in Arabia are topographic basins. These features are characterized by a converging shape like river valleys, but lack an outflow. Because of their shape they are apparent in the TWI data layer. But the fact that coalescing surface runoff is collected in the lowermost area of the feature represents an additional hydrological characteristic not expressed in the TWI. The absence of outflows promotes the storage of water. Thus, during humid periods these basins can develop into wetlands, making these areas favourable for human habitation. But when these lakes desiccate in drier phases, the substantial outwash of minerals from the surrounding areas results in the development of salt plains. Within the Arabian Pe-

With this procedure, large structural basins have been outlined within the Zagros mountains. In the northern part of the Arabian Peninsula, the Jordan Rift and Wadi Siram are considered. In southern Arabia, the Umm as-Samin de-

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Fig. 30: Hydrological conditions in Arabia. Class 1 refers to extensive and highly productive aquifers, class 2 indicates local or moderately productive aquifers, and classes 3 and 4 designate limited productive aquifers or areas with essentially no groundwater.

According to a regional summary (Burdon 1977), three major basins with fossil groundwater exist in Arabia. These basins are located in the cuesta landscapes of the Arabian Shield in central and eastern Arabia, and in the thick sediment bodies of the northern Arabian Peninsula. Thus, they are situated in structural depressions that lie on a tectonically stable basement. The outcrops of the water bearing formations along the edges of the basins are zones of groundwater recharge, while artesian springs can be found within the centres of the geological basins. These springs are often the origins of oases within the flat deserts, as is the case with the Al Hasa oasis (Hötzl & Zötl 1984:246).

pression and parts of the almost completely in-filled Mutaridah depression are depicted.

GROUNDWATER Occurrences of groundwater play an important role in supporting life in arid regions. They represent a spatial focus of human and animal activities. Most groundwater reservoirs in Arabia have their origin in structural basins. These aquifers are water bearing formations on the order of hundreds of kilometres, with the recharging and discharging areas far apart from each other. These distances account for the sometimes long intervals between recharge and discharge, which can range up to tens of thousand years (Wushiki 1997:10p.). Thus, these water sources exist without the need for concurrent recharge and do not directly depend on prevailing climatic conditions.

Another type of aquifer occurs in the coastal landscapes along the Red Sea and the Arabian Sea. As wadis with sediment fillings drain the hinterland, the less dense fresh water is forced to rise near the coastline by the intrusion of

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CHAPTER 3 aquifers, only a minor impact of these areas on possible dispersal routes can be expected in comparison to the effect that topographic features have on hydrological conditions.

denser seawater. The capacity of these aquifers varies with precipitation and size of the catchment area. The highlands of the Arabian Peninsula are characterised by an extreme scarcity of water in the extensive volcanic plateaus. However, in areas where the underlying crystalline basement is exposed, spatially restricted oases occur in the uppermost reaches of the wadis. These in turn feed additional wadi basins at the mid-altitudes (ibid. 246).

1.4 PEDOLOGY The characteristics of soils represent the final environmental factor to be extensively evaluated in its influence on the dispersal of Neolithic mobile herders over the Arabian Peninsula. Soils develop over a period of time through the interaction of a number of environmental factors such as climate, geology, topography and vegetation. Because the formation of soils involves the transformation of minerals within the soil profile – a process which necessitates the presence of water – the development of soils in arid and semi-arid areas is generally retarded (Stevens 1978:263). Additional factors that negatively affect the development of soils in these areas are wind and water erosion. In arid areas, the absence of plant cover allows for substantial wind erosion. In contrast, surface-runoff after rainfall removes finer soil particles in semi-arid areas with vegetation cover (Schultz 2000:377). Following the FAOUNESCO soil classification schema (FAO 1974), xerosols, arenosols, regosols and vertisols predominate in Arabia. Soils of the solonetz and solonchak type occur to some degree in topographic depressions, while fluvisols are restricted to the alluvial plains of exotic rivers. Most soils in arid and semi-arid areas show limited pedogenesis and have a very low humic content