
Contents
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Introduction Introduction
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Background and Previous Research Background and Previous Research
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Methods Methods
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Biophysical Variables Biophysical Variables
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Anthropogenic Variables Anthropogenic Variables
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Results Results
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Discussion and Conclusions Discussion and Conclusions
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Acknowledgements Acknowledgements
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References References
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16 Growing the Ancient Maya Social-Ecological System from the Bottom Up
Get accessScott Heckbert Chief Environmental Scientist at the Alberta Energy Regulator, Canada
Christian Isendahl Associate Professor and Senior Lecturer in Archaeology at the Department of Historical Studies, University of Gothenburg, Sweden
Joel D. Gunn Lecturer at University of North Carolina at Greensboro, USA
Simon Brewer Assistant Professor at the Department of Geography, University of Utah, Salt Lake City, USA
Vernon L. Scarborough Distinguished University Research Professor and Charles Phelps Taft Professor in the Department of Anthropology at the University of Cincinnati, USA
Arlen F. Chase Professor of Anthropology at the University of Nevada, Las Vegas, USA
Diane Z. Chase Executive Vice President and Provost, and Professor of Anthropology at University of Nevada, Las Vegas, USA
Robert Costanza Professor and Chair in Public Policy at the Crawford School of Public Policy, Australian National University, Canberra, Australia
Nicholas P. Dunning Professor of Geography at the University of Cincinnati, USA
Timothy Beach Professor and Centennial Chair in Geography & Environment at the University of Texas at Austin, USA
Sheryl Luzzadder-Beach Professor, and Fellow of the C.B. Smith, Sr. Centennial Chair in U.S.–Mexico Relations, Department of Geography and the Environment at the University of Texas at Austin, USA
David L. Lentz Professor of Biological Sciences at the University of Cincinnati and Executive Director of the UC Center for Field Studies, USA
Paul Sinclair Professor Emeritus at the Department of Archaeology and Ancient History, Uppsala University, Sweden
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Published:07 April 2016
Cite
Abstract
Archaeological data can be represented in quantitative models to test theories of societal growth, development, and resilience. This chapter describes the results of simulations employing integrated agent-based, cellular automata, and network models to represent elements of the ancient Maya social-ecological system. The purpose of the model is to better understand the complex dynamics of the Maya civilization and to test quantitative indicators of resilience as predictors of system sustainability or decline. The model examines the relationship between population growth, agricultural production, pressure on ecosystem services, forest succession, value of trade, and the stability of trade networks. These combine to allow agents representing Maya settlements to develop and expand within a landscape that changes under climate variation and responds to anthropogenic pressure. The model is able to reproduce spatial patterns and timelines somewhat analogous to that of the ancient Maya, although this model requires refinement and further archaeological data for calibration.
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