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date: 25 June 2022

Abstract and Keywords

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.

Keywords: agent-based model, climate variation, archaeology, resilience, complex systems

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