Gunn, Joel D.; Scarborough, Vernon; Folan, William J; Isendahl, Christian; Chase, Arlen F; Sabloff, Jeremy A; Volta, Beniamino. 2016. A distribution analysis of the central Maya lowlands ecoinformation network: its rises, falls, and changes. Ecology and Society. (Abstract)
We report a study of central Maya lowland dynastic information networks, i.e., six cities’ external elite ceramic influences, and how they reflect the decision-making practices of Maya elites over 3000 years. Forest cover, i.e., Moraceae family pollen, was added to the network analysis to provide ecological boundary conditions, thus ecologically moderated information networks. Principal components analysis revealed three dominant patterns. First, the networking of interior cities into powerful polities in the Late Preclassic and Classic periods (400 BCE-800 CE). In a second pattern, coastal cities emerged as key entrepôts based on marine navigation (Terminal and Postclassic periods, 800-1500 CE). Climate dynamics and sustainability considerations facilitated the transition. Forest cover, a measure of ecosystem health, shows interior forests diminished as interior cities networked but rebounded as their networks declined. By contrast, coastal forests flourished with networks implying that the marine-based economy was sustainable. Third, in the Classic, the network-dominant coast, west or east, changed with interior polities’ political struggles, the critical transition occurring after 695 CE as Tikal gained dominance over the Calakmul-Caracol alliance. Beginning with the Late Preclassic about 2000 years ago, it is possible to assign names to the decision makers by referencing the growing literature on written Maya records. Although the detectable decision sequence evident in this analysis is very basic, we believe it does open possible avenues to much deeper understanding as the study proceeds into the future. The Integrated History and Future of People on Earth–Maya working group that sponsored the analysis anticipates that it will provide actionable social science intelligence for future decision making at the global scale.