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Title: Adaptive self-organization of Bali's ancient rice terraces
Authors: Lansing, J. Stephen
Thurner, Stefan
Chung, Ning Ning
Coudurier-Curveur, Aurélie
Karakaş, Çağil
Fesenmyer, Kurt A.
Chew, Lock Yue
Keywords: Science::Geology
Issue Date: 2017
Source: Lansing, J. S., Thurner, S., Chung, N. N., Coudurier-Curveur, A., Karakaş, Ç., Fesenmyer, K. A., & Chew, L. Y. (2017). Adaptive self-organization of Bali’s ancient rice terraces. Proceedings of the National Academy of Sciences, 114(25), 6504-6509. doi:10.1073/pnas.1605369114
Journal: Proceedings of the National Academy of Sciences of the United States of America
Abstract: Spatial patterning often occurs in ecosystems as a result of a self-organizing process caused by feedback between organisms and the physical environment. Here, we show that the spatial patterns observable in centuries-old Balinese rice terraces are also created by feedback between farmers' decisions and the ecology of the paddies, which triggers a transition from local to global-scale control of water shortages and rice pests. We propose an evolutionary game, based on local farmers' decisions that predicts specific power laws in spatial patterning that are also seen in a multispectral image analysis of Balinese rice terraces. The model shows how feedbacks between human decisions and ecosystem processes can evolve toward an optimal state in which total harvests are maximized and the system approaches Pareto optimality. It helps explain how multiscale cooperation from the community to the watershed scale could persist for centuries, and why the disruption of this self-organizing system by the Green Revolution caused chaos in irrigation and devastating losses from pests. The model shows that adaptation in a coupled human-natural system can trigger self-organized criticality (SOC). In previous exogenously driven SOC models, adaptation plays no role, and no optimization occurs. In contrast, adaptive SOC is a self-organizing process where local adaptations drive the system toward local and global optima.
ISSN: 0027-8424
DOI: 10.1073/pnas.1605369114
Rights: © 2017 The Author(s) (published by National Academy of Sciences). This is an open-access article distributed under the terms of the Creative Commons Attribution License.
Fulltext Permission: open
Fulltext Availability: With Fulltext
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