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|Title:||Adaptive self-organization of Bali's ancient rice terraces||Authors:||Lansing, J. Stephen
Chung, Ning Ning
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.||URI:||https://hdl.handle.net/10356/137256||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|
|Appears in Collections:||EOS Journal Articles|
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