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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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Earth Life Emerge
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VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies

1. Geosphere, Hydrosphere, Atmosphere

Watkins, Nicholas and Mervyn Freeman. Natural Complexity. Science. 320/323, 2008. Scientists from the British Antarctic Survey seek a revised Earth Systems Science which abides in and springs from a dynamically creative, self-similar network nature.

One such avenue is based on the science of complexity, which describes systems with many strongly interacting parts, concentrating on how the parts connect. A particularly influential strand of complexity science unites two ideas: universality (a given property arises in different complex systems) and emergence (complex behaviors arise from simple interaction rules. (323)

Werner, B. T. Complexity in Natural Landform Patterns. Science. 284/102, 1999. The standard reductionist methods are no longer suitable; therefore: An alternative modeling methodology based on the tendency of natural systems to self-organize in temporal hierarchies is described. (102)

Werner, Brad and Dylan McNamara. Dynamics of Coupled Human-Landscape Systems. Geomorphology. 91/393, 2007. From an issue on Complexity in Geomorphology, (see Preface by Murray and Fonstad above) University of California, San Diego geophysicists explain how both diverse land forms and persons in societies are distinguished by the same nonlinear, hierarchical phenomena. Circa 2010 might we at last realize that the very ground we walk upon is a natural scripture, with the same chapter and verse being repeated in our individual and communal lives?

A preliminary dynamical analysis of landscapes and humans as hierarchical complex systems suggests that strong coupling between the two that spreads to become regionally or globally pervasive should be focused at multi-year to decadal time scales. At these scales, landscape dynamics is dominated by water, sediment and biological routing mediated by fluvial, oceanic, atmospheric processes and human dynamics is dominated by simplifying, profit-maximizing market forces and political action based on projection of economic effect. (393) Based on this analysis, human-landscape coupled systems can be modeled using heterogeneous agents employing prediction models to determine actions to represent the nonlinear behavior of economic and political systems and rule-based routing algorithms to represent landscape processes. (393)

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