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ABSTRACT: While phenomenological investigations of ecosystem patterns often fail to reveal underlying dynamic mechanisms, we highlight
a universal principle for pattern formation in ecosystems. We consider ecosystems to be typical complex adaptive systems that
seek an optimal process to obtain maximized flux under given constraints. An analysis of the optimal process reveals underlying
microscopic dynamic mechanisms that induce complex patterns in ecosystems. We emulate ecosystem patterns using a Self-Organization
Feature Map: an artificial neural network theoretical model by which evolution processes, structural classifications, and
the fractal growth of ecosystem patterns can be simulated. The results help us analyze the formation and dynamics of ecosystem
patterns, with attending implications for the classification, protection, and optimization of ecosystems.
KeywordsEcosystem-Pattern Formation-Fractal-Dynamics-Maximum Flux Principle (MFP)
Environmental Modeling and Assessment 04/2012; 15(6):519-529. · 0.97 Impact Factor
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Sixth International Conference on Natural Computation, ICNC 2010, Yantai, Shandong, China, 10-12 August 2010; 01/2010
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Sixth International Conference on Natural Computation, ICNC 2010, Yantai, Shandong, China, 10-12 August 2010; 01/2010