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Related Experiment Videos

The balance between adaptability and adaptation.

Robert E Ulanowicz1

  • 1Chesapeake Biological Laboratory, Center for Environmental Sciences, University of Maryland, PO Box 38, Solomons, MD 20688-0038, USA. ulan@cbl.umces.edu

Bio Systems
|January 5, 2002
PubMed
Summary
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Natural systems maintain a "window of vitality" between chaos and order, not at the edge of chaos. Network flows follow power laws, with a connectivity limit of ~3.015 connections per node.

Area of Science:

  • Ecology
  • Information Theory
  • Systems Theory

Background:

  • Michael Conrad's 1983 work, "Adaptability," utilized information theory's conditional entropy to quantify adaptability and adaptation.
  • Conditional entropy serves as a metric for network exchange connectivity, a crucial factor in system stability.
  • The May-Wigner criterion for linear dynamical system stability can be reformulated using conditional entropy to define the 'edge of chaos'.

Discussion:

  • Ecosystem flow network data reveal that natural systems typically operate within a broad 'window of vitality,' not precisely at the edge of chaos.
  • This window exists between purely chaotic and deterministic dynamics, suggesting a more resilient operational range.
  • Network flows within this vitality window exhibit power-law distributions, indicating scale-invariant properties.

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Key Insights:

  • Natural self-organizing systems are not confined to the 'edge of chaos' but exist within a wider 'window of vitality.'
  • Power-law distributions characterize network flows in this vital region.
  • A theoretical upper limit of approximately 3.015 effective connections per node is proposed for natural self-organizing systems.

Outlook:

  • Further research can explore the implications of power-law distributions for ecosystem resilience and function.
  • Investigating the precise boundaries and characteristics of the 'window of vitality' across different natural systems is warranted.
  • Understanding the connectivity limit may inform the design and management of artificial complex systems.