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Ecodynamics pp 164-180 | Cite as

On Quantifying the Effects of Formal and Final Causes in Ecosystem Development

  • R. E. Ulanowicz
  • A. J. Goldman
Conference paper
Part of the Research Reports in Physics book series (RESREPORTS)

Abstract

In physics and in traditional biology it has sufficed until now to describe phenomena as the results of purely material or efficient causes. However, a growing number of biologists and philosophers think that a satisfactory description of biological development must also include reference to what Aristotle labeled formal and final (or teleonomic, sensu Mayr) causation. A measure called the network ascendency has been defined to track the changes in the system that result from positive feedback acting as an endogenous formal cause of system development. In turn, positive feedback appears to exert a selection pressure reminiscent of teleonomic final cause upon each of its constituent elements.

Associating development with the increase of network ascendency permits the modelling of final cause using the powerful modern tools of mathematical optimization. Cheung and Goldman have developed an algorithm to find a reconfiguration of any given starting network that locally optimizes its network ascendency. Typically, the optimal configuration, as demonstrated by two simple examples, is a “one-tree“, that is, a single, directed cycle adjoined to a tree. Studying the differences between the observed and the optimal networks yields insights into the particular constraints acting on the system and reveals the most efficient pathways through the network.

Keywords

Positive Feedback Network Ascendency Optimal Configuration Average Mutual Information Ecosystem Development 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1988

Authors and Affiliations

  • R. E. Ulanowicz
    • 1
  • A. J. Goldman
    • 2
  1. 1.Chesapeake Biological LaboratoryUniversity of MarylandSolomonsUSA
  2. 2.Department of Mathematical SciencesThe Johns Hopkins UniversityBaltimoreUSA

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