Information Theory in Ecology

ROBERT E. ULANOWICZ (University of Maryland Chesapeake Biological Laboratory Solomons, MD 20688-0038)

Abstract for 1998 American Association for the Advancement of Science (AAAS) Annual Meeting and Science Innovation Exposition Philadelphia, Pennsylvania Monday, February 16, 1998, 3:00pm-6:00pm Track: Emerging Science: Transforming the Next Generation Session number: 101.0

Ecosytem dynamics (unlike mechanical behaviors encountered in ontogeny) appear to be causally open. Hence, deterministic mathematics are inadequate to treat the full gamut of ecological phenomena, and splicing unconditional probabilities onto continuous mathematics seems like a poor fix. A potentially fruitful way out of the conundrum has been provided by Karl Popper, who called for the development of a "calculus of conditional probabilities" to quantify open systems. Unfortunately, Popper gave no details regarding how such a calculus might be achieved. It happens, however, that when conditional probabilities are introduced into information theory, the resulting "mutual information" appears to satisfy Popper's desiderata. Furthermore, the index encapsulates as well several observed trends in ecosystem succession, thereby giving rise to a quantitative phenomenological description of how ecosystems develop. When this formulation is viewed against the background of irreversible thermodynamics, one recognizes in the phenomenological principle certain analogies to Newton's laws (in the same sense that Newton's second law provided Schroedinger with a starting point from which to develop the basic equations of quantum physics.) Information theory applied to ecological succession, it appears, could serve as a template for how to treat open systems in general and how to achieve Popper's truly "evolutionary theory of knowledge."


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