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Measuring Complexity in an Aquatic Ecosystem

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 232)

Abstract

We apply formal measures of emergence, self-organization, homeostasis, autopoiesis and complexity to an aquatic ecosystem; in particular to the physiochemical component of an Arctic lake. These measures are based on information theory. Variables with an homogeneous distribution have higher values of emergence, while variables with a more heterogeneous distribution have a higher self-organization. Variables with a high complexity reflect a balance between change (emergence) and regularity/order (self-organization). In addition, homeostasis values coincide with the variation of the winter and summer seasons. Autopoiesis values show a higher degree of independence of biological components over their environment. Our approach shows how the ecological dynamics can be described in terms of information.

Keywords

Complex Systems Information Theory Complexity Self-organization Emergence Homeostasis Autopoiesis 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Laboratorio de Hidroinformática, Facultad de Ciencias BásicasUnivesidad de PamplonaPamplonaColombia
  2. 2.Centro de Micro-electrónica y Sistemas DistribuidosUniversidad de los AndesMéridaVenezuela
  3. 3.Departamento de Ciencias de la Computación, Instituto de Investigaciones en Matemáticas Aplicadas y en SistemasUniversidad Nacional Autónoma de MéxicoMéxico CityMéxico
  4. 4.Centro de Ciencias de la ComplejidadUniversidad Nacional Autónoma de MéxicoMéxicoMéxico

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