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. © Springer International Publishing Switzerland 2014.
CITATION STYLE
Fernández, N., & Gershenson, C. (2014). Measuring complexity in an aquatic ecosystem. In Advances in Intelligent Systems and Computing (Vol. 232, pp. 83–89). Springer Verlag. https://doi.org/10.1007/978-3-319-01568-2_12
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