Measuring Complexity in an Aquatic Ecosystem


Abstract. We apply to aquatic ecosystem components, formal measures of emergence, self-organization, homeostasis, autopoiesis and complexity developed by the authors. These measures are based on information theory, created by Claude Shannon. In particular, they were applied to the physiochemical component of an aquatic ecosystem located in the Arctic Polar Circle. The results show that variables with a “homogeneous” distribution of its values in all states presented obtained higher values of emergence, while variables with a more “heterogeneous” value’s distribution had a higher self-organization. It is confirmed that variables having high complexity values reflect a balance between change (emergence) and regularity/order (self-organization). In addition, homeostasis values were coinciding with the variation of winter and summer season. Also, autopoiesis values confirmed a higher degree of independence of some components (physiochemical and biological) over others. This approach showed how the ecological dynamics can be described in terms of information.