Measuring Complexity in an Aquatic Ecosystem

TitleMeasuring Complexity in an Aquatic Ecosystem
Publication TypeBook Chapter
Year of Publication2014
AuthorsFernández, N, Gershenson, C
EditorCastillo, LF, Cristancho, M, Isaza, G, Pinzón, A, Rodríguez, JManuel Cor
Book TitleAdvances in Computational Biology
Series TitleAdvances in Intelligent Systems and Computing

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.