TY - CHAP T1 - Measuring Complexity in an Aquatic Ecosystem T2 - Advances in Computational Biology Y1 - 2014 A1 - Fernández, Nelson A1 - Gershenson, Carlos ED - Castillo, Luis F. ED - Cristancho, Marco ED - Isaza, Gustavo ED - Pinzón, Andrés ED - Corchado Rodríguez, Juan Manuel AB - 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. JF - Advances in Computational Biology T3 - Advances in Intelligent Systems and Computing PB - Springer VL - 232 UR - http://arxiv.org/abs/1305.5413 ER -