Title | Measuring Complexity in an Aquatic Ecosystem |
Publication Type | Book Chapter |
Year of Publication | 2014 |
Authors | Fernández, N, Gershenson, C |
Editor | Castillo, LF, Cristancho, M, Isaza, G, Pinzón, A, Rodríguez, JManuel Cor |
Book Title | Advances in Computational Biology |
Series Title | Advances in Intelligent Systems and Computing |
Volume | 232 |
Pagination | 83-89 |
Publisher | Springer |
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. |
URL | http://arxiv.org/abs/1305.5413 |
DOI | 10.1007/978-3-319-01568-2_12 |