Howard Odum’s “Self-organization, transformity and information”: Three decades of empirical evidence
•The Biosphere´s energy quality hierarchy is shown with the use of empirical data.•The results confirm linear, log-log, inverse relation between energy quality and energy quantity.•The hypothesis of Howard T. Odum in 1988 was supported by additional empirical data. The Biosphere is self-organized in...
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Published in | Ecological modelling Vol. 407; p. 108717 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.09.2019
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Subjects | |
Online Access | Get full text |
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Summary: | •The Biosphere´s energy quality hierarchy is shown with the use of empirical data.•The results confirm linear, log-log, inverse relation between energy quality and energy quantity.•The hypothesis of Howard T. Odum in 1988 was supported by additional empirical data.
The Biosphere is self-organized into a hierarchy of energy transformations. More dilute forms of energy (e.g. solar energy) are concentrated in biological structures and through socioeconomic transformation processes forming energy outputs that are able to perform higher quality work. To assess the hierarchy level of different forms of energy in the Biosphere, over 30 years Howard T. Odum introduced the concept of “transformity”, i.e., the amount of available energy of the same kind (usually solar energy) needed to obtain a specific output of available energy of another kind. Transformities represent energy quality and have been calculated for a broad set of energy forms and products, both natural and anthropic. In this paper, we report on this broad literature illustrating how the energy quality hierarchy of the biosphere works. This study leads to the definition of lower and higher energy quality thresholds supporting H.T. Odum’s initial hypothesis of an inverse linear logarithmic relationship between energy quality and quantity. A model is proposed to obtain transformities from data on energy flows. |
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ISSN: | 0304-3800 1872-7026 |
DOI: | 10.1016/j.ecolmodel.2019.06.005 |