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A quantitative engineering study of ecosystem robustness using thermodynamic power cycles as case studies.


ABSTRACT: Human networks and engineered systems are traditionally designed to maximize efficiency. Ecosystems on the other hand, achieve long-term robustness and sustainability by maintaining a unique balance between pathway efficiency and redundancy, measured in terms of the number of flow pathways available for a given unit of flow at any node in the network. Translating this flow-based ecosystem robustness into an engineering context supports the creation of new robust and sustainable design guidelines for engineered systems. Thermodynamic cycles provide good examples of human systems where simple and clearly defined modifications can be made to increase efficiency. Twenty-three variations on the Brayton and Rankine cycles are used to understand the relationship between design decisions that maximize a system's efficient use of energy (measured by thermodynamic first law efficiency) and ecological measures of robustness and structural efficiency. The results reveal that thermodynamic efficiency and ecological pathway efficiency do not always correlate and that while on average modifications to increase energy efficiency reduce the robustness of the system, the engineering understanding of ecological network design presented here can enable decisions that are able to increase both energy efficiency and robustness.

SUBMITTER: Panyam V 

PROVIDER: S-EPMC6938333 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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A quantitative engineering study of ecosystem robustness using thermodynamic power cycles as case studies.

Panyam Varuneswara V   Layton Astrid A  

PloS one 20191231 12


Human networks and engineered systems are traditionally designed to maximize efficiency. Ecosystems on the other hand, achieve long-term robustness and sustainability by maintaining a unique balance between pathway efficiency and redundancy, measured in terms of the number of flow pathways available for a given unit of flow at any node in the network. Translating this flow-based ecosystem robustness into an engineering context supports the creation of new robust and sustainable design guidelines  ...[more]

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