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Trajectories toward maximum power and inequality in resource distribution networks
Natalie Davis1,2, Andrew Jarvis1, M J Aitkenhead2
1Lancaster Environment Centre, Lancaster University, Lancaster, United Kingdom.
Plos One
|March 11, 2020
Summary
Resource distribution networks can amplify inequality as they grow. This study models how spatial heterogeneity in networks increases power consumption inequality, highlighting implications for natural and human systems.
Area of Science:
- Ecological economics
- Network theory
- Spatial analysis
Background:
- Resource distribution networks are crucial for biotic and abiotic systems.
- Self-organization to maximize power production is a known principle, but its link to network development and spatial resource heterogeneity is unclear.
- Quantifying resource distribution heterogeneity is key to understanding inequality and niche emergence.
Purpose of the Study:
- To quantitatively analyze the relationship between network development, maximum power, and inequality.
- To introduce a theoretical framework for simulating power consumption and inequality in spatial resource distribution networks.
- To explore the outcomes of heterogeneous distribution in natural versus engineered networks.
Main Methods:
- Development of a theoretical framework for resource distribution networks.
- Simulation of power consumption and inequality in generalized, spatially explicit networks.
- Analysis of the impact of increasing resource flows and hierarchical branching on power consumption.
Main Results:
- Increasing resource flows in networks amplify inequality in power consumption at endpoints.
- Spatial heterogeneity in network architecture is a key driver of this amplified inequality.
- Both increased resource flow and hierarchical branching can increase power consumption.
Conclusions:
- Heterogeneous resource distribution in networks can lead to significant power consumption inequality.
- Findings raise questions about equity in human-engineered versus natural distribution systems.
- Prioritizing equitable distribution is crucial for human-engineered networks.
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