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Co-evolution of network structure and consumer inequality in a spatially explicit model of energetic resource acquisition

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  • Davis, Natalie
  • Jarvis, Andrew
  • Polhill, J. Gareth

Abstract

Energetic resources in ecological and social–ecological systems are distributed through complex networks, which co-evolve with the system and consumers to move resources from points of origin to those of end use. Past research has focused on effects of spatiotemporal resource heterogeneity in ecosystems and society, or socioeconomic drivers of inequality, with less attention to interactions between resource network structure and population-level outcomes. Here, we develop a spatially explicit, stock-flow consistent agent-based model of generic consumers building and crossing links between resources, and we explore the co-evolution of the emergent network structure and inequality in consumers’ resource reserves across three distinct landscapes. We show that the consumer inequality initially decreased during network expansion, then increased rapidly as the network reached a more stable state. The spatial distribution of resources in each of the three landscapes constrained the structures that could emerge, and therefore the specific rates and timings of these dynamics. This work demonstrates the use of energetically consistent modelling to understand possible relationships among a spatially distributed set of resources, the network structure that connects them to a population, and inequality in that population. This can provide a theoretical underpinning informing further work to better understand causes of resource inequality and heterogeneity in observed systems.

Suggested Citation

  • Davis, Natalie & Jarvis, Andrew & Polhill, J. Gareth, 2022. "Co-evolution of network structure and consumer inequality in a spatially explicit model of energetic resource acquisition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
  • Handle: RePEc:eee:phsmap:v:608:y:2022:i:p1:s0378437122008196
    DOI: 10.1016/j.physa.2022.128261
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    References listed on IDEAS

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    1. Miller, Matt L. & Ringelman, Kevin M. & Eadie, John M. & Schank, Jeffrey C., 2017. "Time to fly: A comparison of marginal value theorem approximations in an agent-based model of foraging waterfowl," Ecological Modelling, Elsevier, vol. 351(C), pages 77-86.
    2. Guus ten Broeke & George van Voorn & Arend Ligtenberg, 2016. "Which Sensitivity Analysis Method Should I Use for My Agent-Based Model?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(1), pages 1-5.
    3. George Van Voorn & Geerten Hengeveld & Jan Verhagen, 2020. "An agent based model representation to assess resilience and efficiency of food supply chains," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-27, November.
    4. Adrian Dragulescu & Victor M. Yakovenko, 2000. "Statistical mechanics of money," Papers cond-mat/0001432, arXiv.org, revised Aug 2000.
    5. Fichera, Alberto & Pluchino, Alessandro & Volpe, Rosaria, 2018. "A multi-layer agent-based model for the analysis of energy distribution networks in urban areas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 710-725.
    6. Iris Lorscheid & Bernd-Oliver Heine & Matthias Meyer, 2012. "Opening the ‘black box’ of simulations: increased transparency and effective communication through the systematic design of experiments," Computational and Mathematical Organization Theory, Springer, vol. 18(1), pages 22-62, March.
    7. Michael A. Long & Lara Gonçalves & Paul B. Stretesky & Margaret Anne Defeyter, 2020. "Food Insecurity in Advanced Capitalist Nations: A Review," Sustainability, MDPI, vol. 12(9), pages 1-19, May.
    8. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
    9. Little, L.R. & McDonald, A.D., 2007. "Simulations of agents in social networks harvesting a resource," Ecological Modelling, Elsevier, vol. 204(3), pages 379-386.
    10. Beltran, Roxanne S. & Testa, J. Ward & Burns, Jennifer M., 2017. "An agent-based bioenergetics model for predicting impacts of environmental change on a top marine predator, the Weddell seal," Ecological Modelling, Elsevier, vol. 351(C), pages 36-50.
    11. Amie Gaye, 2007. "Access to Energy and Human Development," Human Development Occasional Papers (1992-2007) HDOCPA-2007-25, Human Development Report Office (HDRO), United Nations Development Programme (UNDP).
    12. Sun, Ye & Chen, Yu, 2018. "On the mechanism of phase transitions in a minimal agent-based macroeconomic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 613-624.
    13. Hannon, Bruce, 1994. "Sense of place: geographic discounting by people, animals and plants," Ecological Economics, Elsevier, vol. 10(2), pages 157-174, July.
    14. Nauta, Johannes & Simoens, Pieter & Khaluf, Yara, 2022. "Group size and resource fractality drive multimodal search strategies: A quantitative analysis on group foraging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    15. Yongfan Wang & Marc W. Cadotte & Yuxin Chen & Lauchlan H. Fraser & Yuhua Zhang & Fengmin Huang & Shan Luo & Nayun Shi & Michel Loreau, 2019. "Global evidence of positive biodiversity effects on spatial ecosystem stability in natural grasslands," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
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