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Information, energy, and eco-exergy as indicators of ecosystem complexity

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  • Vihervaara, Petteri
  • Franzese, Pier Paolo
  • Buonocore, Elvira

Abstract

Human societies are dependent on a large set of ecosystem services (ES) generated by the diversity of life on Earth. It has been proposed that the negative impact of human societies on ecosystems could be reduced if the economic value of ES would be acknowledged. However, the evaluation of ES vital for human well-being using traditional economic models following market principles (based on the concept of scarcity and regarding ES as an intrinsic market structure) poses some limitations. Ecological Economics offers an alternative perspective based on the idea that human economy should not exceed the biophysical limits of the planet. Understanding the economic value of natural resources and ES may be effective to optimize the environmental performance at local scale. However, the sustainable use of natural resources is ultimately a question of understanding the value of the biosphere at different scales - from local to global - using multiple perspectives and criteria. This paper proposes alternative ways of understanding the real significance and value of biodiversity and its links to the generation of ES based on thermodynamics and information theory. In particular, the use of two indicators of ecosystem complexity reflecting the potential for ES delivery is suggested: information (e.g., genetic diversity) and eco-exergy (e.g., the chemical energy stored in organic matter and the genetic information embodied in biomass of living organisms).

Suggested Citation

  • Vihervaara, Petteri & Franzese, Pier Paolo & Buonocore, Elvira, 2019. "Information, energy, and eco-exergy as indicators of ecosystem complexity," Ecological Modelling, Elsevier, vol. 395(C), pages 23-27.
    • Handle: RePEc:eee:ecomod:v:395:y:2019:i:c:p:23-27
    DOI: 10.1016/j.ecolmodel.2019.01.010
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    References listed on IDEAS

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    4. Vassallo, P. & Paoli, C. & Buonocore, E. & Franzese, P.P. & Russo, G.F. & Povero, P., 2017. "Assessing the value of natural capital in marine protected areas: A biophysical and trophodynamic environmental accounting model," Ecological Modelling, Elsevier, vol. 355(C), pages 12-17.
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    3. Sayadzadeh, Mohammad Esmaiel & Samani, Majid Riahi & Toghraie, Davood & Emami, Sobhan & Eftekhari, Seyed Ali, 2023. "Numerical study on pollutant emissions characteristics and chemical and physical exergy analysis in Mild combustion," Energy, Elsevier, vol. 278(PB).
    4. Buonocore, Elvira & Appolloni, Luca & Russo, Giovanni F. & Franzese, Pier Paolo, 2020. "Assessing natural capital value in marine ecosystems through an environmental accounting model: A case study in Southern Italy," Ecological Modelling, Elsevier, vol. 419(C).
    5. Grande, U. & Piernik, A. & Nienartowicz, A. & Buonocore, E. & Franzese, P.P., 2023. "Measuring natural capital value and ecological complexity of lake ecosystems," Ecological Modelling, Elsevier, vol. 482(C).
    6. Buonocore, Elvira & Donnarumma, Luigia & Appolloni, Luca & Miccio, Antonino & Russo, Giovanni F. & Franzese, Pier Paolo, 2020. "Marine natural capital and ecosystem services: An environmental accounting model," Ecological Modelling, Elsevier, vol. 424(C).

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