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Concerns regarding the proposal for an ecological equation of state: an assessment starting from the organic biophysics of ecosystems (OBEC)

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  • Riera, Rodrigo
  • Fath, Brian D.
  • Herrera, Ada M.
  • Rodríguez, Ricardo A.

Abstract

The goal of testing the theoretical fruitfulness and empirical utility of the links between ecology and thermodynamics has been elusive. This could explain the breakdown of ecology into multiple branches, some of them intended to develop models in agreement with the principles of physics. The maximum entropy algorithm (MaxEnt) is one of the most frequently mentioned topics in this field. Within the MaxEnt framework, a quantitative relationship between various ecological parameters has recently been proposed as a seeming ecological equation of state (EESH; Harte et al. 2022. An equation of state unifies diversity, productivity, abundance and biomass. Commun. Biol. 5: 874). We analyze the EESH from the interdisciplinary perspective of Organic Biophysics of Ecosystems (OBEC). Consistent with this analysis, the EESH neglects the analytical similarity between key ecological variables and statistical mechanical variables, it does not include any intensive variable useful to determine the distance of ecological systems from equilibrium, it does not involve any constant useful to define the statistical range within which the system can be considered out of danger despite widespread effects of anthropogenic impact, and its general structure bears no resemblance to previous equations of state because it is based on a subjective approach devoid of physical content that is only useful as a tool for statistical inference. So, our conclusions are: (i) the EESH does not withstand comparison with prior knowledge and empirical evidence from both ecology and physics, and (ii) it cannot be considered an ecological equation of state.

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  • Riera, Rodrigo & Fath, Brian D. & Herrera, Ada M. & Rodríguez, Ricardo A., 2023. "Concerns regarding the proposal for an ecological equation of state: an assessment starting from the organic biophysics of ecosystems (OBEC)," Ecological Modelling, Elsevier, vol. 484(C).
    • Handle: RePEc:eee:ecomod:v:484:y:2023:i:c:s0304380023001916
    DOI: 10.1016/j.ecolmodel.2023.110462
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    1. Amos Golan & John Harte, 2022. "Information theory: A foundation for complexity science," Decision Analysis, INFORMS, vol. 119(33), pages 2119089119-, August.
    2. Rodríguez, Ricardo A. & Herrera, Ada Mª & Delgado, Juan D. & Otto, Rüdiger & Quirós, Ángel & Santander, Jacobo & Miranda, Jezahel V. & Fernández, María J. & Jiménez-Rodríguez, Antonia & Riera, Rodrigo, 2013. "Biomass-dispersal trade-off and the functional meaning of species diversity," Ecological Modelling, Elsevier, vol. 261, pages 8-18.
    3. Rodríguez, Ricardo A. & Herrera, Ada M. & Riera, Rodrigo & Santander, Jacobo & Miranda, Jezahel V. & Quirós, Ángel & Fernández-Rodríguez, María J. & Fernández-Palacios, José M. & Otto, Rüdiger & Escud, 2015. "Distribution of species diversity values: A link between classical and quantum mechanics in ecology," Ecological Modelling, Elsevier, vol. 313(C), pages 162-180.
    4. Rodríguez, Ricardo A. & Herrera, Ada Ma. & Santander, Jacobo & Miranda, Jezahel V. & Fernández-Rodríguez, María J. & Quirós, Ángel & Riera, Rodrigo & Fernández-Palacios, José Mª. & Otto, Rüdiger & Esc, 2015. "Uncertainty principle in niche assessment: A solution to the dilemma redundancy vs. competitive exclusion, and some analytical consequences," Ecological Modelling, Elsevier, vol. 316(C), pages 87-110.
    5. Rodríguez, Ricardo A. & Herrera, Ada M. & Otto, Rüdiger & Delgado, Juan D. & Fernández-Palacios, José M. & Arévalo, José R., 2012. "Ecological state equation," Ecological Modelling, Elsevier, vol. 224(1), pages 18-24.
    6. Rodríguez, Ricardo A. & Herrera, Ada Ma. & Riera, Rodrigo & Delgado, Juan D. & Quirós, Ángel & Perdomo, María E. & Santander, Jacobo & Miranda, Jezahel V. & Fernández-Rodríguez, María J. & Jiménez-Rod, 2015. "Thermostatistical distribution of a trophic energy proxy with analytical consequences for evolutionary ecology, species coexistence and the maximum entropy formalism," Ecological Modelling, Elsevier, vol. 296(C), pages 24-35.
    7. Amos Golan & John Harte, 2022. "Information theory: A foundation for complexity science," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(33), pages 2119089119-, August.
    8. Rodríguez, Ricardo A. & Duncan, Janelle M. & Delgado, Juan D. & Vanni, Michael J. & Riera, Rodrigo & Herrera, Ada M. & González, María J., 2017. "Assessment of ecosystem trophodynamic power: A model based on the power equation for an oscillating string," Ecological Modelling, Elsevier, vol. 362(C), pages 80-86.
    9. Ian W. Renner & David I. Warton, 2013. "Equivalence of MAXENT and Poisson Point Process Models for Species Distribution Modeling in Ecology," Biometrics, The International Biometric Society, vol. 69(1), pages 274-281, March.
    10. Tiezzi, Enzo & Pulselli, Riccardo Maria, 2008. "An entropic approach to living systems," Ecological Modelling, Elsevier, vol. 216(2), pages 229-231.
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