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Incorporating Heterogeneous Interactions for Ecological Biodiversity

Published 23 Mar 2024 in physics.bio-ph and cond-mat.stat-mech | (2403.15730v1)

Abstract: Understanding the behaviors of ecological systems is challenging given their multi-faceted complexity. To proceed, theoretical models such as Lotka-Volterra dynamics with random interactions have been investigated by the dynamical mean-field theory to provide insights into underlying principles such as how biodiversity and stability depend on the randomness in interaction strength. Yet the fully-connected structure assumed in these previous studies is not realistic as revealed by a vast amount of empirical data. We derive a generic formula for the abundance distribution under an arbitrary distribution of degree, the number of interacting neighbors, which leads to degree-dependent abundance patterns of species. Notably, in contrast to the well-mixed system, the number of surviving species can be reduced as the community becomes cooperative in heterogeneous interaction structures. Our study, therefore, demonstrates that properly taking into account heterogeneity in the interspecific interaction structure is indispensable to understanding the diversity in large ecosystems, and our general theoretical framework can apply to a much wider range of interacting many-body systems.

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References (28)
  1. H.-K. Janssen, Z. Phys. B 23, 377 (1976).
  2. C. De Dominicis and L. Peliti, Phys. Rev. B 18, 353 (1978).
  3. U. C. Täuber, Critical Dynamics: A Field Theory Approach to Equilibrium and Non-Equilibrium Scaling Behavior (Cambridge University Press, Cambridge, United Kingdom, 2014).
  4. A. Crisanti and H. Sompolinsky, Phys. Rev. E 98, 062120 (2018).
  5. M. Helias and D. Dahem, Statistical Field Theory for Neural Networks (Springer, Cham, Switzerland, 2022).
  6. T. Galla and Y.-C. Zhang, J. Stat. Mech. 2009, P11012 (2009).
  7. J. W. Baron, Phys. Rev. E 104, 044309 (2021).
  8. M. Opper and S. Diederich, Phys. Rev. Lett. 69, 1616 (1992).
  9. H. Sompolinsky and A. Zippelius, Phys. Rev. Lett. 47, 359 (1981).
  10. M. Tikhonov and R. Monasson, Phys. Rev. Lett. 118, 048103 (2017).
  11. S.-G. Yang and H. J. Park, arXiv preprint arXiv:2305.12341  (2023).
  12. T. Galla, Europhys. Lett. 123, 48004 (2018).
  13. G. Bunin, Phys. Rev. E 95, 042414 (2017).
  14. R. M. May, Nature (London) 238, 413 (1972).
  15. S. Allesina and S. Tang, Nature (London) 483, 205 (2012).
  16. P. R. Guimarães Jr., Annu. Rev. Ecol. Evol. Syst. 51, 433 (2020).
  17. J. M. Montoya and R. V. Solé, J. Theor. Bio. 214, 405 (2002).
  18. M. E. J. Newman, Networks (Oxford University Press, Oxford, United Kingdom, 2018).
  19. R. Albert and A.-L. Barabási, Rev. Mod. Phys. 74, 47 (2002).
  20. R. Pastor-Satorras and A. Vespignani, Phys. Rev. E 63, 066117 (2001).
  21. F. Iglói and L. Turban, Phys. Rev. E 66, 036140 (2002).
  22. C. Castellano and R. Pastor-Satorras, Phys. Rev. Lett. 105, 218701 (2010).
  23. D.-S. Lee, Phys. Rev. E 72, 026208 (2005).
  24. P. Erdős and A. Rényi, Publ. Math. Debrecen 6, 290 (1959).
  25. E. N. Gilbert, Ann. Math. Stat. 30, 1141 (1959).
  26. M. E. J. Newman, Phys. Rev. Lett. 89, 208701 (2002).
  27. J. Park and M. E. J. Newman, Phys. Rev. E 70, 066117 (2004).
  28. See Supplemental Materials at [URL].
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