English

Self-organized criticality in complex model ecosystems

Statistical Mechanics 2025-12-09 v1 Disordered Systems and Neural Networks Populations and Evolution

Abstract

We show that spatial extensions of many-species population dynamics models, such as the Lotka-Volterra model with random interactions we focus on in this work, generically exhibit scale-free correlation functions of population sizes in the limit of an infinite number of species. Using dynamical mean-field theory, we describe the many-species system in terms of single-species dynamics with demographic and environmental noises. We show that the single-species model features a random mass term, or equivalently a random space-time averaged growth rate, poising some species very close to extinction. This introduces a hierarchy of ever larger correlation times and lengths as the extinction threshold is approached. In turn, every species, even those far from extinction, are coupled to these near-critical fields which combine to make fluctuations of population sizes generically scale-free. We argue that these correlations are described by exponents derived from those of directed percolation in spatial dimension d=3d=3, but not in lower dimensions.

Keywords

Cite

@article{arxiv.2512.06961,
  title  = {Self-organized criticality in complex model ecosystems},
  author = {Thibaut Arnoulx de Pirey},
  journal= {arXiv preprint arXiv:2512.06961},
  year   = {2025}
}
R2 v1 2026-07-01T08:13:52.925Z