In recent times, the remarkable biodiversity characterizing natural ecosystems has gathered
interest not only among ecologists but also theoretical physicists and mathematicians.
Accurately quantifying the interactions within a species-rich ecosystem poses significant
challenges, necessitating the use of advanced inference methods and Random Matrix
Theory.
In this talk, I will discuss timely questions in theoretical ecology by focusing on the
Generalized Lotka-Volterra (GLV) model, which incorporates random interactions among
species and demographic fluctuations [1, 2]. I will unveil a rich and, eventually, hierarchical
structure of the emerging equilibria and relate the slowdown of correlation functions to aging
and glass-like features.
Then, I will provide a proof of concept on how this framework can qualitatively capture the
complexity of the gut microbiota. This will be illustrated by metagenomic data of healthy and
unhealthy patients, suffering from Crohn’s disease. The different physiological states of the
human gut microbiome will be shown to correspond to different noise-driven and disorder-
driven regimes within the GLV model [3]. Finally, I will briefly discuss the effect of spatial
dependence through a metacommunity scenario. Depending on the interplay between the
dispersal rate and demographic fluctuations, unexpected discontinuous phase transitions
can be pinpointed [4].
[1] A. Altieri, F. Roy, C. Cammarota, G. Biroli, Phys. Rev. Lett. 126 (2021)
[2] G. Garcia Lorenzana, A. Altieri, Phys. Rev. E 105 (2022)
[3] J. Pasqualini, E. V. Savarino, A. Maritan, A. Altieri; S. Suweis, to be submitted to
PNAS
[4] G. Garcia Lorenzana, A. Altieri*, G. Biroli*, PRX Life (2024) — in press.
Luca Leuzzi