Ecosystems represent archetypal complex dynamical systems, often modelled by coupled
differential equations of the form dxidt= xi ϕ i (x 1,…, x N), where N represents the number of …

Complex system stability can be studied via linear stability analysis using random matrix
theory (RMT) or via feasibility (requiring positive equilibrium abundances). Both approaches …

This paper is divided into two parts. The first part is devoted to the study of a class of
Approximate Message Passing (AMP) algorithms which are widely used in the fields of …

Ecosystems with a large number of species are often modelled as Lotka–Volterra dynamical
systems built around a large interaction matrix with random part. Under some known …

Abstract The Lotka-Volterra (LV) model is a simple, robust, and versatile model used to
describe large interacting systems such as food webs or microbiomes. The model consists of …

Approximate Message Passing (AMP) algorithmshave recently gathered significant attention
across disciplines such as statistical physics, machine learning, and communication …

The notions of intraspecific competition and population self-regulation play a central role in
ecological theory, leading to foundational concepts such as limiting similarity and niche …

Abstract The multivariable Lokta-Volterra dynamic model has been widely used to describe
interacting and competing populations and has found applications in biology, ecology …

The diversity of species and the complexity of their interactions represent a huge challenge
in theoretical ecology. The system's complexity requires mathematical modelisation. The …

Evolution is an inherently stochastic process comprised of many randomly occurring events.
The evolutionary fate of a population depends largely on its underlying ecological …