Approximate message passing for block-structured ecological systems

TL;DR

This paper develops a theoretical framework using approximate message passing to analyze the equilibrium properties of block-structured ecological networks, revealing how interaction patterns influence community stability and persistence.

Contribution

It introduces a set of fixed-point equations for large, block-structured ecological systems with correlated interactions, providing explicit equilibrium abundance distributions.

Findings

Local correlation changes affect global species persistence.

Community structure impacts robustness to inter-community coupling.

Asymmetric variance alone can induce feedback loops.

Abstract

Ecological interaction networks are rarely homogeneous: species naturally form communities with distinct interaction structures, resulting in block-structured variance and correlation profiles in the interaction matrix. We study the equilibrium properties of generalized Lotka-Volterra systems whose interaction matrices are random and non-symmetric with variance and correlation profiles. Based on recent advances in approximate message passing (AMP) for heterogeneous and correlated random matrices, we derive a set of self-consistent fixed-point equations that, in the large-$n$ limit, characterize the equilibrium abundance distribution. In particular, we show that this limiting distribution is an explicit mixture of truncated Gaussian, driven by the variance and correlation profiles. We then illustrate the ecological implications of this result through three applications involving two interacting communities. First, we show that local changes in the correlation profile within a single community induce system-wide responses in species persistence, revealing the non-local nature of persistence dynamics. Second, we find that communities dominated by mutualistic or competitive interactions are more robust to increasing inter-community coupling, whereas communities structured by predator-prey interactions are more prone to collapse. Third, we demonstrate that asymmetric interaction variance alone, in the complete absence of correlation, can generate feedback loop between communities.