Structured and random interactions interplay in complex ecosystems dynamics

Minimal models for complex ecosystems often assume random interactions, whose statistics suffice to predict dynamical and macroecological patterns. However, interaction networks commonly possess large-scale structures, such as hierarchies or functional groups. Here, we ask how conclusions from random interaction models are altered by the presence of such large-scale network structures. We consider a simple superposition of structured and random interactions in a classic population dynamics model, and study macroscopic observables, abundance distributions and dynamical regimes. Randomness and structure combine in a surprisingly yet deceptively straightforward way: contributions from each component to the patterns are largely independent, and yet their interplay has non-trivial consequences, notably out of equilibrium. We conclude that whether interaction structure matters depends on the pattern: conclusions from randomly interacting models are less robust when considering static patterns of species presence and abundance, and more robust in the dynamical nature of their ecological regimes.