Time-varying ecological interactions characterise equilibrium and stability

TL;DR

This study introduces a time-varying network model to analyze how species interactions in ecological communities change over time with environmental fluctuations, revealing diverse dynamic patterns across ecosystems.

Contribution

The paper develops a novel time-varying ecological network model using a generalized Lotka-Volterra framework to quantify interaction rewiring and stability over time.

Findings

Interaction networks show significant rewiring with environmental stress in high-resolution datasets.

Networks with coarse temporal data tend to maintain constant interaction structures.

Environmental context influences the balance between cooperation and competition in ecosystems.

Abstract

Ecological communities are composed of species interactions that respond to environmental fluctuations. Despite increasing evidence of temporal variation in these interactions, most theoretical frameworks remain rooted in static assumptions. Here, we develop and apply a time-varying network model to five long-term ecological datasets spanning diverse taxa and environments. Using a generalized Lotka-Volterra framework with environmental covariates, we quantify temporal rewiring of interspecific interactions, asymmetry patterns, and structural stability. Our results reveal contrasting dynamics across ecosystems: in datasets with rich temporal resolution, interaction networks exhibit marked rewiring and shifts in cooperation-competition ratios that correlate with environmental stress, consistent, though not always linearly, with the stress-gradient hypothesis. Conversely, in datasets with coarser temporal sampling, networks retain constant interaction sign structure and remain in cooperation-dominated regimes. These findings highlight the importance of temporal resolution and environmental context in shaping ecological coexistence.