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Mapping a path to functionality in ecological communities: understanding Ecological Network Coherence
Alexandre Fuster Calvo, Dominique Caron, Francis Banville, François Massol, Gracielle Teixeira Higineo, Guillaume Blanchet, Katherine Hébert, Laura Pollock, Luigi Maiorano, Pablo Silva, Paulo Guimaraes, Wilfried Thuiller, Dominique Gravel
Ecological interactions are central to how ecosystems function and respond to environmental change, yet integrating these dynamics into applied biodiversity indicators remains in its infancy. While data limitations are often cited as the primary obstacle, we argue that the lack of clear, theoretically derived expectations for how interacting species respond to environmental change is a more pressing challenge. To address this, we introduce the concept of Ecological Network Coherence (ENC), which quantifies the degree of shared or divergent responses to the environment between interacting species, and link these patterns to ecosystem functioning. Through mathematical formulations and simulations, we demonstrate how ENC patterns—such as distributions with stronger correlations—can disrupt community stability and functioning. Applying this framework to natural systems, we show how ENC patterns derived from time series and SDMs might provide insights into ecosystem vulnerability. These results highlight how ENC, built from empirical data, can inform theoretical models to explore the consequences of coherence on ecosystem functioning. By providing a common framework that bridges the gap between empiricists and theoreticians, ENC offers a pathway to improve statistical inference in large, sparse interaction networks, link environmental co-responses to interaction dynamics, and establish a baseline for a global, scalable indicator of ecosystem change and potential collapse.
