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Understanding how species coexist within ecological communities is a fundamental question in ecology. Traditionally, the focus has been on individuals as the biological units driving interactions within a community. These interactions, in turn, are shaped by the properties of species, creating a dynamic interplay. The abiotic environment also plays a crucial role, acting as a conditioning space that further influences the structuring of the community. While various modeling frameworks have been employed to study ecological communities, none have been able to simultaneously address the challenges of handling large-scale systems, providing detailed interaction mechanisms, and facilitating meaningful model comparisons at the analytical level, i.e. beyond simulation outcomes.

In this talk, we propose a paradigm shift by introducing the language of reaction networks, a concept native to systems biology. Unlike existing frameworks, reaction networks consider both species and abiotic environment as equally important components, with the focus shifting from specific species interactions to more general processes governing the persistence of the entire community. We demonstrate how this novel approach, particularly within the framework of Chemical Organization Theory (COT), offers a powerful analytical toolset to investigate the relationship between ecological system structure and stability. By computationally identifying closed and self-maintaining sub-collections of species, known as organizations, COT unveils groups of species that can coexist over the long-term. The set of organizations encompasses all potential stable regimes in the ecological system dynamics, and can be used to formalize a "multidimensional" view of the concept of resilience in ecology.

Furthermore, we illustrate some other mathematical properties that reveal interesting connections between ecology, logic and computation, showcasing the potential of COT to introduce innovative mathematical tools for ecological modeling.