Abstract
Ecosystems’ microbiome organization is the epitomic feature of ecosystem function and an incredibly fascinating system considering its complexity, ecology and evolution, and practical applications for individual and population health. Due to its ‘’unknowns’’ the microbiome also provides the opportunity to test and develop information theoretic models that mimic and predict its dynamics. A novel information and network theoretic model that predicts microbiome network organization, diversity, dynamics and stability for the human gut microbiome is presented. The model is able to classify health states based on microbiome entropic patterns, that, in the optimal biological function are related to neutral scale-free information organization of species interactions. The healthy state is characterized by an optimal metabolic function that is predicted by macroecological quintessential indicators whose variability is meaningful of state transitions. Information propagation analyses detect total species importance, proportional to outgoing information flow, which can be use for microbial engineering or disease diagnosis and etiognosis. Finally a link with ocean microbial ecosystems is highlighted as well as the collectivity-diversity-dynamics triality.