Microbial ecosystems consist of many interacting components that integrate through stochastic and highly dynamic processes across multiple scales. Yet, despite this complexity, microbial communities exhibit remarkably robust patterns and reproducible functions. This apparent paradox reflects the role of constraints, whether physical, physiological, or evolutionary, that channel stochasticity into structured outcomes. Due to the limited knowledge of the nature of these constraints, models in ecology have traditionally relied on stochastic exploration under minimal mechanistic assumptions. Now, advances in data availability and computational methods increasingly allow us to construct models that incorporate explicit mechanistic constraints. In this review, we synthesize emerging modeling approaches that explore the space of ecological possibility in microbial ecosystems under realistic constraints, such as those imposed by metabolic stoichiometry, thermodynamics, or the structure of ecological interaction networks. We argue that integrating such constraints can significantly improve the predictive resolution of models, helping us build a much needed bridge between theory and data. We further discuss how novel statistical approaches are revealing simple, low-dimensional patterns in microbial communities, offering empirical clues for identifying the underlying constraints. Together, these developments suggest a path toward a data-driven and mechanistically informed theory in microbial ecology.

Nitrous oxide (N₂O) is a potent greenhouse gas of primarily microbial origin. Oxic and anoxic emissions are commonly ascribed to autotrophic nitrification and heterotrophic denitrification, respectively. Beyond this established dichotomy, we quantitatively show that heterotrophic denitrification can significantly contribute to aerobic nitrogen turnover and N₂O emissions in complex microbiomes exposed to frequent oxic/anoxic transitions. Two planktonic, nitrification-inhibited enrichment cultures were established under continuous organic carbon and nitrate feeding, and cyclic oxygen availability. Over a third of the influent organic substrate was respired with nitrate as electron acceptor at high oxygen concentrations (>6.5 mg/L). N₂O accounted for up to one-quarter of the nitrate reduced under oxic conditions. The enriched microorganisms maintained a constitutive abundance of denitrifying enzymes due to the oxic/anoxic frequencies exceeding their protein turnover—a common scenario in natural and engineered ecosystems. The aerobic denitrification rates are ascribed primarily to the residual activity of anaerobically synthesised enzymes. From an ecological perspective, the selection of organisms capable of sustaining significant denitrifying activity during aeration shows their competitive advantage over other heterotrophs under varying oxygen availabilities. Ultimately, we propose that the contribution of heterotrophic denitrification to aerobic nitrogen turnover and N₂O emissions is currently underestimated in dynamic environments.

Nitrous oxide (N2O) is a potent greenhouse gas of primarily microbial origin. Aerobic and anoxic emissions are commonly ascribed to nitrification and denitrification, respectively. Beyond this established dichotomy, we quantitatively prove that heterotrophic denitrification can significantly contribute to aerobic nitrogen turnover and N2O emissions in complex microbiomes exposed to frequent oxic/anoxic transitions. Planktonic, nitrification-inhibited denitrifying enrichments respired over a third of the influent organic substrate with nitrate at high oxygen concentrations. N2O accounted for up to one quarter of the aerobically respired nitrate. The constitutive detection of all denitrification enzymes in both anoxic and oxic periods highlight the selective advantage offered by metabolic preparedness in dynamic environments. We posit that aerobic denitrification and associated N2O formation is currently underestimated in dynamic microbial ecosystems.