Trait-based frameworks, notably Grime's competitor–stress-tolerant–ruderal theory, offer a powerful lens for predicting how environmental fluctuations govern community structure. Yet, classical ecological models assume environments combining extreme stress and intense disturbance are non-viable for sustained colonisation, leaving a critical bottleneck in our ability to predict how microbial systems withstand compounded operational pressures. This gap severely hinders the predictive management of engineered microbiomes critical for global waste-to-energy conversion. Here we extend the application of classic ecological frameworks by demonstrating that anaerobic digester microbiomes deploy distinct, predictable life-history strategies across a 182-day compounded gradient of biomass turnover and organic loading. High-intensity single-event disturbances drive severe volatile fatty acid accumulation (propionate reaching 2,955 mg L⁻¹), selectively shifting the microbiome toward stress-tolerant and stress-tolerant–ruderal strategies. Traits associated with ribosome function, molecular chaperones, and enzymatic reactive oxygen species detoxification were particularly enriched under highly disturbed conditions. Conversely, intermediate regimes were associated with ruderal strategies that prioritise rapid growth over resource-uptake efficiency, dropping total chemical oxygen demand removal to 41%. Cross-system comparisons encompassing anaerobic digestion, activated sludge, and soil ecosystems, revealed both universal and context-dependent ecological traits. Survival-associated traits linked to cell maintenance and repair, protective mechanisms, and cell motility were universally associated with stress-tolerant or ruderal strategies across ecosystems, whereas nutrient transport and metabolic traits exhibited greater context dependency. These insights establish a gene-resolved framework that reconciles microbial trait selection with ecological theory, providing a roadmap to engineer microbiome resilience against process failures.