Storms are a dominant driver of variability in stream metabolism, yet comparing responses across events is challenging because disturbances differ widely in magnitude, duration, and recovery dynamics. We developed a disturbance–response framework that integrates resistance (impact magnitude) and resilience (recovery efficiency) to quantify whole-ecosystem metabolic stability during storm events. Storm impacts were calculated as cumulative departures of gross primary production (GPP) and ecosystem respiration (ER) from antecedent conditions and normalized by disturbance duration, and these components were combined into a unitless stability index (Ψ).
We applied this framework to >10 years of high-frequency dissolved oxygen data from East Fork Poplar Creek, Tennessee, focusing on the downstream monitoring station (efk5.4). A total of 1,560 storm events were delineated using the DMCA-ESR method, of which 115 groups met criteria for metabolic analysis and were classified as isolated or multi-storm (successional) disturbances. Preliminary results indicate that metabolic departures during multi-storm periods were comparable to or slightly greater than those during isolated storms. Instead, stability differences were driven by faster recovery. Median recovery factors increased by ~50% for GPP and ~10–15% for ER, resulting in ~20–30% higher overall stability (Ψ) during multi-storm periods. Across events, Ψ closely tracked recovery metrics rather than resistance, indicating that resilience dynamics, rather than reduced disturbance magnitude, primarily governed metabolic stability.
These results suggest that prior disturbances condition ecosystem responses to subsequent storms and demonstrate that recovery processes, rather than reduced disturbance magnitude, dominate whole-stream metabolic stability. This framework provides a process-based and transferable approach for comparing metabolic stability across heterogeneous hydrologic regimes.