The concepts of resistance, recovery, and resilience are in diverse fields from behavioral psychology to planetary ecology. These “three Rs” describe some of the most important properties allowing complex systems to survive in dynamic environments. However, in many fields—including ecology—our ability to predict resistance, recovery and resilience remains limited. Here, we propose new disturbance terminology and describe a unifying definition of resistance, recovery, and resilience. We distinguish functional disturbances that affect short-term ecosystem processes from structural disturbances that alter the state factors of ecosystem development. We define resilience as the combination of resistance and recovery—i.e., the ability of a system to maintain its state by withstanding disturbance or rapidly recovering from it. In the Anthropocene, humans have become dominant drivers of many ecosystem processes and nearly all the state factors influencing ecosystem development. Consequently, the resilience of an individual ecological parameter is not an inherent attribute but a function of linkages with other biological, chemical, physical, and especially social parameters. Because every ecosystem experiences multiple, overlapping disturbances, a multidimensional resilience approach is needed that considers both ecosystem structure (configuration of linkages) and disturbance regime. We explore these concepts with a few case studies and recommend analytical tools and community-based approaches to strengthen ecosystem resilience. Disregarding cultural and social dimensions of disturbance regimes and ecosystem structures leads to undesirable outcomes, particularly in our current context of intensifying socioecological crises. Consequently, cultivating reciprocal relationships with natural disturbance regimes and ecosystem structures is crucial to Earth stewardship in the Anthropocene.

Catchment-scale response functions, such as transit time distribution (TTD) and evapotranspiration time distribution (ETTD), are considered fundamental descriptors of a catchment’s hydrologic and ecohydrologic responses to spatially and temporally varying precipitation inputs. Yet, estimating these functions is challenging, especially in headwater catchments where data collection is complicated by rugged terrain, or in semi-arid or sub-humid areas where precipitation is infrequent. Hence, we developed practical approaches for estimating both TTD and ETTD from commonly available tracer flux data in hydrologic inflows and outflows without requiring continuous observations. Using the weighted wavelet spectral analysis method of Kirchner and Neal [2013] for δ18O in precipitation and stream water, we specifically calculated TTDs that contribute to streamflow via spatially and temporally variable flow paths in a sub-humid mountain headwater catchment in Arizona, USA. Our results indicate that composite TTDs most accurately represented this system for periods up to approximately one month and that a Gamma TTD was most appropriate thereafter. The TTD results also suggested that some contribution of subsurface water was beyond the applicable tracer range. For ETTD and using δ18O as a tracer in precipitation and xylem waters, a Gamma ETTD type best matched the observations, and stable water isotopes were capable tracers for the majority of vegetation source waters. This study contributes to a better understanding of a fundamental question in mountain catchment hydrology; namely, how tracer input fluxes are modulated by spatially and temporally varying subsurface flow paths that support evapotranspiration and streamflow at multiple time scales.