The 'ecological resilience' is defined as the capacity of a system to undergo disturbance and reorganize so as to still maintain essentially the same functions, structures, and controls by not moving in a different region of the state space controlled by a diverse set of mutually reinforcing processes (i.e., shift to a different domain of attraction; Figure 1). The state to which the system recovers, through the back loop of the a-phase of the adaptive cycle, is unlikely to be an exact replica of what existed before; it nevertheless contains the same basic elements and supports the same key processes, so that the system's identity is safeguarded.
Addressing resilience in the context of the analysis of SESs prompts to (1) measure the amount of change that a system can absorb at certain scales and for specific source of disturbances; (2) evaluate the degree to which the system is capable of self-organization; and (3) appraise the system ability to build and increase the capacity for learning, adaptation, and novelty. According to these points, attention should shift to determine the constructive role of instability (i.e., disturbance regimes and perturbations) in maintaining diversity and persistence of components and processes, as well as to management designs (i.e., policies, laws or management plans) that maintain or nurse systems' functions in the face of unexpected disturbances.
Natural and social systems are inherently resilient but their capacity to cope with disturbance and uncertainty can be degraded as well as enhanced. Diversity and redundancy of functions (e.g., trophic status and functional groups) and components (e.g., species and cultural diversity) at the same and across a range of spatial and temporal scales are key elements for enhancing resilience. System simplification, spatial and temporal heterogeneity reduction, and weakening of across-scale interactions are symptoms of loss of resilience.
Changes from one set of processes to another are usually triggered either by the action of slowly changing drivers (e.g., climate, agricultural land-use intensification, shifts in human values and policies) that force the system over a threshold, or by relatively discrete shocks to the system (e.g., natural disasters or institutions collapse). Direct and precise measurement of resilience is difficult as it requires to estimate the potential of system drivers and disturbance regimes to move a system across thresholds and boundaries separating alternative domains (Figure 1). As experimental manipulation of a natural system or an SES may be unfeasible because of system dimensions or costs, or impossible as it could lead to irreversible state, or unethical as an undesirable highly resilient domain could be reached, resilience can be addressed by a retrospective description of system evolution once an analysis framework is identified by specifying the set of spatiotemporal scales and types of disturbances of interests. The analysis of the system history can lead to gain in an insight into present-day resilience status and support the modeling process of system dynamics to estimate and forecast future resilience for pressing environmental concerns.
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