The general meaning of resilience, derived from its Latin roots 'to jump or leap back', is the ability to recover from or adjust easily to misfortune or change.
In the Resilience Alliance we put more emphasis on the capacity to "get back" than to "bounce back". Our focus is social-ecological systems - linked systems of people and nature. It involves resilience at multiple scales, from the scale of a farm or village, through communities, regions, and nations to the globe. By "social-ecological system" we mean a multi-scale pattern of resource use around which humans have organized themselves in a particular social structure (distribution of people, resource management, consumption patterns, and associated norms and rules).
the ability to absorb disturbances, to be changed and then to re-organise and still have the same identity (retain the same basic structure and ways of functioning). It includes the ability to learn from the disturbance. A resilient system is forgiving of external shocks. As resilience declines the magnitude of a shock from which it cannot recover gets smaller and smaller. Resilience shifts attention from purely growth and efficiency to needed recovery and flexibility. Growth and efficiency alone can often lead ecological systems, businesses and societies into fragile rigidities, exposing them to turbulent transformation. Learning, recovery and flexibility open eyes to novelty and new worlds of opportunity.
The aim of resilience management and governance is...
either, to keep the system within a particular configuration of states (system 'regime') that will continue to deliver desired ecosystem goods and services (preventing the system from moving into an un-desirable regime from which it is either difficult or impossible to recover) or, to move from a less desirable to a more desirable regime.
The basic concepts underpinning a resilience approach to policy and management are: non-linearity, alternate regimes and thresholds; adaptive cycles; multiple scales and cross-scale effects - "panarchy"; adaptability; transformability; general versus specified resilience.
1. Non-linearity, alternate regimes and thresholds
Because of non-linear dynamics, many systems can exist in what are called alternate stable states. The term "states" is often used loosely and can be confusing, so we need to define it. The state of a system at any time is defined by the values (amounts) of the variables that constitute the system. For example, if a rangeland system is defined by the amounts of grass, shrubs and livestock, then the state space is the three-dimensional space of all possible combinations of the amounts of these three variables. The dynamics of the system are reflected as its movement through this space. The state of the rangeland system at any particular time is the amounts of grass, shrubs and livestock at that time. Using the metaphor of basins of attraction in a stability landscape (Walker et al 2004 -- and we stress that this is only a metaphor to help us visualize alternate system regimes), the SES can exist in one or more system configurations (Figure 1). Some configurations are desirable from a human perspective, and others are undesirable. Each configuration is actually a set of system states that has the same essential structure and function - and such a configuration (same structure and function) is termed a system "regime". As biophysical and social attributes of the system change, the positions of the attractors move around, and the various basins of attraction get smaller and larger, or appear and disappear.
Figure 1. A "ball-in-the-basin" representation of resilience. The state of this two dimensional system is the ball. Its dynamics cause it to move to the 'attractor' - the bottom of the basin. The system can change regimes either by the state changing, or through changes in the shape of the basin (ie, through changes in processes and system function), as shown in (b).
Alternate regimes are separated by thresholds that are marked by levels of controlling (often slowly changing) variables where there is a change in feedbacks. It is the changed feedbacks that lead to the changes in function and therefore structure.
We define resilience, formally, as the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure and feedbacks - and therefore the same identity.
2. Adaptive cycles
SESs, like all systems, are never static, and they tend to move through four, recurring phases, known as an adaptive cycle. Generally, the pattern of change is a sequence from a rapid growth phase through to a conservation phase in which resources are increasingly unavailable, locked up in existing structures, followed by a release phase that quickly moves into a phase of reorganisation, and thence into another growth phase. However, multiple possible transitions among the four phases are possible and the pattern may not reflect a cycle. The growth and conservation phases together constitute a relatively long developmental period with fairly predictable, constrained dynamics; the release and reorganisation phases constitute a rapid, chaotic period during which capitals (natural, human, social, built and financial) tend to be lost and novelty can succeed.
The original metaphor of the adaptive cycle (developed by Buzz Holling) portrayed it as a figure of 8 in two dimensions - increasing connectivity, and increasing capital (Figure 2).
Figure 2. The adaptive cycle - in two dimensions, capital and connectedness, depicted as a figure 8 pattern of dynamics.
Some people now prefer to use a simpler double loop metaphor, a more-or-less predictable and relatively long "foreloop" (the growth and conservation phases) and a rapid, chaotic "backloop" (the release and reorganisation phases) (Figure 3).
Figure 3. The adaptive cycle, as a simple loop, showing possible changes between phases.
3. Multiple scales and cross-scale effects - "Panarchy"
No system can be understood or managed by focusing on it at a single scale. All systems (and SESs especially) exist and function at multiple scales of space, time and social organization, and the interactions across scales are fundamentally important in determining the dynamics of the system at any particular focal scale. This interacting set of hierarchically structured scales has been termed a "panarchy" (Gunderson and Holling 2003). Figure 4 illustrates the original panarchy portrayal.
Figure 4. "Panarchy" - nested adaptive cycles, with influences between scales.
Adaptability is the capacity of a SES to manage resilience in relation to alternate regimes (sometimes called adaptive capacity). It involves either or both of two abilities:
i) The ability to determine the trajectory of the system state - the position within its current basin of attraction;
ii) The ability to alter the shape of the basins, that is move the positions of thresholds or make the system more or less resistant to perturbation.
The abilities to effect both of these are determined by a combination of attributes of both the social domain and the ecosystem.
In cases where a system is already in an undesirable regime and efforts to get it back into a desirable regime are no longer possible (or worse, make the undesirable basin larger), one option for resolving the predicament is transformation to a different kind of system - new variables, new ways of making a living, different scales - a different panarchy.
6. General vs. Specified resilience
We can think about "specified" resilience as the resilience "of what", "to what". This is what we are mostly concerned about - the resilience of some aspect of a system (its productivity, the species it contains, the livelihoods of people) to some defined shocks (a drought, a fire, a market shift). However, efforts to increase resilience of some aspect of a system regime to a specified set of disturbances can unwittingly reduce the resilience of other aspects of that system to other, non-specified (perhaps novel) disturbances.
There is therefore a need to balance the maintenance of general resilience while engaged in necessary efforts to enhance specified resilience to known threats and disturbances. It is a difficult issue to address.
Resilience assessment is about understanding which basin the system is in, where in that basin it is (in relation to the basin's boundaries), how to navigate (either to avoid going into an undesirable basin or to get from an undesirable to a desirable one), how to alter the stability landscape to make such navigation easier or more difficult, and how to transform to become a different kind of system when that is the only useful option left.
The influence of the states of the system (including where they are in their adaptive cycles) at scales above and below the focal scale influence resilience at the focal scale. From above, the effects can be positive (in the form of providing "memory" and "subsidies", but also negative (preventing actions, etc). From below, the hyper-coherence of system states or stages in the adaptive cycle can trigger a system collapse at the focal scale.