“Resilience,” like love, is difficult to define. Yet everyone – from United Nations Secretary-General Ban Ki-moon to government agencies, company boards, and community groups – is talking about how to build or maintain it. So, is resilience a useful concept or just a fleeting buzzword?
To answer that question, we need to start with a different one: How much do you think you can change without becoming a different person? How much can an ecosystem, city, or business change before it looks and functions like a different kind of ecosystem, city, or business?
All of these are self-organizing systems. Your body, for example, maintains a constant temperature of approximately 37 degrees Celsius. If your body temperature rises, you start to sweat in order to cool down; if your temperature falls, your muscles vibrate (shiver) to warm up. Your body relies on negative feedbacks to keep it functioning in the same way.
That is basically the definition of resilience: the capacity of a system to absorb disturbance, re-organize, and keep functioning in much the same way as before.
But there are limits, or thresholds, to a system’s resilience, beyond which it assumes a different way of functioning – a different identity. Many coral reefs that were once home to a rich diversity of fish, for example, have become algal or turf ecosystems with very few fish.
Two main thresholds dictate this change in coral reefs. The more nutrients that enter the water (run-off from nearby land), the more the algae are favored, until, at some point, they take over. Likewise, if too many herbivorous fish are removed, algae gain a competitive advantage over the corals. These two thresholds interact: the more nutrients there are, the less fishing is needed to “flip” the system into the algal state; and the fewer fish there are, the less nutrients are needed.
Moreover, thresholds can move as the environment changes. In the coral reef example, both the nutrient and fish thresholds fall as sea temperatures rise and the oceans become more acidic. So, as climate change proceeds, smaller incremental rises in nutrient levels and drops in fish stocks will flip coral reefs to algal states.
Thresholds also occur in social systems: think of fads or, more seriously, riot behavior in crowds. In business, the debt/income ratio is a well-known threshold, one that can move in step with exchange rates. Threshold effects have also been identified in labor supply, transport services, and other determinants of companies’ well-being.
Given the importance of threshold effects, how can a system’s resilience be maintained?
For starters, making a system very resilient in one way can cause it to lose resilience in other ways. So we have to understand and enhance general resilience – a system’s capacity to cope with a variety of shocks, in all aspects of its functioning. From research on a variety of systems, the following attributes have been shown to confer general resilience:
Comments· A high degree of diversity, especially response diversity (different ways of doing the same thing, often mistakenly thought of as “redundancy”).
· A relatively modular structure that does not over-connect its components.
· A strong capacity to respond quickly to change.
· Significant “openness,” allowing emigration and immigration of all components (closed systems remain static).
· Maintenance of adequate reserves – for example, seed banks in ecosystems or memory in social systems (which speaks against just-in-time supply services).
· Encouragement of innovation and creativity.
· High social capital, particularly trust, leadership, and social networks.
· Adaptive governance (flexible, distributive, and learning-based).
These attributes comprise the essentials of a resilient system. But resilience itself is neither “good” nor “bad.” Undesirable systems, such as dictatorships and saline landscapes, can be very resilient. In these cases, the system’s resilience should be reduced.
Moreover, it is impossible to understand or manage a system’s resilience at only one scale. At least three must be included – the focal scale and at least one below and one above – for cross-scale connections most often determine a system’s longer-term resilience. Most losses in resilience are unintended consequences of narrowly focused optimization (like an “efficiency” drive) that fails to recognize feedback effects on the focal scale that stem from changes produced by such optimization at another scale.
Resilience should not be confused with resistance to change. On the contrary, trying to prevent change and disturbance to a system reduces its resilience. A forest that never burns eventually loses species capable of withstanding fire. Children who are prevented from playing in dirt grow up with compromised immune systems. Building and maintaining resilience requires probing its boundaries.
If a shift into a “bad” state has already happened, or is inevitable and will be irreversible, the only option is transformation into a different kind of system – a new way of living (and making a living). Transformability and resilience are not opposites. In order for a system to remain resilient at one scale, parts of it at other scales may have to transform.
In Australia, for example, the Murray-Darling basin cannot continue as a resilient agricultural region if all parts of it continue doing what they are doing now. There simply is not enough water. So some parts of it will have to transform.
Of course, the need for transformation to create or maintain resilience may also affect the highest scale: If some countries and regions are to remain (or become) resilient social-ecological systems with high human well-being, it may be necessary to transform the global financial system.
Transformation requires getting past denial, creating options for change, and supporting novelty and experimentation. Financial support from higher levels (government) all too often takes the form of help not to change (bailouts of too-big-to-fail banks, for example), rather than help to change.
Resilience, in short, is largely about learning how to change in order not to be changed. Certainty is impossible. The point is to build systems that will be safe when they fail, not to try to build fail-safe systems.