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Resilience Practice

Building Capacity to Absorb Disturbance and Maintain Function

ISLAND PRESS

Preparing for Practice:

The Essence of Resilience Thinking

There are any number of ways of putting resilience science into practice, and it needs to be said at the outset that following strict recipes and prescriptions simply isn't appropriate. Working with resilience requires you to constantly reflect on what you're doing and why you're doing it. And once an assessment of resilience is done, you are encouraged to go back and reexamine it, expand on it, and then adapt accordingly. Our focus in most of this book is on the resilience of social-ecological systems (linked systems of humans and nature). Resilience is a dynamic property of such a system, and managing for it requires a dynamic and adaptive approach.

This being said, the activities undertaken as part of resilience practice can be grouped into three broad steps: describing the system, assessing its resilience, and managing its resilience. In this book we'll provide a variety of ways you can undertake these steps, but the ultimate aim is that you devise your own approach.

While resilience science is not new, attempts to apply it in real-world situations have only recently started taking shape. Workshops of all sizes and flavors have been held around the world on various aspects of resilience practice, and one clear lesson is emerging from this experience. People seeking to undertake resilience assessments or work with resilience need to be in a "resilience frame of mind" to begin with. In other words, it's unlikely they'll engage with resilience practice if they haven't some idea of what resilience is about.

That's not a major hurdle. People with a bit of life experience and some responsibility for managing a system (e.g., a farm, a catchment, a business, or a national park) are usually very quick in picking up on resilience thinking. These systems are self-organizing systems, and people working with them have been attempting to understand them in their day-to-day work. Resilience thinking provides a useful framework for a deeper engagement on why these systems behave as they do.

A simple overview of resilience science is provided in our earlier book, Resilience Thinking, but there are also many other resources available at the website of the Resilience Alliance (www.resalliance.org). This is a group of organizations and individuals involved in interlinked aspects of ecological, social, and economic research. It is the network that has created and developed the framework of "resilience thinking."

Resilience and Identity

The word resilience is now common in many vision and mission statements. But ask the people who use these statements what they think it means, and you get a range of different answers, most of which relate to how something or someone copes with a shock or a disturbance.

Concepts of resilience are used in all sorts of disciplines, but the term has four main origins—psychosocial, ecological, disaster relief (and military), and engineering. We discuss these in chapter 5, but it's helpful to consider them briefly in this introduction.

Psychologists have long recognized marked differences in the resilience of individuals confronted with traumatic and disastrous circumstances. Considerable research has gone into trying to understand how individuals and societies can gain and lose resilience.

Ecologists have tended to describe resilience in two ways: one focused on the speed of return following a disturbance, the other focused on whether or not the system can recover.

People engaging with resilience from the perspective of disaster relief or in a military arena incorporate both aspects (i.e., speed and ability to recover). Indeed, there is a lot of commonality in the understanding of resilience in the three areas of psychology, ecology, and disaster relief.

In engineering the take on resilience is somewhat different. In fact, engineers more commonly use the term robustness with a connotation of "designed resilience." It differs from the other three uses in that it assumes bounded uncertainty—that is, the kinds and ranges of disturbances and shocks are known, and the system being built is designed to be robust in the face of these shocks. This view is now changing, and in chapter 5 we look at the emergence of what is being dubbed a "metarobustness" approach. This sees a convergence of ideas about resilience as used in the other three domains.

In this book we present a definition and description of resilience that is being used commonly by scientists in many areas of inquiry. It is the capacity of a system to absorb disturbance and reorganize so as to retain essentially the same function, structure, and feedbacks—to have the same identity. Put more simply, resilience is the ability to cope with shocks and keep functioning in much the same kind of way.

A key word in this definition is identity. It emerged independently in ecological and psychosocial studies, and it is both important and useful because it imparts the idea that people, societies, ecosystems, and social-ecological systems can all exhibit quite a lot of variation, be subjected to disturbance and cope, without changing their "identity"—without becoming something else.

The following pages seek to present a simple overview of the essence of resilience thinking. If you can appreciate the following ten key points, you're in a good position to consider how you can move from thinking to practice.

1. The systems we are dealing with are self-organizing.

2. There are limits to a system's self-organizing capacity.

3. These systems have linked social, economic, and biophysical domains.

4. Self-organizing systems move through adaptive cycles.

5. Linked adaptive cycles function across multiple scales.

6. There are three related dimensions to resilience: specified resilience, general resilience, and transformability.

7. Working with resilience involves both adapting and transforming.

8. Maintaining or building resilience comes at a cost.

9. Resilience is not about knowing everything.

10. Resilience is not about not changing.

1. Self-Organizing Systems

First and foremost, resilience thinking requires that you recognize and appreciate that the systems we depend upon are complex adaptive systems. We use the more general term self-organizing systems because most people seem to grasp that more readily. Box 1 explains what the terms mean and the difference between being complex and being complicated.

All the things that most resource managers are interested in (e.g., farms, landscapes, and fishing grounds), but also things like your body, your family, and your business, are self-organizing systems. You can change bits of the system, but the system will then self-organize around this change. Other bits will change in response to your control. Sometimes you have a good idea about how the system will respond to your actions, sometimes it's difficult to predict, and sometimes the response comes as a complete surprise.

Most of the time the system can handle the changes it experiences, be they human management or some external disturbance such as a storm. By "handling it" we mean the system absorbs the disturbance, reorganizes, and keeps performing in the way it did—it retains its identity.

But sometimes the system can't cope with the change and begins behaving in some other (often undesirable) way. Sometimes a fishery crashes and doesn't come back when fishing pressure is removed. Sometimes an agricultural catchment becomes salinized as the water table rises and is no longer productive, even if the water table later drops. Even with the best intentions, our management sometimes turns our most precious ecosystems from valuable assets to expensive liabilities.

This often happens because our traditional approach to managing resources, which usually focuses on narrowly optimizing for some product (e.g., fish or timber or grain), fails to acknowledge the limits to predictability inherent in a self-organizing system. Don't worry if that sounds too technical; it makes sense when you work through a few of the concepts embedded in it.

2. Thresholds

There are limits to how much a self-organizing system can be changed and still recover. Beyond those limits it functions differently because some critical feedback process has changed. These limits are known as thresholds. When a self-organizing system crosses a threshold, it is said to have crossed into another "regime" of the system (also called a "stability domain" or "basin of attraction"). It now behaves in a different way—it has a different identity.

On coral reefs, for example, there is a threshold associated with nutrient levels. Plant nutrients find their way to coral reefs from fertilizers being used on the land. The nutrients wash off the land, eventually finding their way to waters around coral reefs. Nutrients stimulate the growth of algae. When the concentration of nutrients rises above a certain level, algae outcompete coral polyps for bare spaces on the reef. There is a critical level of nutrient concentration where this feedback effect on algae-coral competition takes place, and this is a threshold.

Below the nutrient-load threshold, corals predominate and coral polyps rapidly occupy any bare spaces created by disturbances. But if the reef crosses the nutrient threshold, algal growth overwhelms the young corals. It might be a storm that creates the bare space, but suddenly the system is behaving in a dramatically different way. It goes from a coral system to an algae system—it has a new identity; this change has major consequences for all the other organisms (including people) that depend on that reef.

In self-organizing systems you need to put the emphasis on thresholds because crossing them can come with huge consequences. Resilience practice is very much about thresholds—understanding them, determining where they might lie and what determines this, appreciating how you might deal with them, and very importantly, having the capacity to be able to deal with them.

Thresholds occur in ecosystems and in social systems. In social systems they are more often referred to as "tipping points." Tipping points might be changes in fashion, voting patterns, riot behavior, or markets.

Thresholds are often not easy to identify. Most variables in a system don't even have them; that is, considered on their own, the variables show a simple linear response to the change in underlying controlling variables and at no point exhibit a dramatic change in behavior (see figure 1a). For the variables that do have thresholds, it's important to know about them because they cause regime shifts. This means that once a threshold has been crossed, all the variables in the system are likely to undergo significant change. But, as we'll discuss, discovering where thresholds might lie is not easy.

And not all thresholds are the same. Sometimes you can cross a threshold but cross right back relatively easily. Water changes to ice when it crosses a temperature threshold of zero degrees Celsius, but it changes back to water when you raise the temperature above the threshold.

Sometimes there's a large step change when you cross a threshold, and then a similar large reverse change is experienced when you cross back, at the same point (see figure 1b). A common example of this is when some landscapes lose more than about 90 percent of their cover of native vegetation. Below this threshold there is a loss of a suite of native animal species from the landscape. However, provided they haven't been lost entirely from the whole region, restoring the landscape to more than 10 percent cover allows for their reestablishment (Radford et al. 2005).

Sometimes crossing a threshold involves a hysteretic effect. This is where the threshold you need to cross in order to return to the regime you've left is different from the threshold you crossed when you moved out of that regime in the first place. A couple of examples help to explain what we mean by this.

Many lake systems "flip" into a different regime when they get too much of the plant nutrient phosphorus (P). A small increase in P levels in the lake sediment pushes the system over a threshold, and it begins to behave very differently. Due to changes in P solubility under changing oxygen concentrations in the water, the amount of P in the water jumps much higher (it's very soluble under anaerobic conditions) and won't come down until P in the sediment is much lower. Algal growth is stimulated, and the lake goes from clear water to a regime of algal blooms and dead fish. This is shown in figure 1c.

Grassy rangelands that sometimes turn into shrub thickets offer another example. If grazing pressure reduces the amount of grass and causes shrub density to exceed some threshold amount, there then isn't enough grass to carry a fire. Fire kills many shrub species but not grass (which grows back from buds in its crowns below the soil surface). Without fire, the woody shrubs take over as the dominant vegetation. This further suppresses grass growth. The feedback from grass to shrubs via fire has changed, and even if grazing pressure is then reduced, the system stays in the woody shrub-dominated state for a very long time before shrubs die and the grass returns in sufficient amounts to allow fire to again play a role. And that delay might be enough to bankrupt the pastoralist. We look at rangelands in more detail in case study 1.

Sometimes this hysteretic effect is described as a "lag effect" because returning involves a delay. The word hysteresis comes from the Greek husteros, which means "late." However, it's more than just a delay. The pathway back is different from the pathway that took you over the threshold in the first place. Unless you dramatically reduce phosphorus levels in the lake or shrub levels on the rangelands, you don't return at all. In other words, it's not a matter of how much time passes (i.e., it's not a lag); it is a matter of the amount of the controlling variable. The hysteretic effect results in a system having two alternate stable states (or regimes) for the same amount of the controlling variable.

The lake and rangelands systems are able to return to their original states if the controlling variables (e.g., nutrient loads, shrub cover) are reduced to much lower levels than those that led to the change. For some systems, however, crossing thresholds represents a one-way trip. When saline groundwater reaches the surface of an agricultural landscape, it's effectively game over. The saline water will devastate crops and trees, but worse still, it will change the structure of the soil. Sodium disperses clay particles, making the soil "soapy" and sticky, greatly reducing water infiltration into the soil. This happens to such an extent that the salt will remain in the surface layers for a long time after the water table sinks (figure 1d). It will take large quantities of water to flush the salt out.

Not only are thresholds critical to understanding the behavior of self-organizing systems, they are the basic limits to your enterprise. To use the phrase in a recent analysis of global-scale thresholds (Rockström et al. 2009), they define the "safe operating space" of your system.

Thresholds Can Move

So, for a number of reasons, thresholds are difficult things to deal with: they come in different forms and they're often difficult to spot (that is, until you've crossed them, and then it can be too late).

As if that weren't enough, some thresholds can move because of other changes in the system. This means that resilience (the distance your system is away from a threshold) can increase or decrease. For all thresholds, including those that are fixed (the two-meter water table salinity threshold in figure 1d is an example), you need to know what determines their positions in order to manage resilience. The ones that can move are the hardest to analyze.

For example, consider the nutrient-load threshold in connection to coral reefs. The position of this threshold depends on how many herbivorous fish there are. Above a certain nutrient load, algal growth is favored over coral growth, so if any little shock opens up some space, algae occupy it, displacing coral. In places like the Caribbean, high levels of fishing pressure have removed fish groups that graze down algae, and in these situations the nutrient threshold that triggers a flip from a coral-dominated reef to an algae-dominated reef is lower than in places where lots of grazing fish are present (as on the Great Barrier Reef in Australia). As the fish that control algae disappear, the nutrient threshold allowing algae to take over gets lower and lower and is more likely to be crossed (resilience is diminished).

So, to recap, thresholds come in different forms, are often invisible, and can move. They can occur along biophysical variables like nutrients and plant cover, but they also exist in the social and economic domains of your system.

3. Domains Are Linked

Many of the problems associated with managing natural resources relate to the fact that our approaches don't acknowledge that we're dealing with systems that have linkages between the social, economic, and biophysical domains that make them up. Fisheries, for example, are often based on models of how many fish can be harvested over time, but the models focus only on our understanding of the biophysical domain—the dynamics of the fish population under various levels of harvesting—and quotas are set accordingly.

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Excerpted from Resilience Practice by Brian Walker, David Salt. Copyright © 2012 Brian Walker David Salt. Excerpted by permission of ISLAND PRESS.
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