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PART I
Understanding Resilience: Theory, Metaphors, and Frameworks
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1
Resilience of Large-Scale Resource Systems
Lance H. Gunderson, C. S. Holling, Lowell Pritchard Jr., and Garry D. Peterson
Regional-scale systems of people and nature provide some of the most vexing challenges for attaining social goals of sustainability, biological conservation, or economic development. There are many more examples of failures than successes, as measured by numerous resource systems that exist in a constant or recurring state of crisis (Ludwig et al. 1993). In the Florida Everglades, agricultural interests, environmentalists, and urban residents contest with one another for control over clean water (Light et al. 1995). In the Pacific Northwest region of the United States, various advocates of salmon argue over the appropriate use of the Columbia River with those who prefer cheap hydroelectric power (Lee 1993; Volkman and McConnaha 1993). The nations surrounding the Baltic Sea struggle with issues of governance as the fish populations and water quality of the sea declines (Jansson and Velner 1995). Within Zimbabwe, large-scale land use conversions are testing stabilities of both ecological and political structures. In these cases resource management has taken a pathological form in which the complexity of the issues, institutional inertia, and uncertainty lead to a state of institutional gridlock, when inaction causes ecological issues to be ignored and existing policies and relationships to be continued.
Paradoxically, this failure often arises from the success of initial management actions. Managers of natural resource systems are often successful at rapidly achieving a set of narrowly defined goals. Unfortunately, this success encourages people to build up a dependence upon its continuation while simultaneously eroding away the ecological support that it requires. This leads to a state in which ecological change is increasingly undesirable to the people dependent upon the natural resource and simultaneously more difficult to avoid. This management pathology leads to unwanted changes in nature, a loss of ecological resilience, conservative management policies, and loss of trust in management agencies.
Recent work reveals a way out of this pathology in large, regional-scale systems. These systems move through periods of surprise, crisis, and reformation (Gunderson et al. 1995). Managers are surprised when the inadequacies of many, if not most, management policies are revealed by ecosystem dynamics. A crisis occurs when it is becomes unambiguously clear that existing policies caused this surprise. The crisis is followed by periods of denial, resistance, and often, finally, by a period of reformation during which new policies are developed and implemented. It is during these periods of crisis that institutions and the connections between them are most open to dramatic transformation. This ability to transform and survive requires that the resource system have sufficient resilience to permit the experimental development of new management policies.
What Is Resilience?
Resilience has been defined in two different ways in the ecological literature, each reflecting different aspects of stability. One definition focuses on efficiency and depends on constancy and predictabilityâall attributes of engineersâ desire for fail-safe design. The other focuses on persistence, despite change and unpredictabilityâall attributes embraced and celebrated by evolutionary biologists and by resource managers who search for safe-fail designs. Holling (1973) first emphasized these contrasting aspects of stability to draw attention to the tensions between efficiency and persistence, between constancy and change, and between predictability and unpredictability.
The more common definition, which we term engineering resilience (Holling 1996), conceives ecological systems to exist close to a stable steady state. Engineering resilience, then, is the speed of return to the steady state following a perturbation (Pimm 1984; OâNeill et al. 1986; Tilman and Downing 1994). This idea of disturbance away from and return to a stable state is also at the center of twentieth-century economic theory (Varian 1992; Kamien and Schwartz 1991).
The second definition, which we term ecological resilience (Walker et al. 1981; Holling 1996), emphasizes conditions far from any stable steady state, where instabilities can shift or flip a system into another regime of behaviorâin other words, to another stability domain (Holling 1973). In this case, resilience is measured by the magnitude of disturbance that can be absorbed before the system is restructured with different controlling variables and processes.
The differences between these two aspects of stabilityâessentially between a focus on maintaining efficiency of function (engineering resilience) and a focus on maintaining existence of function (ecological resilience)âare so fundamental that they can become alternative paradigms in which subscribers dwell on received wisdom rather than the reality of nature. Those using the concept of engineering resilience tend to explore system behavior near a known stable state, while those examining ecological resilience tend to search for alternative stable states and the properties of the boundaries between states.
Those who explore engineering resilience and the near-equilibrium behavior of ecosystems operate in the primarily deductive tradition of mathematical theory (e.g., Pimm 1984) that imagines simplified, untouched ecological systems; or they draw upon the traditions of engineering, which are motivated by the need to design systems with a single operating objective (Waide and Webster 1976; DeAngelis 1980; OâNeill et al. 1986). These approaches simplify the mathematics and accommodate the engineerâs drive to develop optimal designs. However, there is an implicit assumption that ecosystems exhibit only one equilibrium steady state or, if other operating states exist, that those states should be avoided (figure 1.1).
On the other hand, those who emphasize ecological resilience come from traditions of applied mathematics and applied resource ecology at the scale of ecosystemsâfor example, of the dynamics and management of freshwater systems (Fiering 1982), of forests (Holling et al. 1977), of fisheries (Walters 1986), of semi-arid grasslands (Walker et al. 1981) and of interacting populations in nature (Sinclair et al. 1990; Dublin et al. 1990). Because these researchers are rooted in inductive rather than deductive theory formation, and because they have experience with the impacts of large-scale management actions, they believe that it is the variability of critical variables that forms and maintains the stability landscape. When this variability is reduced, an ecosystem can flip from one organization to another (figure 1.1).
Figure 1.1. Stability landscapes can be used to represent the dynamics of a system and alternative definitions of resilience. The ball represents the system âstate.â The state can be changed by disturbances, which move the system along a stability landscape. The shape of the landscape is determined by controlling variables of the system. Engineering resilience (speed of recovery) is a local measure and is determined by the slope of the landscape. (a) Depressions in the landscape with low slopes have less engineering resilience than areas that have steep slopes. (b) Ecological resilience of a system corresponds to the width of a stability basin.
In economics, there has also been a focus on single stable state. The history of economics has been to rapidly move from establishing the existence of a general equilibrium to examining issues of equilibrium uniqueness, stability, and comparative statics. If multiple equilibria are shown to theoretically exist, then the challenge is to theoretically reduce the salience of alternate stable states by proposing that expectations, norms, and social institutions make some equilibria un...
