The adaptive process needs three ingredients: 1) options, 2) decision and 3) implementation (Norberg et al 2008). Failure in either of these will disrupt the adaptive process.

Some example for options are:

• alternative management strategies
• institutional or
• organizational arrangements

Some options are incompatible and require a binary choice or replacement, while other combinations are complementary. With options comes uncertainties in their potential outcomes. Some are well tested, in other regions or in past time, while others are novel and rely on imagination and understanding of the the current system.

The decision process is a complex social and cognitive process involving aspects of knowledge about expected benefits, uncertainties and power relations. Governance often deals with putting the right people in the right place for providing knowledge and making decisions. Stakeholder participation is one governance tool for bringing different or multiple types of knowledge to the table to improve decisions, but also can play an important role in dealing with inequity in power relations by ensuring the weaker actors have a voice. Furthermore, stakeholder participation is generally a good way to prepare for the implementation phase by creating a sense of shared responsibility for the changes made.

Remember any options or decision are only as good as the possibility to implement the change and the compliance of affected actors. Non-compliance is, for example, affected by legitimity of authority, perceived justice and economic status. Thus, power relations and conflicts between user groups plays a fundamental role for successful implementation.

Exploitation vs. Exploration

This fundamental tradeoff comes from the fact that known and established solutions are well known, with lower relative uncertainty than untested solutions. Furthermore, transaction costs of change provide an inherent threshold for change in any organization. Thus, the cost of change, as well as the uncertainty in perceived benefit of change provides incentives for “exploiting” the already established system.

Exploration, on the other hand, can hold promise of better benefits or solutions to current conflicts but with greater uncertainty. Exploitation also involves experimentation; that is, processes of testing, evaluating, refining, and reapplying new forms of governance, institutional configurations, policies, and practices; within a given policy area. Such processes of trial-and-error are highly useful for coping with changing circumstances under high uncertainty but are also likely to be costly. In practical settings, the explorative capacity of a given community is reflected in the quality of its educational system and informational infrastructures, such as the existence of independent universities, research institutes, and “think tanks,” as well as arenas for public debate, science-policy dialogues and unbiased mass media. Exploration also entails having sufficient resources, such as physical, monetary, and human capital.

Learning processes, experimentation, and information gathering are often costly, and the capacity for exploration might therefore be limited by insufficient resources.

Stakeholder participation, for example, entails a large transaction cost and uncertainty in outcomes. Force and hierarchy, third-party enforcement (G. Hardin 1968), generalized trust, network structures, (Putnam, Leonardi, and Nanetti 1993), institutional trust (Levi 1997; Rothstein and Stolle 2003), norms of reciprocity (Ostrom and Walker 2003), perceptions, beliefs, taboos (R. Hardin 2002), and the creation of institutional rules (Ostrom 2005) are all examples of mechanisms that can be called upon to ensure cooperation among actors in a governance system, as well as for keeping transaction costs on an acceptable level. Consequently, the strength of these mechanisms also determines the governance system’s capacity for exploitation.

Adaptive Management

Adaptive management is a form of environmental management that is predicated on the assumption that ecosystems are complex, self-organized, dynamic systems (Holling 1978, Walters 1986). Such systems (ecosystems or social ecological systems) are characterized by: a) large number of interacting variables and components, b) non-linear relationships among the components, and c) cross-scale interactions. The consequence of these characteristics is that great uncertainties limit tractability, analysis and predictability of outcomes, and system behaviors exceed the bounds of rational expectations. Rather than ignore or assume away such uncertainties, adaptive management was developed to confront complexity by posing questions or hypotheses to address uncertainty, then using management actions to evaluate these unknowns in order to learn about the complexities of system dynamics, as well as to achieve intended social objectives (Holling 1978, Walters 1986, Lee 1993).

Assessing a system requires synthesizing available data to generate a set of competing alternative explanations about particular sets of resource problems and social objectives. Management actions are designed by considering what actions are robust to uncertainties among alternative explanations and what actions will help test and winnow those uncertainties (Walters 1986). Management actions are evaluated by monitoring system indicators in a process that uses that information to promote learning.

While these activities are described linearly, adaptive management is typically an iterative process that develops an ongoing dialogue about the functioning of the system and the goals of management. In sum, adaptive management consists of two activities; an assessment phase, which engages scientists, managers and stakeholders to build integrative models that develop a set of hypotheses to evaluate. The second activity is to design, conduct and evaluate experiments that test the collective understanding of system dynamics and evaluate interventions and policy implementation.

At least four key volumes have proposed the ideas, provided methods, and reported on results of applications of adaptive management over the past four decades. These include Adaptive Environmental Assessment and Management (Holling 1978); Adaptive Management of Renewable Resources (Walters 1986) Compass and Gyroscope (Lee 1993) and Barriers and Bridges to the Renewal of Ecosystems and Institutions (Gunderson, Holling and Light 1995). Holling (1978) and Walters (1986) describe the use of computer models during the assessment phase of the process. These models are not used to predict the effects of policy actions on ecosystems, but rather as devices to clarify management objectives, highlight and winnow alternative explanations or hypotheses regarding resolution of resource issues. A suite of models are generally developed, each covering distinct spatial and temporal scales and are used as games to explore and reflect on understanding. Moreover, the models are used to develop policies that are structured as experiments to probe the identified uncertainties. Lee (1993) and Gunderson et al. (1995) describe how adaptive management has been attempted in large-scale resource systems. Lee (1993) focuses on social, political and institutional constraints on experimentation in the Columbia River Basin. The Gunderson, Holling and Light (1995) volume compares similar patterns of change in managed resource systems. The pattern is such that management that stabilizes key ecological processes (populations, water flows) inevitably leads to a type of crises (ecological, economic or social). Following a crisis, informal groups collaborate, to resolve the crisis by developing an integrated understanding (often an adaptive assessment). Finally, such assessments lead to transient learning processes that result in a reorganization of the management institutions and society, with new goals and policies in place.

Adaptive Governance

Adaptive governance is a form of environmental governance or the management and governing of natural resources. Some authors argue that it involves the management of complex social-ecological interactions characterized by high degrees of uncertainty (Dietz, Ostrom, & Stern, 2003). Folke et al. (2005) describe this form of governance as necessary for the management of complex ecosystems, particularly when change is “abrupt, disorganizing, or turbulent. Brunner et al. (2005), provide a rich set of examples to illustrate the emergence of adaptive governance as a way of solving problems created by top-down control of decision making and attempts at implementation of singular scientific and technical solutions that are bereft of political considerations. They (op cit), describe adaptive governance as operating in a situation where the science is contextual, knowledge is incomplete, multiple ways of knowing and understanding are present, policy is implemented to deal with modest steps and unintended consequences and decision making are both top-down (although fragmented) and bottom-up. As such, adaptive governance is aimed at integrating science, policy and decision-making in systems that assume and manage for change, rather than against change. Moreover, adaptive governance attempts to overcome obstacles to the implementation of adaptive management.

References

DUIT, A. and GALAZ, V. (2008), Governance and Complexity—Emerging Issues for Governance Theory. Governance, 21: 311–335.

Norberg, J., & Wilson, J. (2008). Diversity and resilience of social-ecological systems. Complexity Theory for a sustainable future. Columbia university press

Gunderson, L., C.S. Holling, and S.S. Light, editors. 1995. Barriers & Bridges for the Renewal of Ecosystems and Institutions. Columbia University Press, New York.

Holling, C. S. 1978. Adaptive environment assessment and management. John Wiley, Lee, K. N. 1993. Compass and Gyroscope. Island Press, Washington, D.C.

Walters, C. J. 1986. Adaptive Management of Renewable Resources. McGraw Hill, New York.

Brunner, R. D., Steelman, T. A., Coe-Juell, L., Cromley, C. M., Edwards, C. M., & Tucker, D. W. (2005). Adaptive governance: Integrating science, policy, and decision making. New York: Columbia University Press.

Dietz, T., Ostrom, E., & Stern, P. C. (2003). The struggle to govern the commons. Science, 302, 1907-1912.

Folke, C., Hahn, T., Olsson, P., & Norberg, J. (2005). Adaptive governance of social-ecological systems. Annual Review of Environment and Resources, 30, 441-473.

contributors

Lance Gundersson, Jon Norberg