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date: 22 November 2017

Adaptive Governance

Summary and Keywords

Adaptive governance is defined by a focus on decentralized decision-making structures and procedurally rational policy, supported by intensive natural and social science. Decentralized decision-making structures allow a large, complex problem like global climate change to be factored into many smaller problems, each more tractable for policy and scientific purposes. Many smaller problems can be addressed separately and concurrently by smaller communities. Procedurally rational policy in each community is an adaptation to profound uncertainties, inherent in complex systems and cognitive constraints, that limit predictability. Hence planning to meet projected targets and timetables is secondary to continuing appraisal of incremental steps toward long-term goals: What has and hasn’t worked compared to a historical baseline, and why? Each step in such trial-and-error processes depends on politics to balance, if not integrate, the interests of multiple participants to advance their common interest—the point of governance in a free society. Intensive science recognizes that each community is unique because the interests, interactions, and environmental responses of its participants are multiple and coevolve. Hence, inquiry focuses on case studies of particular contexts considered comprehensively and in some detail.

Varieties of adaptive governance emerged in response to the limitations of scientific management, the dominant pattern of governance in the 20th century. In scientific management, central authorities sought technically rational policies supported by predictive science to rise above politics and thereby realize policy goals more efficiently from the top down. This approach was manifest in the framing of climate change as an “irreducibly global” problem in the years around 1990. The Intergovernmental Panel on Climate Change (IPCC) was established to assess science for the Conference of the Parties (COP) to the U.N. Framework Convention on Climate Change (UNFCCC). The parties negotiated the Kyoto Protocol that attempted to prescribe legally binding targets and timetables for national reductions in greenhouse gas emissions. But progress under the protocol fell far short of realizing the ultimate objective in Article 1 of the UNFCCC, “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference in the climate system.” As concentrations continued to increase, the COP recognized the limitations of this approach in Copenhagen in 2009 and authorized nationally determined contributions to greenhouse gas reductions in the Paris Agreement in 2015.

Adaptive governance is a promising but underutilized approach to advancing common interests in response to climate impacts. The interests affected by climate, and their relative priorities, differ from one community to the next, but typically they include protecting life and limb, property and prosperity, other human artifacts, and ecosystem services, while minimizing costs. Adaptive governance is promising because some communities have made significant progress in reducing their losses and vulnerability to climate impacts in the course of advancing their common interests. In doing so, they provide field-tested models for similar communities to consider. Policies that have worked anywhere in a network tend to be diffused for possible adaptation elsewhere in that network. Policies that have worked consistently intensify and justify collective action from the bottom up to reallocate supporting resources from the top down. Researchers can help realize the potential of adaptive governance on larger scales by recognizing it as a complementary approach in climate policy—not a substitute for scientific management, the historical baseline.

Keywords: scientific management, adaptive management, collective action, urban sustainability, decentralized decision-making, procedural rationality, case studies, resilience, common interests, historical sciences

A History of Research

Scientific Management Baseline

The origins of scientific management have been traced back to early modern European statecraft, when complex, opaque, and diverse local practices obstructed state officials seeking more revenue, conscripts, and public order. In response, officials sought to standardize and rationalize local practices, “to make the terrain, its products, and its workforce more legible—and hence manipulable—from above and from the center” (Scott, 1998, p. 2). For example, the crown’s interest reduced forests to the annual revenue yield of timber, but local communities depended on the forests for fodder, food, medicine, kindling, resins, and building materials. Thus, “The forest as a habitat disappears and is replaced by the forest as an economic resource to be managed efficiently and profitably” (Scott, 1998, p. 13). Carried to extremes in the 20th century, legibility gave nondemocratic states with uncritical confidence in science-based technology the capacity to impose utopian social engineering schemes at great human cost. Among them were collectivization in Russia and the Great Leap Forward in China.

In the United States, scientific management emerged in the 1880s from industrial innovations synthesized by Frederick Winslow Taylor. Among other devices to increase the efficiency and speed of machine shop production, scientific managers subdivided work into specialized tasks, rationalized them through time and motion studies to find “the one best way” to perform each task, and replaced day wages with piecework wages. Buttressed by statistical and accounting controls, such devices shifted power in the production process from skilled workers to scientific managers and middle-class technicians. Labor initially resisted Taylorism. But at its core, “Taylorism was clearly an explicit call for reconciliation between capital and labor, on the neutral ground of science and rationality. The bribe was higher productivity . . .” (Merkle, 1980, p. 15). In 1911, Taylor renamed his synthesis “scientific management” for testimony in a federal investigation of railroad rates, setting off a national “efficiency craze” that diffused into politics and government.

As Merkle (1980, p. 244) described it, “Scientific Management, translated into politics, advocated the development of the state as an organ of national planning and allocation according to a rationally derived system of priorities; it glorified a monolithic rational-technical order in place of the weak democratic forum that compromised among the interests of powerful groups.” Advocates of scientific management, allied with progressives, succeeded in establishing merit civil service, improving budgeting and fiscal controls, and implementing other managerial reforms. But they lacked meaningful standardized measures of success, such as profits, and activated resistance from other interest groups. In natural resource policy, for example, “Grass-roots groups throughout the country had few objectives in common, but they shared a violent revulsion against the scientific, calculated methods of resource use adjustment favored by [progressive] conservationists” (Hayes, 1959, pp. 272–273). For the latter, “The crux of the gospel of efficiency lay in a rational and scientific method of making basic technological decisions through a single, central authority” (p. 271). In 1937, the Brownlow commission proposed means for centralizing control of policy in the executive branch, but Congress withheld support until World War II, when national defense mobilization justified more efficiency (Merkle, 1980).

Scientific management was flexible and worked well enough to spread through competition among industrial organizations and nations. In doing so, it evolved into various forms under different labels, including “rationalization” in Europe. Eventually, it “worked its way into the fabric of all modern industrial societies, where it is now so common as to go unnoticed by most people” (Merkle, 1998, p. 2040). Scientific management continues to shape the framing of emerging policy problems, including climate change, despite disappointing outcomes. Among other factors, the proliferation of organized and networked interest groups has undermined key conditions on which the effectiveness of scientific management depends: The control of central authorities from the top down, the priority of technically rational and efficient policy, and the predictability of outcomes through science. In short, problems once considered technical became political, and therefore much less amenable to scientific management.

Adaptive Governance Emerges

Adaptive governance emerged as a pragmatic response to the limitations of scientific management more or less independently in many areas of applied science beyond climate change (Brunner, 2010). It also emerged from different streams of research directly relevant to climate change policy and governance, which are reviewed in order in this section: Global climate change mitigation, urban sustainability, local climate adaptation, collective action theory, and adaptive management. The emergents were not always labelled “adaptive governance.” However, each bears a family resemblance to the concept (Brunner & Lynch, 2010) described in the Summary.

Global Climate Change Mitigation

In this stream, some researchers set aside the “irreducibly global” framing of climate problems and moved their focus down and out, to what has worked, or might work, at smaller scales on a decentralized basis. For example, in response to proposals for “managing planet Earth” (Clark, 1989) and a program of the U.S. Environmental Protection Agency to “stabilize the climate system,” Tennekes (1990, p. 68) reported that he was “terrified by the hubris, the conceit, the arrogance implied by words like these. Who are we to claim that we can manage the planet? We cannot even manage ourselves. Who are we to claim that we can run the planetary ecosystem? In an ecosystem, no one is boss, virtually by definition.” Morgan (2000, p. 2285) focused on the advantages of an “evolutionary bottom-up strategy” over the UNFCCC’s “universal top-down framework” as “the only route to a global regime for managing CO2.” A bottom-up strategy, he explained, “can start today. As early adopters try different strategies, the world can evaluate and learn from alternative approaches. Early adopters can provide the inspiration, and proof of concept, to inspire or shame citizens in other regions . . . to take action.”

Similarly, Victor et al. (2005, p. 1820) observed that “After years of gridlock and indecision, serious efforts to slow the greenhouse express are finally taking hold.” This referred to six different systems to cap and trade CO2 emissions, led by the European Union’s system. They considered “This fragmented ‘bottom-up’ approach to carbon trading . . . pragmatic and effective” (p. 1820) and “the only way to build credible institutions that are essential for markets” (p. 1821). Theoretically, a universal trading system is a more attractive alternative to prevent free-riding on the efforts of others. “However, global institutions are too weak to monitor and enforce what is, in effect, a new monetary system. Global agreements are also vulnerable to exit when commitments become inconvenient” (p. 1820). The United States abandoned the Kyoto process, for example; Canada withdrew after ratification in 2011.

Expanding the earlier analysis, Keohane and Victor (2011) focused on the decentralized “regime complex” that emerged under the UNFCCC. It is “a loosely coupled set of specific regimes” (Figure 1). It includes various “clubs” of governments, such as the seven in the Asian Pacific Partnership that “agreed in 2005 to cooperate on research and development of new low-carbon technologies” (p. 10). It includes various bilateral deals; international institutions repurposed to reduce emissions, like the World Bank; subnational institutions, such as the State of California; the IPCC and its national counterparts; and for-profit and nonprofit organizations in civil society that address climate issues. The wide array “includes some tight couplings, especially where links between regime elements help channel resources such as money, technology, and ideas. However, most of the institutional elements in that array are decentralized and marked by loose couplings and lack of hierarchy” (p. 8).

Keohane and Victor (2011, p. 16) explained that, in decentralization, “Serious international cooperation is emerging ‘bottom up’ because integrated ‘top down’ institutions have been too difficult to craft” (p. 16). They attributed the difficulty to diverse interests backed by differences in power, uncertainties about the benefits of costly commitments and others’ commitments to cooperate, and the continuing struggle to find productive linkages among institutions. The fragmenting effects of these factors are magnified by economic cost and competitiveness considerations and by the diversity of problems: “Climate change is actually many distinct problems—each with its own attributes, administrative challenges, and distinctive political constituencies” (p. 13). Thus “it is prohibitively complicated to arrange all couplings ex ante into a single comprehensive regime. No single country has the power to impose a solution on all others” (p. 13).

Keohane and Victor (2011) contended that a loosely coupled regime complex is inevitable under these conditions and potentially more effective than a comprehensive regime. A regime complex has the advantage of flexibility across issues: “Without a requirement that all rules be bound within a common institution, it may be possible to adapt rules to distinctively different conditions on different issues, or for different coalitions of actors” (p. 15). It also facilitates adaptability over time, especially “when the best strategy for institutional adaptation is unclear and thus many diverse efforts should be tried and the more effective ones selected through experience” (p. 16). This is trial and error. Because of loose coupling, countries newly engaged in climate change mitigation or adaptation can benefit from the experience of others.

Under the Paris Agreement, the parties each pledged decentralized or nationally determined contributions to reduce greenhouse gas emissions. Keohane and Victor (2016) deemed this “shallow coordination” and considered it “crucial to move . . . towards deeper cooperation, while at the same time creating the conditions for favorable political coalitions within countries” (p. 572). The idea was to focus on “smaller, easier problems and in smaller groups where progress is feasible . . . and then working with reciprocity-based strategies that are known to promote deeper collaboration over time” (p. 572). They recommended a “strategy of decentralized policy coordination” through which “many partial efforts could build confidence and lead to larger cuts in emissions” (p. 1). This strategy is consistent with adaptive governance, which is implicitly recognized in the Paris Agreement and facilitated by it.

Urban Sustainability

In this stream, some researchers moved their focus in the opposite direction—out from individual cities and up—after the Brundtland Report in 1987 recognized the important role of cities in sustainable development. For example, Kates and Wilbanks (2003, pp. 22−23) argued that “For local places to act to reduce their bundle of greenhouse gas emissions, they must . . . have some control over a significant portion of their emissions . . . This requires enabling actions at larger scales—from market forces and corporate policies to actions of states, nations, and international agreements—that encourage localities to take action.”

Similarly, Bulkeley and Betsill (2005, p. 48) considered it “necessary to step beyond the local as a frame of reference, and to engage with the processes which shape local capacity and political will for sustainable development at multiple sites and scales of governance . . .” Their “multilevel governance” approach employed two case studies—Newcastle-upon-Tyne and Cambridgeshire—showing “how the governance of urban sustainability is being conducted both through relations between nested tiers of governance, and through a number of ‘spheres of authority’, including multiscalar coalitions of state and non-state actors . . .” (p. 59). They concluded that “we need to move away from an analysis which is explicitly concerned with the urban as a separate and discrete scale of political authority” (pp. 58−59).

When Bulkeley and Betsill (2013) reconsidered their earlier analysis, they noted the persistence of municipal volunteerism, in which local leaders encouraged community members to act on climate projections through existing local policy processes, provoking conflicts that often frustrated implementation. But they also noted the emergence of a more overtly political phase, strategic urbanism, exemplified by the Climate Protection Agreement of U.S. Mayors and the European Covenant of Mayors to engage more cities in pledges to reduce greenhouse gas emissions and to press their demands from the bottom up: “In each case, members have sought to raise the profile of cities in national and international climate debates and to put pressure on national governments (especially in the United States) to take more robust action” (p. 140). Similarly, the C40 Cities Climate Leadership Group emerged in 2005 and partnered with the Clinton Climate Initiative in 2007, with a dual focus on reducing greenhouse gas emissions and the risks of unavoidable climate change through adaptation.

Local Climate Adaptation

Researchers once distinguished mitigating climate change from adapting to climate change and set aside the latter as an alternative, not a complement, to reductions in greenhouse gas emissions. However, in the 1990s, Rayner and Malone (1997, p. 332), among others, challenged the “grip emissions reduction strategy has on policy” under the UNFCCC, despite continuing increases in emissions and “other pressing issues of human welfare” that had been sidestepped. To move beyond existing efforts to “predict the unpredictable,” they urged opening research to “assessing human vulnerability and social adaptation.”

Similarly, some researchers are challenging a distinction used in the Third U.S. National Climate Assessment: “While societal adaptation to climate variability is as old as civilization itself, the focus of this chapter is on preparing for unprecedented human-induced climate change through adaptation” (Bierbaum et al., 2014, p. 672; their emphasis). But it is difficult to distinguish the influence of climate change relative to variability in any extreme weather event, and the distinction is less relevant to community members impacted by an event than to climate specialists. Challenging the distinction opens research to decades of experience harvested by specialists in natural hazard and emergency management. Some of them have begun to integrate climate change considerations into their own research and practice (e.g., Bullock et al., 2009, 2016).

To illustrate the experience available, consider Project Impact, a field-tested model of adaptive governance for federal agencies seeking to assist local communities in reducing their losses and vulnerability to climate impacts. Under the leadership of director James Lee Witt in the Clinton administration, the Federal Emergency Management Agency (FEMA) considered how some local communities had already reduced losses on their own, evaluated prior disaster mitigation programs, and held a series of town hall meetings to clarify community-wide perspectives. Based on this research, FEMA initiated Project Impact in 1997, with seven pilot planning grants to communities committed to building community-wide partnerships. It worked well enough in a deliberately incremental and iterative process to expand to more than 250 communities within a few years. To share information and lessons among peers, FEMA added an annual conference of participating communities (Cowan, 2009, p. 78).

Holdeman and Patton (2008) distinguished Project Impact from the federal program in the scientific management tradition that “throws money at a specific and identifiable problem, with requisite rules and regulations attempting to control the outcome.” In Project Impact,

The idea was to devolve hazard-mitigation responsibility and authority down to the lowest possible level. If money changed hands from the feds to the locals, it was only seed money for growing a process that would not end when the money ran out. In this model, the federal government became not an authoritarian parent, but instead a partner and facilitator to help inspire and empower locals to size up and solve their own problems─ideally before disasters struck. Local communities were helped to take ownership of their disaster problems and solutions.

Building on their Project Impact grants, Tulsa, Miami-Dade County, and Manhattan, Kansas, among many other communities, continued to work on reducing their losses to natural disasters even after Project Impact was terminated early in 2001, a casualty of the new Bush administration.

A major appraisal of FEMA’s disaster mitigation grants from 1993 to 2003, including Project Impact, found that, “On average, across all grants, regions, and hazards studied, each dollar spent on mitigation saves society an average of $4 in avoided future losses” (Ganderton et al., 2006, p. 1). Project Impact also generated lessons for reducing losses to extreme weather events and climate change. According to George Haddow (2009, p. 202), deputy chief of staff under Witt, “The most important thing we have learned is that reducing disaster risks and losses is best done at the community level. Outside resources and technical assistance are critical, but effective and sustainable hazard mitigation programs and actions must be designed and implemented at the local level where disasters strike. Without the full support and participation of all stakeholders of a community in this effort it cannot be successful.” In this bottom-up strategy, community-wide participation helps advance the common interest.

Collective Action

In the seminal work, Ostrom (1990) sought to “shatter the convictions of many policy analysts that the only way to solve CPR problems is for external authorities to impose full private property rights or centralized regulation” (p. 182, her emphasis). A CPR is a common-pool resource—a communal grazing area, fishing ground, or irrigation canal, for example—defined by two traits: It is difficult to exclude individuals seeking to appropriate the resource, and each appropriation subtracts from what is available to others. In such situations, collective action theory predicted that individuals would not cooperate to sustain the CPR. Instead, self-interested free-riders appropriating whatever they could would deplete, degrade, or destroy the CPR. This is the “tragedy of the commons” (Hardin, 1968). However, Ostrom contended, intensive case studies showed that some self-organized and self-governing appropriators had sustained smaller-scale CPRs.

A case in point is an inshore fishery at Alanya in Turkey. Early in the 1970s, about a hundred fishers faced problems of unrestrained use of the fishery, including hostility, occasional violence, and increased uncertainty and costs in production from competition for the best fishing sites. “After more than a decade of trial-and-error efforts,” they “devised an ingenious system for allotting fishing sites to local fishers” (p. 19). The system had “the effect of spacing the fishers far enough apart on the fishing grounds that the production capabilities at each site are optimized. All fishing boats also have equal chances to fish at the best spots. Resources are not wasted searching for and fighting over a site. No signs of overcapitalization are apparent” (p. 19). Ostrom considered Alanya’s institutional performance “fragile”: While successful so far, it might lack the institutional capacity to restrict the number of fishers in the future. Of the other cases, she considered five a “failure,” two more “fragile,” and five “robust” (pp. 178−181, Table 5.2).

Generalizing across cases, Ostrom (1990, pp. 185−186) concluded that “individuals can be expected to make contingent commitments to rules that

  • define a set of appropriators who are authorized to use a CPR . . .

  • relate to the specific attributes of the CPR and the community of appropriators using the CPR . . .

  • are designed, at least in part, by local appropriators . . .

  • are monitored by individuals accountable to local appropriators . . . , and

  • are sanctioned using graduated punishments . . .”

Such rules bear a family resemblance to adaptive governance, limited to a group of appropriators and to their interest in sustaining their CPR. The rules are developed, monitored, enforced, and otherwise adapted to uncertain and complex environments through broad participation by appropriators operating as a self-governing group.

Ostrom (1990) also sought to “direct analysts’ attention to important variables to be taken into account in empirical and theoretical work” (p. 183). The resulting framework is suitable for inquiry on adaptive governance. It postulates that “one needs to view [an institutional-choice situation] from the perspective of the individuals making choices about future operational rules” (pp. 192−193). They “have very similar limited capabilities to reason and figure out the structure of complex environments” (p. 25). In complex environments with unstructured problems, they “are engaged in a trial-and-error effort to learn more about the results of their actions so that they can evaluate benefits and costs more effectively over time” (p. 38). The rules they select are contingent on expected benefits and costs as well as discount rates and internalized norms. Like other situational variables, these perspectives must be specified in each situation to understand or predict the rules chosen. This concept of procedurally rational action “places most of the explanatory weight on situational variables, rather than on [a priori] assumptions” (p. 193).

In Ostrom’s framework, “All rules are nested in another set of rules that define how the first set of rules can be changed” (pp. 51−52). Thus, operational rules that “directly affect the day-to-day decisions made by appropriators” are contingent on collective-choice (or policy) rules that are in turn contingent on constitutional-choice rules. The rules at any level are “those actually used, monitored, and enforced when individuals make choices about the actions they will take.” They are “common knowledge” in that “every participant knows the rules, and knows that others know the rules . . .” The demand for rule changes is contingent on problems like those resolved in Alanya. The supply is biased toward what has worked in similar circumstances elsewhere: “Given the substantial uncertainty associated with any change in rules, individuals are less likely to adopt unfamiliar rules than they are to adopt rules used by others in similar circumstances that have been known to work relatively well” (p. 209).

Dietz, Ostrom, and Stern (2003) drew attention to the vulnerability of local institutions for governing the commons once buffered from outside forces: Climate and other transboundary changes could force them to change too rapidly and fail. To address the problem, they outlined some generic “Requirements of Adaptive Governance in Complex Systems” (pp. 1908−1909; Fig. 3) and strategies for meeting them. (This is perhaps the first published appearance of the term “adaptive governance,” chosen by the authors over “adaptive management” to convey the importance of politics.) Ostrom (2010) addressed global climate change more directly, emphasizing a polycentric approach based on “multiple governing authorities at differing scales” (p. 552) rather than a monocentric and hierarchical unit like the UNFCCC. “Polycentric approaches facilitate achieving benefits at multiple scales as well as experimentation and learning from experience with diverse policies” (p. 550).

Adaptive Management

In the seminal work, Holling (1978) and co-authors sought to replace environmental assessments that assumed stable system behavior and sought to predict, in the tradition of scientific management, the environmental consequences of a policy or project already planned. They argued that “environmental assessments are not, and cannot be predictions in any real sense” (p. 133): The many variables necessarily excluded from an assessment interact with those few included, and because of project impacts, “the post-project system is a new system, and its nature cannot be deduced simply by looking at the original one.” The underlying issue was uncertainty arising from unknowns, including future societal preferences and such complexities of coupled social-ecological systems as nonlinearities, thresholds, and time delays. Environmental management that sought to “replace trial-and-error with some attempt to eliminate the uncertain and the unknown . . . could only result in tighter monitoring, regulation, and control based upon an illusory assumption of sufficient knowledge” (p. 8). The effect could only be loss of resilience. “Institutions, like biological systems, learn to handle change by experiencing change” (p. 135).

The authors’ alternative, adaptive management, became a step toward adaptive governance. They recommended integrating environmental with economic and social considerations at the outset of the planning process, rather than after a policy or project had already been designed. They also recommended integrating planning and assessment into a continuous process to be iterated, rather than treating them as separate and discrete processes. Given uncertainty, a continuous, iterative process of trial-and-error does not require that “all the final details are planned and fixed before the first action is taken” (p. 137). It does require monitoring the consequences of actions taken, among other disturbances, to improve understanding and management of the system. The authors considered this alternative “not really much more than common sense” that was “not always in common use” (p. 136).

In the development and testing of adaptive management, Holling (1978) and collaborators employed five case studies. “In each case, the purpose was to develop a set of alternatives policies or plans and assess their environmental, economic, and, in some cases, social consequences” (p. 12). They applied various techniques from systems analysis—including computer modeling, optimization, and multi-attribute utility analysis—to integrate information for specific management purposes, not scientific purposes. These models sought to reduce but not eliminate uncertainty, as part of a larger effort to design “policies and economic developments that can allow trial-and-error to work again” (p. 8). In particular, they thought the models could “serve as ‘laboratory worlds’ for the testing and evaluation of intrusions, developments, and policies” (p. 7). In addition, “Adaptive management can take a more active form by using the project itself as an experimental probe” (p. 137) to reduce unknowns.

Nearly two decades later, McLain and Lee (1996) sought “to see how adaptive management theory holds up in practice” (p. 437) in three cases: Spruce budworm management in New Brunswick and fisheries management in British Columbia, both of which had been featured in Holling (1978), and hydropower and fisheries management in the Columbia River Basin. They concluded that “the scientific adaptive management approach suffers from an overreliance on rational comprehensive planning models, a tendency to discount nonscientific forms of knowledge, and an inattention to policy processes that promote the development of shared understandings among diverse stakeholders” (p. 437). In sustainable management, the real issue was “how to foster the sense of collective responsibility that is needed to convince relatively autonomous stakeholders to engage in long-term, collective action” (p. 445).

Similarly, Walters (1997) evaluated adaptive management in riparian and coastal ecosystems. He concluded that “the simple, attractive idea of treating management as experimentation has been . . . difficult to put into practice. Objections to large-scale experiments . . . provide a rich set of excuses to delay decisive action by those who can profit from, or find protection in, such delays.” What to do about it? “The critical need today is . . . creative thinking about how to make management experimentation an irresistible opportunity, rather than a threat to various established interests.” Here politics were both an obstacle and an opportunity.

Gunderson and Light (2006) later evaluated adaptive management efforts in the Everglades ecosystem, where chronic environmental issues persisted. Everglades management, they contended, “is based upon a culture of scientific management and planning (i.e., rule-following behavior that is not easily translated into ecological predictions). That is, to achieve an acceptable plan, one must be able to rigorously predict outcomes before acting” (p. 328). Instead, the authors insisted that “Leaders embrace uncertainty and foster a culture that seeks and encourages opportunities for learning through experimentation” (p. 332). They also recognized the importance of politics integrating community interests: “Without managing the uncertainties in the social and political relationships in a way that integrates the ecological concerns of the area, restoration will continue to founder on the shoals of special interests” (p. 332).

Gunderson and Light (2006) recommended that “the Everglades should seek a transition to adaptive governance . . .” (p. 330). In their perspective, “Adaptive governance deals with the complex human interactions that have been obstacles to the implementation of adaptive management” (p. 325). As they described it, “Adaptive governance consists of social structures and processes that link individuals, organizations, agencies, and institutions at multiple organizational levels” (p. 330). As such, it recognizes the larger social and political context of adaptive management. Thus “Adaptive management is a critical component of adaptive governance that focuses on learning and uncertainty” (p. 326). For more on adaptive governance in this tradition, see Folke et al. (2005). (See Brunner, 2010, pp. 313−314, for a summary.)

In addition to ecological resilience, Gunderson, Allen, and Holling (2010, p. 424) refer to two other major theoretical developments in adaptive management. All three are useful heuristics for research in adaptive governance. One is the adaptive cycle, a sequence of four phases of change arising from the cumulative effects of many decisions and other disturbances in social-ecological systems. During the exploitation and conservation phases, the potential for change and the connectedness of resources in a system increase at a decreasing rate. Meanwhile, its resilience slowly decreases, making the system more vulnerable to disturbances that may lead rather abruptly to release of its resource commitments. Release leads to a reorganization of the system’s resources, initiating a new adaptive cycle. The other development is panarchy, which refers to the “evolutionary nature of adaptive cycles that are nested within and across space and time scales.” The term panarchy was chosen to avoid the “rigid, top-down” connotations of hierarchy (Gunderson & Holling, 2002, p. 74).

An Evolutionary Pattern

Other streams of research are relevant to adaptive governance in climate change (e.g., Garrick, 2015; Rayner, 2010; Scholz & Stiftel, 2005), but these five are prominent in the literature and illustrate two broad trends. One trend is toward comprehensiveness, through the integration of considerations once discounted or ignored but found to be relevant for research or policy purposes. At the risk of oversimplification, consider some examples:

  • Noticing gridlock and indecision in the UNFCCC’s top-down approach to mitigating climate change, Keohane and Victor and others pursued complementary means, including a regime complex for reducing greenhouse gas emissions from the bottom up.

  • Noticing the limited control of local governments, among other constraints in urban sustainability policy, Bulkeley and Betsill and others pursued a multilevel governance approach to understand and improve local policies for reducing greenhouse gas emissions.

  • Noticing the limits of mitigating global climate change in reducing human vulnerability, Rayner and Malone and others opened inquiry into adapting to climate change and later to the vast experience on adapting to local climate variability, including Project Impact.

  • Noticing that some smaller communities had avoided the tragedy of the commons and sustained their common pool resources, Ostrom and others opened collective action theory, once limited to full property rights or centralized regulation, to local self-governance.

  • Noticing problems in conventional environmental assessments, Holling and many collaborators and followers developed and concurrently integrated adaptive management into the management of social-ecological systems and eventually into adaptive governance.

The pattern is clearly evolutionary. In each stream, recognition of a problem motivated the exploration and integration of additional considerations in a path-dependent process of inquiry. The additional considerations were often political. In adaptive management, for example, grappling with non-environmental interests in practice challenged the earlier emphasis on computer models and experimental interventions designed to advance ecosystem resilience. They were insufficient to bypass or overcome political opposition.

Another trend is toward convergence on the concept of adaptive governance, despite differences in purposes and points of departure (Chaffin et al., 2014). Convergence is sometimes obscured by differences in vocabulary. Nevertheless, there is a family resemblance between what Brunner and Lynch (2010, p. 19) called “decentralized decision making” based on local experience and networking from the bottom up; what Holling et al. (2002, p. 74) called panarchy, referring to the “evolutionary nature of adaptive cycles that are nested within and across space and time scales”; what Ostrom (2010, p. 552) called “polycentric approaches” based on “multiple governing authorities at differing scales”; what Bulkeley and Betsill (2005, p. 59) called “multiscalar coalitions of state and non-state actors”; and what Keohane and Victor (2011, p. 7) called a “regime complex” consisting of “a loosely coupled set of specific regimes.” Without an innovation in vocabulary, Project Impact in response to climate variability decentralized decision-making from FEMA to hundreds of local communities with wide participation.

Whatever it is called, a decentralized structure of decision-making factors a large policy problem into many smaller and more tractable problems, fosters innovations in response to diverse circumstances, and facilitates adaptation of what has worked anywhere to similar circumstances elsewhere in a network. Without reviewing the details here, each stream of research in response to profound uncertainties recognized that policy is at best procedurally rational, a matter of trial and error. Each stream also recognized that balancing or integrating diverse interests through politics is a prerequisite for implementing policy and evaluating what worked on that basis. Whatever interest there may have been in predictions derived from theoretical generalizations, these streams of research relied on intensive inquiry into particular contexts considered comprehensively, in case studies or experimental interventions in the field.

Convergence indicates that adaptive governance is grounded in our era, not in the a priori assumptions of any particular stream of research. In other words, a pattern of adaptive governance is available to be discovered and developed by any stream of policy research open to observations on contemporary experience. The concept of adaptive governance in the Summary is no exception. It emerged from applications of the policy sciences, an “adaptation of the general approach to public policy that was recommended by John Dewey and his colleagues in the development of American pragmatism” (Lasswell, 1971, pp. xiii–xiv; see also Lasswell & Kaplan, 1950; Lasswell & McDougal, 1992). The applications were motivated in large part by evidence that local community-based initiatives are a promising but relatively neglected means of advancing common interests when and where scientific management becomes less effective. The applications began with research on decentralized energy policies (Brunner, 1980) and eventually focused on natural resource policy (Brunner et al., 2002, 2005). Concurrent with the latter, this concept of adaptive governance was field-tested in research on the North Slope of Alaska designed to help the village of Barrow advance its common interest in response to coastal erosion and flooding (Brunner & Lynch, 2010; Lynch & Brunner, 2007).

State of Research

In assessing the state of research on adaptive governance in climate change, one can identify strengths and weaknesses relevant to guiding future research and its contributions to society. The conclusions of any assessment logically depend on observations and the criteria applied to them. In each of the discussions of research goals, empirical research, and the use of research that follow, we make our criteria explicit before applying them to observations on appropriate research. Readers are encouraged to make their own criteria explicit for comparison.

Research Goals: Problem-Oriented

We prefer and recommend research that is problem-oriented, in the sense that it is directly relevant to helping communities advance their common interests in response to climate variability and change. As noted, advancing common interests is the point of governance in a free society (Lasswell & McDougal, 1992). The interests affected by climate, and their relative priorities, differ from one community to the next, but typically they include protecting life and limb, property and prosperity, other human artifacts, and ecosystem services, while minimizing costs. An interest is a perspective, a pattern of goal values sought by a person or group of persons, supported by their expectations about realizing the pattern. In clarifying the common interest, it is reasonable to discount interests in the community that are invalid with respect to the best available evidence or inappropriate with respect to larger value commitments, such as human dignity for all people.

This problem-oriented criterion recognizes the professional responsibility we incur when the funding of our research, including basic research, is justified by its contributions to society. For example, the self-proclaimed goal of the U.S. Global Change Research Program, as its funding began to ramp up dramatically in fiscal year 1989, was “to provide a sound scientific basis for national and international decision making on global change issues” (Committee on Earth Sciences, 1989, p. 4). The program’s mandate under the U.S. Global Change Research Act of 1990 (P. L. 101–106, Sec. 104) is “to produce information readily usable by policy makers attempting to formulate effective strategies for preventing, mitigating, and adapting to the effects of global climate change.” Similarly, the report of the 21st session of the Joint Science Committee of the World Climate Research Programme (2000, p. 5, their emphasis) advocated “much more cooperation . . . to provide solutions (i.e., involving ‘end-to-end’ projects) rather than just a piece of good new science.” Future Earth (2014, p. 5), the successor to the International Human Dimensions Programme on Global Environmental Change, markets itself as “the start of what should be a step change in international collaboration in the service of all people on our planet.”

Common Interests

Under this problem-oriented criterion, both mitigating and adapting to climate impacts are means of protecting or advancing common interests, not ends in themselves. Similarly, all versions of scientific management, adaptive governance, and any other approaches to research on climate change are means of advancing common interests, and may be evaluated and compared according to their contributions to that end. For example, we have contended that progress under the scientific management approach of the COP fell far short of advancing the common interest of the international community, including reductions in greenhouse gas emissions. Meanwhile, adaptive governance approaches have contributed significantly to advancing common interests in some smaller communities, including reductions in vulnerability to climate impacts and in local greenhouse gas emissions. Consider some examples of common interests, as specified by communities.

The common interest of the international community includes multiple interests formulated in the UNFCCC and the Paris Agreement. The goal in Article 1 of the UNFCCC—on stabilization of greenhouse gas concentrations in the atmosphere at a level not “dangerous”—should not be mistaken as a single target. Article 2 recognizes additional interests: “Such a level should be achieved within a time frame sufficient to allow ecosystems to adapt naturally to climate change, to ensure that food production is not threatened and to enable economic development to proceed in a sustainable manner.” Article 4 (7–8) recognizes developing country parties’ overriding interest in economic development and poverty alleviation. Similarly, the first goal of the Paris Agreement—to limit the increase in global average temperature to “well” below 2°C—reconsiders what is “dangerous” as a temperature level, not a concentration level. The second goal—to foster climate-resilient development—succinctly recognizes other interests involved in community development in addition to climate. (The third goal—to ensure finance flows consistent with the first two goals—is a means, not an end in itself.)

Among smaller communities involved in adaptive governance, consider Soldiers Grove, Wisconsin, called “the granddaddy” of local efforts demonstrating “how land use policies and actions can enhance the sustainability of [vulnerable] communities” (Burby, 1998, p. 240). After enduring decades of devastating floods, the village rejected a proposed levee early in 1975 and pressed ahead to relocate its downtown out of the floodplain. With completion of relocation in 1983, the floodplain was transformed into a public park. One community leader, William Becker (1983, p. 29) summarized the village’s common interest in his evaluation: “From the standpoint of improving the business climate, increasing the tax base, creating jobs, modernizing services and eliminating blight, relocation is succeeding.” Indeed, “The move provided individual owners and the village as a whole the opportunity and excuse to fix many long-standing problems” in addition to flood damage (p. 27). According to the village website, the wisdom of moving the downtown was reaffirmed after near-record floods in August 2007 and June 2008 caused only minor damage.

Consider also the Danish island of Samsø, recognized worldwide for becoming carbon neutral within a decade and then carbon negative by averting more CO2 emissions than it releases into the atmosphere (Jorgensen et al., 2007). Prompted by the Ministry of Energy in 1997, the island began developing wind turbines and other means to harvest renewable energy under the leadership of Søren Hermansen, who appealed to valid and appropriate interests in the community: “When I go out to explain to people why moving to renewable energy is a good thing . . . it helps to make the economic argument about saving oil costs, selling wind power and getting Government money. But there is a good feeling among Danes about self-sufficiency and the environment I can play on, too. Danes have a romantic attachment to the idea of leaving land unharmed” (quoted in Hoge, 1999). Community ownership and responsibility are also important: “We care about the production, because we own the wind turbines. Every time they turn around, it means money in the bank. And, being part of it, we also feel responsible” (Hermansen, quoted in Kolbert, 2008).

From the perspective of communities like these, climate change is not a separate problem overriding all others, as some climate researchers assume. It is another challenge in the ongoing process of community development in which the main tasks are clarifying and advancing the common interest. Efforts to mitigate or adapt to climate change can be motivated by projected losses with respect to a community’s common interest (as in the international agreements), by actual losses (as in Soldiers Grove) or by missed opportunities (as in Samsø). Cumulative and sustained progress depends on incremental steps that succeed often enough in advancing the common interest. However, substitutes for the common interest can be found in peer-reviewed research on adaptive governance in climate change. These are questionable under the problem-oriented criterion.

Substitute Goals

One substitute goal is more research of various kinds. An example advocates conceptual frameworks: “Only further development and application of shared conceptual frameworks taking into account the real complexity of governance regimes can generate the knowledge base needed to advance current understanding to a state that allows giving meaningful policy advice” (Pahl-Wostl, 2009, p. 354, emphasis added). This accepts our professional role and responsibility as researchers to give meaningful policy advice. However, conceptual frameworks at best contribute only indirectly to meeting that responsibility. Like other kinds of research, frameworks are not necessarily shared, nor do they necessarily accommodate real complexity or generate the knowledge base needed to advance understanding. There are many pitfalls on the path to meaningful policy advice, and many other factors involved in reaching that destination. Meanwhile, meaningful policy advice can be provided more directly and immediately through research evaluating practical experience, as, for example, Moss et al. (2013) have recommended and Vogel et al. (2016b) have done. The most relevant and reliable practical experience comes from places like Soldiers Grove and Samsø that have made significant progress in advancing common interests.

Another substitute goal is resilience. Holling (1978) and collaborators suggested resilience as “an overall criterion for policy design” (p. 19), defined it as “a property that allows a system to absorb and utilize (or even benefit from) change” (p. 11; their emphasis), and generalized it from ecological to social systems. However, Nelson (2011, p. 113) argued against resilience as a normative concept. “The desirability of a resilient system, or community, must be considered in light of social goals and how benefits and risks are distributed.” Building resilience “entails the implicit (or explicit) creation of winners and losers” (p. 118); questions of equity and power are involved. Thus for Nelson, the desirability of a resilient community is contingent on something quite like the common interest. And for us, the common interest does not always lie in the resilience or even the sustainability of a community. For example, recurring flood damage associated with rising sea levels in the 20th century motivated residents to abandon established communities on islands in the Chesapeake Bay and to relocate elsewhere (Fahrenthold, 2010). Residents acted on their common interest. Nelson (p. 116) recognized that resilience in the sense of “maintaining a system in its current form is not always feasible (or desirable).”

Another practice, normative in itself, is to avoid an explicit normative commitment. In their edited book Successful Adaptation to Climate Change, Moser and Boykoff (2013, p. xxii, their emphasis) “admit that we did not find the ‘holy grail,’ and, in fact, we would insist that there still is not, and. in fact, likely never will be, one answer that adequately addresses all the intersecting dimensions of adaptation success.” What follows is a list of factors that might contribute to success, beginning with “the critical importance of effective risk communication” and concluding with “the need to institutionalize and operationalize monitoring, evaluation, and learning.” But to what end? An answer to this normative question is left implicit. But a normative commitment to a definition of success is logically necessary to guide any reasonable approach to the planning and evaluation of research. “Reason, taken by itself, is instrumental. It can’t select our final goals . . . All reason can do is help us reach agreed-upon goals more efficiently” (Simon, 1983, p. 106). Under the problem-oriented criterion, empirical research is a means, not an end in itself.

Similarly, in a review and synthesis of research, Chaffin et al. (2014) observed that adaptive governance emerged from an “undesirable state” and that all versions pursue “a desired state” somehow related to “good governance.” They review different definitions of these terms but leave them ambiguous for the most part: A “desired state” consists of “specific ecological and social outcomes” left unspecified; the “principles of good governance” are listed as “legitimacy, transparency, accountability, inclusiveness, and fairness” (p. 7). This reflects the authors’ intent to “take a value neutral approach to defining environmental governance” (p. 1). In lieu of an explicit normative commitment to guide the rational planning and evaluation of research, they provided questions for further research. For example, “who and what sets of values determine the desired state, in both ecological and social terms?” (p. 5). Such questions invite both empirical and normative answers: What is? What ought to be? Logically, these questions must be distinguished and answers to them compared in the rational planning and evaluation of research. Implicit answers to the normative question cannot be avoided, but they can be made explicit.

Oughts

From our perspective under the problem-oriented criterion, the “desired state” ought to be the common interest of the community at hand, as determined by that community. This allows for assistance from outsiders, including advice from climate researchers in a supporting role. Community members typically demand a leading role (e.g., Becker, 1983, pp. 41−42), insisting they know more about balancing and integrating their own multiple interests than an outside expert on any one interest such as climate change. Some researchers disagree. But community members, unlike outside experts, must take de facto responsibility for their policy decisions by living with the consequences. “Success” ought to be progress in advancing the community’s common interest compared to a historical baseline. (Projections or visions of the future provide only direction, not baselines, to the extent that future interests and material conditions are uncertain.) The “desired state” and “success” are not merely abstractions. As case studies show, practitioners for practical purposes must operationalize them at least in qualitative terms. Researchers may and do participate in operationalizing goals (e.g., Victor & Kennel, 2014). The task is “to move from definitions that are brief and abstract toward definitions (and examples) that are detailed and delimited” (Lasswell & McDougal, 1992, p. 39), as we have tried to do here.

Empirical Research: Contextual

We prefer and recommend contextual research in which problem-oriented inquiry is contingent on a map of the particular context, a map both detailed and comprehensive within practical constraints. For example, a map centered on Barrow, Alaska, is appropriate if the problem is defined as losses from coastal erosion and flooding there. A map that includes Barrow, Point Hope, Shishmaref, and others is appropriate if the problem is defined as such losses in Alaskan Native villages. Including certain Alaskan and federal agencies in the map is appropriate if their resources are needed to reduce losses in the villages. As these examples suggest, the representation of each local context tends to become less comprehensive and less detailed as the scope of the map expands. To salvage a degree of legibility, a national or global map must erase differences among the many local contexts in which the problem occurs. But even a detailed and comprehensive local map is not the terrain; it is a simplified representation of it.

This contextual criterion is consistent with IPCC findings that context matters. For example, in Chapter 17 of its Fourth Assessment Report, Working Group II used variations on the word “context” 20 times in 17 pages of text, tables, and boxes. But it included only one case study—centered on Tsho Rolpa, a glacial lake in Nepal—that integrated enough considerations to qualify as relatively intensive (Brunner & Lynch, 2010, pp. 72−73). That context matters is also clear in research already cited. Keohane and Victor (2011, p. 13) found that “Climate change is actually many distinct problems—each with its own attributes, administrative challenges, and distinctive political constituencies.” Ostrom (1990, p. 23) found that “a set of rules used in one physical environment may have vastly different consequences if used in a different physical environment.” Chaffin et al. (2014, p. 9) found that “Adaptive governance is never the same in two places.” More generally, the concepts of panarchy, polycentric and multiscalar governance, and regime complex emerged as more contextual alternatives from relatively reductionist origins.

Moreover, each context matters: Under a comprehensive and detailed description, each case is unique. Logically, this is a consequence of the conjunction rule of probability. Empirically, reconsider three cases: Spruce budworm management in New Brunswick, fisheries management in British Columbia, and hydropower and fisheries management in the Columbia River Basin. They are each significant in the history of adaptive management (McLain & Lee, 1996), but they are not interchangeable for scientific or management purposes if their relevant geophysical, ecological, and social details are considered comprehensively. The details were critical in testing and revising the adaptive management approach and subject to change at varying rates in the adaptive cycle. Change is also evident in the Tsho Rolpa case. Beginning in 1998, villagers were actively involved in measures to mitigate a catastrophic release of water accumulating in the glacial lake, including controlled release, an active warning system, and drills. However, by 2010 the villagers’ perceptions of catastrophic risk had diminished and the drills had lapsed (Dahal & Hagelman, 2011).

Intensive Case Studies

As these examples suggest, under the contextual criterion, the priority observations and behavioral relationships are those integrated into intensive case studies. To clarify why, consider an action plan for mitigating or adapting to climate impacts in a particular local community. The plan’s significance for advancing the common interest—or any special interest, for that matter—depends on whether it gains public support, authorization by relevant authorities, and funding among other resources; whether it is implemented and evaluated; and whether it is sustained, revised, or terminated on that basis. Contingencies like these are recognized in various conceptual models of decision process (Lasswell, 1971, pp. 28–30), including the requirements for adaptive governance in Dietz et al. (2003, pp. 1908–1909), the policy cycle for improving outcomes in Pahl-Wostl (2009, Fig. 3), and the generalized adaptation process in Bierbaum et al. (2014, Fig. 28.3). Many observations and relationships must be integrated into a case study to clarify the significance of any one of them. Depending on the context, a plan may gather dust on a shelf, serve as a substitute for action, or contribute to advancing a special interest or the common interest, among other possibilities.

Metrics and Behavioral Relationships

Researchers sometimes assume that metrics, or quantitative observations, are necessary to evaluate outcomes in climate change mitigation and adaptation. A lack of “comprehensive evaluation metrics” is considered a problem (Bierbaum et al., 2014, p. 691; see also Bulkeley & Betsill, 2013, p. 150, and Berrang-Ford et al., 2011, p. 26), while new metrics are advocated (Chaffin et al., 2014, p. 10). However, metrics were not necessary for citizens of Samsø to know they had reduced greenhouse gas emissions; they saw wind turbines replace power plants. Nor were metrics necessary for citizens of Soldiers Grove to know they had reduced their vulnerability to floods; they saw buildings removed from the floodplain and replaced on higher ground. Local practitioners, judging from their case-study evaluations (e.g., Becker, 1983; Dickson, 2009; Jorgensen et al., 2007; Patton, 2009), found metrics useful in describing some outcomes but not others, and observations explaining outcomes—such as leadership, trust, and political will—were often impractical to quantify. More generally, “research suggests that performance measurement rarely leads to improved government performance or more efficient and accountable municipal management” (Sanger, 2013, p. 185).

The assumption that comprehensive evaluation metrics are necessary is a legacy of scientific management, with historical roots in the crown’s quest for legibility in early modern European statecraft. It is worth reconsidering under the contextual criterion and in light of experience. Regarding experience, consider the effort of NOAA’s Coastal Services Center (CSC) to develop a Community Resilience Index (CRI) to measure progress toward a more resilient nation. In July 2006, one of us participated in a CSC workshop that easily identified hundreds of factors relevant to measuring resilience in principle. But the subset measurable in practice would divert attention from those that are not, and would also frustrate aggregation into a single local or national index to the extent they are incommensurable. The effort apparently fell far short of its original aspirations. Perhaps it culminated in a Coastal CRI, a simple and inexpensive self-assessment tool consisting of checklists “created to identify areas in which your community may become more resilient” but not to compare communities (Sempier et al., 2010, p. 10).

The alternative to measures fixed and standardized across communities are context-sensitive observations, both qualitative and quantitative (Brunner, 2004). Local practitioners depend on them, as documented in their case studies. Context-sensitive observations also acknowledge the prevalence of “index instability” in the social sciences. Lasswell and Kaplan (1950, p. xx; see also Barrett, 2016) illustrated this concept by noting that signs of anger differ in the cultures of New England and Mexico, in subgroups within each culture, and over time. (In contrast, they noted, certain wave bands on a spectroscope signal carbon regardless of context.) Given index instability, do not ask, What are the indicators of progress everywhere? Ask, What are the signs of progress in the context at hand? Similarly, what are the signs of leadership, trust, political will and other factors that explain progress (or the lack of it) in that context? Index instability alone is enough to frustrate the quest for behavioral relationships that are valid regardless of context (Lasswell & Kaplan, 1950).

That quest is also diversionary for another reason. We humans, as individuals and in groups, act on internal perspectives that are much less than omniscient in response to complex external environments. Ostrom (1990) as noted was relatively explicit about this. Even more explicit were: Lasswell and Kaplan (1950, pp. 69−70) and Lasswell (1971, pp. 16−17) on the maximization postulate, Simon (1957, pp. 196−197, 1996) on the principle of bounded rationality, and Holland (1992, 2014) on complex adaptive systems. Consider also the challenge by the physicist Murray Gell-Mann (quoted in Ariely, 2009, p. 322) to “Think how hard physics would be if particles could think.” In this frame of reference, every act is a matter of trial and error in some degree. What works satisfactorily from the actors’ own perspectives tends to be stabilized as normal behavior, but as circumstances differ or change, the perception that normal behavior is no longer working tends to motivate a search for alternatives. Thus, we create, modify, and abandon “normal” behavioral relationships imperfectly adapted to differing and changing circumstances in an evolutionary process. Hence behavioral relationships serve as heuristics for exploring particular contexts, not as premises for deducing predictions. In adaptive management, for example, “The adaptive cycle is one part of a heuristic theory of change” (Gunderson & Holling, 2002, p. 49, emphasis added), not a predictive theory.

Social scientists recognize contingent relationships in recurring references to “path dependence” (Keohane & Victor, 2011). The paleontologist Gould (1989, p. 283) elaborated path dependence in a paradigm for the historical sciences: “A historical explanation does not rest on direct deductions from laws of nature, but on an unpredictable sequence of antecedent states, where any major change in any step of the sequence would have altered the final result. This final result is therefore dependent, or contingent, upon everything that came before—the unerasable and determining signature of history.” Thus, contingency is “the central principle of all history” in this paradigm. Similarly, Simon (1985, p. 301) considered the social sciences to be historical sciences because “What will happen next is not independent of where the system is right now. And a description of where it is right now must include a description of the subjective view of the situation that informs the choices of the actors.” Simon added that even the natural sciences “get only a little mileage from their general laws. Those laws have to be fleshed out by a myriad of facts, all of which must be harvested by laborious empirical research.” Empirical research into the context is the priority in this paradigm, not abstract theorizing.

Insight

Working with contingent, or context-dependent, indices and behavioral relationships, what can researchers contribute to society? “Insight, self-understanding, and freedom of choice” is the short answer offered by Lasswell and McDougal (1992, p. 875), who judged these to be “of even greater importance” than prediction. Indeed, these contributions undermine the accuracy of predictions when people change their behavior in response. For example, the insight that scientific management assumptions may have unwittingly dominated climate change science, policy, and decision-making frees us to evaluate those assumptions and consider alternatives that, if adopted, would change our behavior. Applied researchers might consider as role models those physicians who do not consider their patients interchangeable, but assist each with insights and self-understanding that free them to choose treatments and lifestyles on a more informed basis. Researchers in general might recognize the importance of context: “If modern historical and social scientific inquiry has underlined any lesson, it is that the significance of any detail depends upon its linkages to the context of which it is a part” (Lasswell, Lerner, & Pool, 1952, p. 11).

Use of Research: Used In Practice

We prefer and recommend research that is both usable and used in practice by decision makers in communities at all scales from local to global. Problem-oriented and contextual research is usable in principle. But to the extent that usable research is not used in practice, it serves our interest in research more directly than it serves the common interests of communities. Preferences for usable, if not used, research are recognized in titles and subtitles like these from research on climate change:

  • “Reconciling the Supply of Scientific Information with User Demands” (McNie, 2007)

  • “Creating Usable Science” (Dilling & Lemos, 2011)

  • “Narrowing the Climate Information Usability Gap” (Lemos et al., 2012)

  • “Broadening the Usability of Climate Science” (Kirchhoff et al., 2013)

  • “Delivering Climate Services” (McNie, 2013)

  • “Co-Producing Actionable Science for Water Utilities” (Vogel et al., 2016a)

These examples also suggest that problems, including missed opportunities, exist in uses of climate change research. (Notice that differences in vocabulary once again tend to obscure convergence on nearly equivalent concepts.)

Self-Evaluations

The use-in-practice criterion calls for continuing self-evaluations of our contributions to society as researchers, individually and collectively. For this purpose, the relevant questions are: Who communicates what, to whom, how, and with what effects? (Lasswell, 1960). The default answers tend to be variations on the understanding that researchers communicate scientific information on climate change to decision makers through written reports. But the effects are sometimes deemed problematic. For example, Cash (2000, p. 241) evaluated “top-down, centralized” scientific assessments “primarily focused on producing written reports” like those of the IPCC. In his view, they “failed in assisting local decision-makers in taking actions to help prevent global environmental problems, or in implementing responses to adapt to local impacts of global change.” Such assessments lack the fine scale and high resolution needed by local decision makers: “Global mean temperature change, while perhaps spurring international action, is irrelevant to local emergency relief managers in Bangladesh or farmers in Nebraska” (p. 242; his emphasis).

More generally, Kirchhoff et al. (2013, p. 406) found that “Despite the growing availability of scientific information, there is a persistent gap between knowledge production and its use to inform decision making.” But they also found signs of progress in the specifics: “In climate-related decision making, empirical evidence suggests that scientific information uptake can be improved for specific decision makers in specific contexts” (p. 394). Most examples of improved uptake “have been driven by highly interactive and well-established relationships between producers and users of climate information brokered by mechanisms created specifically for that purpose” (p. 404). NOAA’s eleven Regional Integrated Sciences and Assessments (RISA) programs are the examples offered; they translate and contextualize scientific information into more usable forms. (For more on RISA programs, see McNie, 2013.) But the authors considered the RISAs, like other highly interactive programs, problematic under a criterion of broad accessibility: They “tend to reach predominantly high-capacity users located near the RISA, raising questions about broader accessibility of climate information for users with less capacity and those located further away from the RISAs” (p. 405). In conclusion, Kirchhoff et al. (2013, p. 407) called for “new approaches capable of more effectively responding to higher levels of demand and a broader user base.” Perhaps the needed approaches are not so much new as neglected.

Networking

Local leaders frequently contact their peers in similar communities directly—through site visits, meetings, or other personal means—for more specific information about a shared policy problem. Typically, one community has made progress on a specific problem that others have only begun to face. The effects include learning from practical experience, and possibly adapting what has worked. These peer-to-peer networks are an approach to meeting higher demands for meaningful policy advice by a broader user base.

One example is the Samsø Energy Academy, which hosts about 4,000 visitors each year and works with others interested in Samsø’s experience in developing renewable energy sources (Newsletter No. 13, December, 2016, at http://energiakademiet.dk/en). For example, “Sustainable Molokai was especially interested in learning about some of the challenges we faced working with stakeholders [in Samsø] . . . One of the many questions was what to do when there were too many economic interests involved which didn’t correspond with the needs and awareness of the island’s inhabitants.” As a result of this initiative, two Danes from the Academy visited Molokai in Hawaii to initiate a partnership.

Another example is Soldiers Grove: “Shortly after relocation was proposed in 1975, a small group of villagers traveled to Niobrara, Nebraska, a small community relocating because of flooding problems caused by a dam downriver. The visit allowed villagers to see a relocation first-hand and to talk to its participants” (Becker, 1983, p. 44). Becker himself drew on Soldiers Grove’s experience to assist relocation in similar Midwestern communities after the Great Mississippi Flood of 1993 and to influence policy at the federal level. Additional examples of peer-to-peer networking are documented in other case studies, including coastal South Australia (Nursey-Bray et al., 2016), and Avalon, New Jersey, El Paso, Texas, Tulsa, Oklahoma, and Flagstaff, Arizona, in the United States (Vogel et al., 2016b).

Such examples corroborate a tendency for leading communities to become models for the guidance of similar communities that have lagged behind. Such models played an important role in the diffusion and adaptation of scientific management more than a century ago. The company “showcases” for Taylorism included Tabor Manufacturing, Link-Belt, and Yale and Towne (Merkle, 1980, pp. 56−57). In our time, such models are more often considered examples of “best practices” (e.g., Bierbaum et al., 2014; McCook et al., 2010). Substantively, the models tend to be detailed and comprehensive, selectively accessed according to user needs, and distributed through “decentralized diffusion systems” (Rogers, 1995), “communities of practice” (Wenger & Snyder, 2000), or “distributed assessment systems” as Cash (2000, p. 242) described them.

Cash (2000) drew attention to a pioneering model, the Pacific ENSO Applications Center (PEAC). PEAC helped islanders on U.S.-affiliated Pacific Islands reduce their vulnerability to droughts from the 1997−1998 El Niño/Southern Oscillation (ENSO). In doing so, PEAC also showed researchers how to make information on climate variability and change not only usable but also used in practice to advance common interests (Lynch & Brunner, 2010; Schroeder et al., 2012). So far as we know, however, PEAC and other models for researchers worth scaling out and scaling up are not prominent in peer-reviewed research on adaptive governance in climate change.

Harvesting Practical Experience

Opportunities exist for researchers to harvest practical experience as models and to develop and field-test new models in cooperation with local decision makers in many different and changing circumstances. Such models are central in theories of social change as the diffusion, partial restriction, and partial incorporation of innovations. (For a summary, see Brunner & Lynch, 2010, pp. 252−256; see also Rogers, 1995.) These processes are alternatives to the linear model of social change driven by unfettered basic science research, a version of scientific management. (For a review and critique of the linear model, see Kirchhoff et al., 2013, p. 395.)

Opportunities also exist to explore and ameliorate malfunctions in decentralized diffusion systems. For example, harvesting practical experience may disclose obsolete information and exaggerated claims of success uncritically accepted. If so, researchers might contribute third-party evaluations of the models in circulation and correct them as needed. Harvesting practical experience may disclose that decision makers are overloaded with information and uncertain about what they need. If so, the task is to design “intelligent information-filtering systems”; “information-distributing systems” are not sufficient (Simon, 1996, p. 144). For example, a system might feature case studies of communities that have implemented and evaluated their projects as successful. They provide more relevant and reliable guidance than the many more communities that have only announced plans.

By harvesting practical experience, researchers can learn how to assist communities in advancing their common interests. But this is only single-loop learning, as understood by Pahl-Wostl (2009, Fig. 3) and others. Beyond that are opportunities for double-loop learning: Researchers could reframe adaptive governance in climate change as a matter of ongoing community development. Mitigating or adapting to climate impacts would become another complication in advancing the community’s common interest. This would improve the usability and use of climate research, if nothing else. Beyond that are opportunities for triple-loop learning: Researchers could transform their scientific paradigms by incorporating insights from the historical sciences. In the latter, consilience is more important in testing explanations than prediction or replication. Consilience designates “the confidence gained when many independent sources ‘conspire’ to indicate a particular historical pattern” (Gould, 1989, p. 282; see also Brunner, 2006).

Conclusion

Assessing adaptive governance in climate change is complicated because goals and criteria differ and the field is in flux. The boundaries are open and expanding, as various streams of research integrate additional considerations as needed. From different origins, the various streams are also converging on decentralized decision-making structures and procedurally rational policies supported by intensive case studies. Nevertheless, the field is far from consolidated. Not all of the streams are self-identified with the term “adaptive governance.” Each tends to have distinctive terms for nearly equivalent key concepts, such as decentralized decision-making structures. And the degree of cross-referencing among the streams, while increasing, is still low in comparison to referencing within streams. The main weakness of the field is a tendency to elaborate established assumptions within the various streams. The main strengths lie in the rich theory and case studies in other streams that are available to challenge the assumptions of researchers in any one stream. Challenging our assumptions is a prerequisite for making progress, however progress is defined.

We define progress in response to climate variability and change as advancing the common interests of communities. From this normative standpoint, the professional role and responsibility of researchers is to assist communities with dependable research that is usable and used in practice. The main opportunities lie in intensive research that harvests the experience of successful practitioners, like those in Samsø, Soldiers Grove, and countless other local communities less well known. Their progress in advancing common interests, including mitigating or adapting to climate impacts, qualifies them as the experts from whom researchers can learn. We can harvest the experience of more and more diverse communities as models for more communities to adapt. We can provide and update third-party evaluations of models in circulation, to minimize misinformation and to filter information according to what has worked. Following the lead of the Pacific ENSO Applications Center, we can go a step further to collaborate with local practitioners, creating new models for other researchers to adapt. Beyond single-loop learning from steps like these, we might reframe climate change as another complication in the ongoing processes of community development and transform conventional scientific paradigms through insights from the historical sciences.

The challenge is to diffuse and adapt more broadly what has worked at the local level, and to reallocate supporting resources from the top down accordingly. By harvesting practical experience, we researchers can contribute insights that help free decision makers, and ourselves, from unexamined or obsolete assumptions—and thus expand the range of informed choices.

References

Ariely, D. (2009). Predictably irrational: The hidden forces that shape our decisions (revised ed.). New York: Harper Perennial.Find this resource:

Barrett, L. F. (2016, November 12). The varieties of anger. New York Times, SR8.Find this resource:

Becker, W. S. (1983). Come rain, come shine: A case study of a floodplain relocation project at Soldiers Grove, Wisconsin. Madison, WI: Bureau of Water Regulation and Zoning, Wisconsin Department of Natural Resources.Find this resource:

Berrang-Ford, L., Ford, J. D., & Paterson, J. (2011). Are we adapting to climate change? Global Environmental Change, 21, 25–33.Find this resource:

Bierbaum, R., Lee, A., Smith, J., . . . Seyller, E. (2014). Adaptation. In J. M. Melillo, T. Richmond, & G. W. Yohe (Eds.), Climate change impacts in the United States: The Third National Climate Assessment (pp. 670–706). U.S. Global Change Research Program. Washington, DC.Find this resource:

Brunner, R. D. (1980). Decentralized energy policies. Public Policy, 28 (Winter), 71–91.Find this resource:

Brunner, R. D. (2004). Context-sensitive monitoring and evaluation for the World Bank. Policy Sciences, 37(2), 103–136.Find this resource:

Brunner, R. D. (2006). A paradigm for practice. Policy Sciences, 39, 135–167.Find this resource:

Brunner, R. D. (2010). Adaptive governance as a reform strategy. Policy Sciences, 43, 301–341.Find this resource:

Brunner, R. D., Colburn, C. H., Cromley, C. M., Klein, R. A., & Olson, E. A. (2002). Finding common ground: Governance and natural resources in the American West. New Haven, CT: Yale University Press.Find this resource:

Brunner, R. D., & Lynch, A. H. (2010). Adaptive governance and climate change. Boston: American Meteorological Association.Find this resource:

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.Find this resource:

Bulkeley, H., & Betsill, M. M. (2005). Rethinking sustainable cities: Multilevel governance and the ‘urban’ politics of climate change. Environmental Politics, 14(1), 42–63.Find this resource:

Bulkeley, H., & Betsill, M. M. (2013). Revisiting the urban politics of climate change. Environmental Politics, 22(1), 136–154.Find this resource:

Bullock, J. A., Haddow, G. D., & Haddow, K. S. (Eds.). (2009). Global warming, natural hazards, and emergency management. Boca Raton, FL: CRC Press.Find this resource:

Bullock, J. A., Haddow, G. D., Haddow, K. S., & Coppola, D. P. (Eds.). (2016). Living with climate change: How communities are surviving and thriving in a changing climate. Boca Raton, FL: CRC Press.Find this resource:

Burby, R. J. (Ed.). (1998). Cooperating with nature: Confronting natural hazards with land use planning for sustainable communities. Washington, DC: Joseph Henry Press.Find this resource:

Cash, D. W. (2000). Distributed assessment systems: An emerging paradigm of research, assessment and decision-making for environmental change. Global Environmental Change, 10, 241–244.Find this resource:

Chaffin, B. C., Gosnell, H., & Cosens, B. A. (2014). A decade of adaptive governance scholarship: Synthesis and future directions. Ecology and Society, 19(3), 56f.Find this resource:

Clark, W. C. (1989). Managing planet Earth. Scientific American, 261, 47–54.Find this resource:

Committee on Earth Sciences. (1989). Our changing planet: The FY 1990 research plan: Executive summary. Washington, DC: U.S. Global Change Research Program.Find this resource:

Cowan, B. (2009). Project impact: Building a disaster-resistant community. In J. A. Bullock, G. D. Haddow, & K. S. Haddow (Eds.), Global warming, natural hazards, and emergency management (pp. 70–82). Boca Raton, FL: CRC Press.Find this resource:

Dahal, K. R., & Hagelman, R. III (2011). People’s risk perception of glacial lake outburst flooding: A case of Tsho Rolpa Lake, Nepal. Environmental Hazards, 10(2), 154–170.Find this resource:

Dickson, D. (2009). Living river: The Napa Valley flood management plan. In J. A. Bullock, G. D. Haddow, & K. S. Haddow (Eds.), Global warming, natural hazards, and emergency management (pp. 126–149). Boca Raton, FL: CRC Press.Find this resource:

Dietz, T., Ostrom, E., & Stern, P. C. (2003). The struggle to govern the commons. Science, 302(12), 1907–1912.Find this resource:

Dilling, L., & Lemos, M. C. (2011). Creating usable science: Opportunities and constraints for climate knowledge use and their implications for science policy. Global Environmental Change, 21, 680–689.Find this resource:

Fahrenthold, D. A. (2010, October 25). Losing battle against the bay. The Washington Post, A10.Find this resource:

Folke, C., Hahn, T., Olsson, P., & Norberg, J. (2005). Adaptive governance of social-ecological systems. Annual Review of Environmental Resources, 30, 441–473.Find this resource:

Future Earth. (2014). Future Earth initial design. Retrieved from http://www.futureearth.org/sites/default/files/Future-Earth-Design-Report_web.pdf.

Ganderton, P. T., Bourque, L., Dash, N., . . . Taylor, C. (2006). Mitigation generates savings of four to one and enhances community resilience. Natural Hazards Observer, XXX(March), 1–3.Find this resource:

Garrick, D. E. (2015). Water allocation in rivers under pressure: Water trading, transaction costs and transboundary governance in the western US and Australia. Cheltenham, U. K.: Edward Elgar.Find this resource:

Gould, S. J. (1989). Wonderful life: The Burgess shale and the nature of history. New York: W. W. Norton.Find this resource:

Gunderson, L. H., Allen, C. R., & Holling, C. S. (2010). Foundations of ecological resilience. Washington, DC: Island Press.Find this resource:

Gunderson, L. H., & Holling, C. S. (Eds.). (2002). Panarchy: Understanding transformations in human and natural systems. Washington, DC: Island Press.Find this resource:

Gunderson, L. H., & Light, S. S. (2006). Adaptive management and adaptive governance in the Everglades ecosystem. Policy Sciences, 39, 323–334.Find this resource:

Haddow, G. D. (2009). Conclusions and recommendations. In J. A. Bullock, G. D. Haddow, & K. S. Haddow (Eds.), Global warming, natural hazards, and emergency management (pp. 201–221). Boca Raton, FL: CRC Press.Find this resource:

Hardin, G. (1968). The tragedy of the commons. Science, 162(13), 1243–1248.Find this resource:

Hayes, S. P. (1959). Conservation and the gospel of efficiency: The progressive conservation movement, 1890–1920. Cambridge, MA: Harvard University Press.Find this resource:

Hoge, W. (1999, October 9). Samsø journal: In this energy project, no tilting at windmills. New York Times.Find this resource:

Holdeman, E., & Patton, A. (2008, December 12). Project Impact initiative to create disaster-resistant communities demonstrates worth in Kansas years later. Emergency Management. Retrieved from http://www.emergencymgmt.com/disaster/Project-Impact-Initiative-to.html.Find this resource:

Holland, J. H. (1992). Complex adaptive systems. Daedalus, 121(Winter), 17–30.Find this resource:

Holland, J. H. (2014). Complexity: A very short introduction. Oxford: Oxford University Press.Find this resource:

Holling, C. S. (Ed.). (1978). Adaptive environmental assessment and management. New York: John Wiley.Find this resource:

Holling, C. S., Gunderson, L. H., & Peterson, G. D. (2002). Sustainability and panarchies. In L. H. Gunderson, & C. S. Holling (Eds.), Panarchy: Understanding transformations in human and natural systems (pp. 63–102). Washington, DC: Island Press.Find this resource:

Jorgensen, P. J., Hermansen, S., Johnsen, A., & Nielsen, J. P. (2007). Samsø, a renewable energy island: 10 years of development and evaluation. Samsø, Denmark: Samsø Energy Academy.Find this resource:

Kates, R. W., & Wilbanks, T. J. (2003). Making the global local: Responding to climate change concerns from the ground up. Environment, 45(3), 12–23.Find this resource:

Keohane, R., & Victor, D. (2011). The regime complex for climate change. Perspectives on Politics, 9(1), 7–23.Find this resource:

Keohane, R. O., & Victor, D. G. (2016 June). Cooperation and discord in global climate policy. Nature Climate Change, 6(6), 570–575.Find this resource:

Kirchhoff, C. J., Lemos, M. C., & Sessai, S. (2013). Actionable knowledge for environmental decision making: Broadening the usability of climate science. Annual Review of Environment and Resources, 38, 393–414.Find this resource:

Kolbert, E. (2008). The island in the wind. The New Yorker (July 7 & 14), 68–77.Find this resource:

Lasswell, H. D. (1960). The structure and function of communication in society. In W. Schramm (Ed.), Mass communications (pp. 117–130). Urbana: University of Illinois Press.Find this resource:

Lasswell, H. D. (1971). A pre-view of policy sciences. New York: Elsevier.Find this resource:

Lasswell, H. D., & Kaplan, A. (1950). Power and society: A framework for political inquiry. New Haven, CT: Yale University Press.Find this resource:

Lasswell, H. D., Lerner, D., & Pool, I. de S. (1952). The comparative study of symbols: An introduction. Stanford, CA: Stanford University Press.Find this resource:

Lasswell, H. D., & McDougal, M. S. (1992). Jurisprudence for a free society: Studies in law, science and policy. New Haven, CT: New Haven Press.Find this resource:

Lemos, M. C., Kirchhoff, C. J., & Ramprasa, V. (2012). Narrowing the climate information usability gap. Nature Climate Change, 2 (November), 789–794.Find this resource:

Lynch, A. H., & Brunner, R. D. (2007). Context and climate change: An integrated assessment for Barrow, Alaska. Climatic Change, 82, 93–111.Find this resource:

Lynch, A. H., & Brunner, R. D. (2010). Learning from climate variability: Adaptive governance and the Pacific ENSO Applications Center. Weather, Climate and Society, 2, 311–319.Find this resource:

McCook, L. J., Ayling, T., Cappo, M., . . . Williamson, D. H. (2010). Adaptive management of the Great Barrier Reef: A globally significant demonstration of the benefits of networks of marine reserves. Proceedings of the National Academy of Sciences of the United States of America, 107(43), 18278–18285.Find this resource:

McLain, R. J., & Lee, R. G. (1996). Adaptive management: Promises and pitfalls. Environmental Management, 20(4), 437–448.Find this resource:

McNie, E. C. (2007). Reconciling the supply of scientific information with user demands: An analysis of the problem and review of the literature. Environmental Science & Policy, 10, 17–38.Find this resource:

McNie, E. C. (2013). Delivering climate services: Organizational strategies and approaches for producing useful climate science information. Weather, Climate, and Society, 5, 14–26.Find this resource:

Merkle, J. A. (1980). Ideology and management: The legacy of the international scientific management movement. Berkeley: University of California Press.Find this resource:

Merkle, J. A. (1998). Scientific management. In J. M. Shafritz (Ed.), International encyclopedia of public policy and administration (pp. 2036–2040). Boulder, CO: Westview.Find this resource:

Morgan, M. G. (2000). Managing carbon from the bottom up. Science, 289(29), 2285.Find this resource:

Moser, S. C., & Boykoff, M. T. (2013). Successful adaptation to climate change: Linking science and policy in a rapidly changing world. London: Routledge.Find this resource:

Moss, R. H., Meehl, G. A., Lemos, M. C., . . . Wilbanks, T. J. (2013). Hell and high water: Practice-relevant adaptation science. Science, 342(8), 696–698.Find this resource:

Nelson, D. R. (2011). Adaptation and resilience: Responding to a changing climate. WIREs Climate Change, 2, 113–120.Find this resource:

Nursey-Bray, M., Harvey, N., & Smith, T. F. (2016). Learning and local government in coastal South Australia: Towards a community of practice framework for adapting to global change. Regional Environmental Change, 16(3), 733–746.Find this resource:

Ostrom, E. (1990). Governing the commons: The evolution of institutions for collective action. Cambridge, U.K.: Cambridge University Press.Find this resource:

Ostrom, E. (2010). Polycentric systems for coping with collective action and global environmental change. Global Environmental Change, 20(4), 550–557.Find this resource:

Pahl-Wostl, C. (2009). A conceptual framework for analysing adaptive capacity and multi-level learning processes in resource governance regimes. Global Environmental Change, 19, 354–365.Find this resource:

Patton, A. (2009). A Tulsa story: Learning to live in harmony with nature. In J. A. Bullock, G. D. Haddow, & K. S. Haddow (Eds.), Global warming, natural hazards, and emergency management (pp. 84–113). Boca Raton, FL: CRC Press.Find this resource:

Rayner, S. (2010). How to eat an elephant: A bottom-up approach to climate policy. Climate Policy, 10, 615–621.Find this resource:

Rayner, S., & Malone, E. L. (1997). Zen and the art of climate maintenance. Nature, 390(27), 332–334.Find this resource:

Rogers, E. M. (1995). Centralized and decentralized diffusion systems. In Diffusion of Innovations (4th ed., pp. 364–369). New York: Free Press.Find this resource:

Sanger, M. B. (2013). Does measuring performance lead to better performance? Journal of Policy Analysis and Management, 32(1), 185–203.Find this resource:

Scholz, J. T., & Stiftel, B. (Eds.). (2005). Adaptive governance and water conflict: New institutions for collaborative planning. Washington, DC: Resources for the Future.Find this resource:

Schroeder, T. A., Chowdhury, M. D., Lander, M. A., Guard, C. C., Felkeley, C., & Gifford, D. (2012). The role of the Pacific ENSO Applications Climate center in reducing vulnerability to climate hazards. Bulletin of the American Meteorological Society, 93(July), 1003–1015.Find this resource:

Scott, J. C. (1998). Seeing like a state: How certain schemes to improve the human condition have failed. New Haven, CT: Yale University Press.Find this resource:

Sempier, T. T., Swann, D. L., Emmer, R., Sempier, S. H., & Schneider, M. (2010). Coastal Community Resilience Index: A community self-assessment. MASGP-08-014. Ocean Springs, MS: Mississippi-Alabama Sea Grant Consortium. Retrieved from http://www.masgc.org/pdf/masgp/08-014.pdf.Find this resource:

Simon, H. A. (1957). Models of man: Social and rational. New York: John Wiley.Find this resource:

Simon, H. A. (1983). Reason in human affairs. Stanford, CA: Stanford University Press.Find this resource:

Simon, H. A. (1985). Human nature in politics: The dialogue of psychology with political science. American Political Science Review, 79, 293–304.Find this resource:

Simon, H. A. (1996). The sciences of the artificial (3d ed.). Cambridge, MA: MIT Press.Find this resource:

Tennekes, H. (1990). A sideways look at climate research. Weather, 45, 67–68.Find this resource:

Victor, D. G., House, J. C., & Joy, S. (2005). A Madisonian approach to climate policy. Science, 309(16), 1820–1821.Find this resource:

Victor, D. G., & Kennel, C. F. (2014). Ditch the 2°C warming goal. Nature, 514(2), 30–31.Find this resource:

Vogel, J., McNie, E., & Behar, D. (2016a). Co-producing actionable science for water utilities. Climate Services, 2–3, 30–40.Find this resource:

Vogel, J., Carney, K. M., Smith, J. B., . . . Stultz, M. (2016b). Climate adaptation: The state of practice in U.S. communities. Troy, MI: The Kresge Foundation.Find this resource:

Walters, C. (1997). Challenges in adaptive management of riparian and coastal ecosystems. Conservation Ecology, 1(2), 1–16.Find this resource:

Wenger, E. C., & Snyder, W. M. (2000). Communities of practice: The organizational frontier. Harvard Business Review, 78(1) (January–February), 139–145.Find this resource:

World Climate Research Programme. (2000). Annual session of the Joint Scientific Committee. Retrieved from http://www.wcrp-climate.org/documents/jsc21report.pdf.