Adaptive management

Adaptive management (AM), also known as adaptive resource management (ARM), is a structured, iterative process of robust decision making in the face of uncertainty, with an aim to reducing uncertainty over time via system monitoring. In this way, decision making simultaneously meets one or more resource management objectives and, either passively or actively, accrues information needed to improve future management. Adaptive management is a tool which should be used not only to change a system, but also to learn about the system (Holling 1978). Because adaptive management is based on a learning process, it improves long-run management outcomes. The challenge in using the adaptive management approach lies in finding the correct balance between gaining knowledge to improve management in the future and achieving the best short-term outcome based on current knowledge (Allan & Stankey 2009).

Objectives

There are a number of scientific and social processes which are vital components of adaptive management, including:

  1. Management is linked to appropriate temporal and spatial scales
  2. Management retains a focus on statistical power and controls
  3. Use of computer models to build synthesis and an embodied ecological consensus
  4. Use of embodied ecological consensus to evaluate strategic alternatives
  5. Communication of alternatives to political arena for negotiation of a selection

The achievement of these objectives requires an open management process which seeks to include past, present and future stakeholders. Adaptive management needs to at least maintain political openness, but usually aims to create it. Adaptive management must therefore be a scientific and social process. It must focus on the development of new institutions and institutional strategies in balance with scientific hypothesis and experimental frameworks (resilliance.org).

Adaptive management can proceed as either passive adaptive management or active adaptive management, depending on how learning takes place. Passive adaptive management values learning only insofar as it improves decision outcomes (i.e. passively), as measured by the specified utility function. In contrast, active adaptive management explicitly incorporates learning as part of the objective function, and hence, decisions which improve learning are valued over those which do not (Holling 1978; Walters 1986). In both cases, as new knowledge is gained, the models are updated and optimal management strategies are derived accordingly. Thus, while learning occurs in both cases, it is treated differently. Often, deriving actively adaptive policies is technically very difficult, which prevents it being more commonly applied.[1]

Features

Key features of both passive and active adaptive management are:

However, a number of process failures related to information feedback can prevent effective adaptive management decision making (Elzinga et al. 1998):

  1. data collection is never completely implemented;
  2. data are collected but not analyzed;
  3. data are analyzed but results are inconclusive;
  4. data are analyzed and are interesting, but are not presented to decision makers;
  5. data are analyzed and presented, but are not used for decision-making because of internal or external factors

History

The use of adaptive management techniques can be traced back to peoples from ancient civilisations. For example, the Yap people of Micronesia have been using adaptive management techniques to sustain high population densities in the face of resource scarcity for thousands of years (Falanruw 1984). In using these techniques, the Yap people have altered their environment creating, for example, coastal mangrove depressions and seagrass meadows to support fishing and termite resistant wood (Stankey and Shinder 1997).

The origin of the adaptive management concept can be traced back to ideas of scientific management pioneered by Frederick Taylor in the early 1900s (Haber 1964). While the term ‘adaptive management’ evolved in natural resource management workshops through decision makers, managers and scientists focussing on building simulation models to uncover key assumptions and uncertainties (Bormann et al. 1999).

Two ecologists at The University of British Columbia, C.S. Holling (1978) and C.J Walters (1986) further developed the adaptive management approach as they distinguished between passive and active adaptive management practice. Kai Lee, notable Princeton physicist, expanded upon the approach in the late 1970s and early 1980s while pursuing a post-doctorate degree at UC Berkeley. The approach was further developed at the International Institute for Applied Systems Analysis (IIASA) in Vienna, Austria, while C.S. Holling was director of the Institute. In 1992, Hilbourne described three learning models for federal land managers, around which adaptive management approaches could be developed, these are reactive, passive and active.

Adaptive management has probably been most frequently applied in Yap, Australia and North America, initially applied in fishery management, but received more broad application in the 1990s and 2000s. One of the most successful applications of adaptive management has been in the area of waterfowl harvest management in North America, most notably for the mallard (Johnson et al., 1993; Nichols et al., 2007).

Adaptive management in a conservation project and program context can trace its roots back to at least the early 1990s, with the establishment of the Biodiversity Support Program (BSP) in 1989. BSP was a USAID-funded consortium of WWF, The Nature Conservancy (TNC), and World Resources Institute (WRI). Its Analysis and Adaptive Management Program sought to understand the conditions under which certain conservation strategies were most effective and to identify lessons learned across conservation projects. When BSP ended in 2001, TNC and Foundations of Success (FOS, a non-profit which grew out of BSP) continued to actively work in promoting adaptive management for conservation projects and programs. The approaches used included Conservation by Design (TNC) and Measures of Success (FOS).

In 2004, the Conservation Measures Partnership (CMP) – which includes several former BSP members – developed a common set of standards and guidelines for applying adaptive management to conservation projects and programs.

Use in environmental practices

Applying adaptive management in a conservation project or program involves the integration of project/program design, management, and monitoring to systematically test assumptions in order to adapt and learn. The three components of adaptive management in environmental practice are:

Application to environmental projects and programs

Figure 1: CMP Adaptive Management Cycle

Open Standards for the Practice of Conservation lay out 5 main steps to an adaptive management project cycle (see Figure 1). The Open Standards represent a compilation and adaptation of best practices and guidelines across several fields and across several organizations within the conservation community. Since the release of the initial Open Standards (updated in 2007 and 2013), thousands of project teams from conservation organizations (e.g., TNC, Rare, and WWF), local conservation groups, and donors alike have begun applying these Open Standards to their work. In addition, several CMP members have developed training materials and courses to help apply the Standards.

Some recent write-ups of adaptive management in conservation include: wildlife protection (SWAP, 2008), forests ecosystem protection (CMER, 2010), coastal protection and restoration (LACPR, 2009), natural resource management (water, land and soil), species conservation especially, fish conservation from overfishing (FOS, 2007) and climate change (DFG, 2010). In addition, some other examples follow:

Tools and guidance for conservation practitioners

The following resources offer guidance on designing and planning conservation projects (Steps 1 and 2 of the Open Standards), as well as more general guidance on the adaptive management process.
Step 1 Conceptualize (Describing the Project’s Context)

Step 2 Plan Actions and Monitoring

Use in other practices as a tool for sustainability

Adaptive management as a systematic process for improving environmental management policies and practices is the traditional application however, the adaptive management framework can also be applied to other sectors seeking sustainability solutions such as business and community development. Adaptive management as a strategy emphasizes the need to change with the environment and to learn from doing. Adaptive management applied to ecosystems makes overt sense when considering ever changing environmental conditions. The flexibility and constant learning of an adaptive management approach is also a logical application for organizations seeking sustainability methodologies. Businesses pursuing sustainability strategies would employ an adaptive management framework to ensure that the organization is prepared for the unexpected and geared for change. By applying an adaptive management approach the business begins to function as an integrated system adjusting and learning from a multi-faceted network of influences not just environmental but also, economic and social (Dunphy, Griffths, & Benn, 2007). The goal of any sustainable organization guided by adaptive management principals must be to engage in active learning to direct change towards sustainability (Verine, 2008). This “learning to manage by managing to learn” (Bormann BT, 1993) will be at the core of a sustainable business strategy.

Sustainable community development requires recognition of the relationship between environment, economics and social instruments within the community. An adaptive management approach to creating sustainable community policy and practice also emphasizes the connection and confluence of those elements. Looking into the cultural mechanisms which contribute to a community value system often highlights the parallel to adaptive management practices, “with [an] emphasis on feedback learning, and its treatment of uncertainty and unpredictability”(Berkes, Colding, & Folke, 2000). Often this is the result of indigenous knowledge and historical decisions of societies deeply rooted in ecological practices (Berkes, Colding, & Folke, 2000). By applying an adaptive management approach to community development the resulting systems can develop built in sustainable practice as explained by the Environmental Advisory Council (2002), “active adaptive management views policy as a set of experiments designed to reveal processes that build or sustain resilience. It requires, and facilitates, a social context with flexible and open institutions and multi-level governance systems that allow for learning and increase adaptive capacity without foreclosing future development options” ( p. 1121).

In an ever changing world, adaptive management appeals to many practices seeking sustainable solutions by offering a framework for decision making that proposes to support a sustainable future which, “conserves and nurtures the diversity — of species, of human opportunity, of learning institutions and of economic options”(The Environmental Advisory Council, 2002, p. 1121).

General resources

Information and guidance on the entire adaptive management process is available from CMP members’ websites and other online sources:

See also

References

  1. ↑ Carey, G, Crammond, B, Malbon, E et al 2015, 'Adaptive policies for reducing inequalities in the social determinants of health.', International Journal of Health Policy and Management. http://www.ijhpm.com/article_3097_0.html
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