Adaptive management, also known as adaptive resource management or adaptive environmental assessment and management, 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. 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. This approach has more recently been employed in implementing international development programs.
Objectives There are a number of scientific and social processes which are vital components of adaptive management, including: Management is linked to appropriate temporal and spatial scales Management retains a focus on statistical power and controls Use of computer models to build synthesis and an embodied ecological consensus Use of embodied ecological consensus to evaluate strategic alternatives 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 (resilience.org).
Adaptive management can proceed as either passive 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. 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.
Features Key features of both passive and active adaptive management are: Iterative decision-making (evaluating results and adjusting actions on the basis of what has been learned) Feedback between monitoring and decisions (learning) Explicit characterization of system uncertainty through multi-model inference Bayesian inference Embracing risk and uncertainty as a way of building understanding
However, a number of process failures related to information feedback can prevent effective adaptive management decision making:
data collection is never completely implemented data are collected but not analyzed data are analyzed but results are inconclusive data are analyzed and are interesting, but are not presented to decision makers 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.
Two ecologists at The University of British Columbia, C.S. Holling and C.J Walters 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.
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 or ecosystem management project 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:
Testing assumptions is about systematically trying different actions to achieve a desired outcome. It is not, however, a random trial-and-error process. Rather, it involves using knowledge about the specific site to pick the best known strategy, laying out the assumptions behind how that strategy will work, and then collecting monitoring data to determine if the assumptions hold true. Adaptation involves changing assumptions and interventions to respond to new or different information obtained through monitoring and project experience. Learning is about explicitly documenting a team's planning and implementation processes and its successes and failures for internal learning as well as learning across the conservation community. This learning enables conservation practitioners to design and manage projects better and avoid some of the perils others have encountered. Learning about a managed system is only useful in cases where management decisions are repeated.
Application to environmental projects and programs
Open Standards for the Practice of Conservation lays out five 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 to version 5.0 in 2025), 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:
In 2006–2007, FOS worked with The National Fish and Wildlife Foundation (NFWF) to develop an evaluation system help NFWF gauge impact across the various coral reef habitat and species conservation projects; In 2007, FOS worked with the Ocean Conservancy (OC) to evaluate the effectiveness of this Scorecard in helping to end overfishing in domestic fisheries. Between 1999 and 2004, FOS worked for WWF's Asian Rhino and Elephant Action Strategy (AREAS) Program to ensure that Asian elephants and rhinos thrive in secure habitats within their historical range and in harmony with people. The Department of Fish and Game (DFG) is developing and implementing adaptation strategies to help protect, restore and manage fish and wildlife, with the understanding that some level of climate change will occur and that it will have profound effects on ecosystems in the United States. The Adaptive Management program was created by CMR to provide science-based recommendations and technical information to assist the Forest Practices Board. In April 2010, the Forest Practices Adaptive Management Annual Science Conference was held in Washington. In 2009, The Louisiana Coastal Protection and Restoration (LACPR) Technical Report has been developed by the United States Army Corps of Engineers (USACE) according to adaptive management process. Since 2009, the Kenya Wildlife Service has been managing its marine protected areas using adaptive management in an ongoing process of learning through the Science for Active Management (SAM)Science for Active Management Program.
In international development