Adaptive management, also called adaptive resource management or adaptive environmental assessment and management, is a step-by-step process that repeats over time to help make strong, thoughtful decisions when information is limited. This method uses system monitoring to reduce uncertainty over time. It helps achieve goals related to managing resources while gathering information that improves future decisions. Adaptive management is a tool used not only to change a system but also to understand it better. Because it focuses on learning, it leads to better long-term results. The challenge is finding the right balance between gaining knowledge for future improvements and achieving the best short-term results with current knowledge. This approach has recently been used in international development programs.

Objectives

Adaptive management involves several important scientific and social steps, including:

• Management decisions are connected to the right time frames and areas
• Management uses data and methods to ensure accurate results
• Computer models help create shared understanding of ecosystems
• Shared understanding of ecosystems is used to compare different plans
• Options are shared with leaders to discuss and choose the best plan

To reach these goals, the management process must be open and include people who have been, are, or may be involved in the future. Adaptive management needs to keep political discussions open, and often aims to make them more open. Because of this, adaptive management must be both a scientific and social process. It should focus on creating new rules and strategies that work well with scientific ideas and experiments (resilience.org).

Adaptive management can be either passive or active, depending on how learning happens. Passive adaptive management only values learning if it helps improve decisions, as measured by a specific goal. In contrast, active adaptive management treats learning as an important goal itself. Decisions that help learning are valued more than those that do not. In both cases, when new knowledge is gained, models are updated and the best management plans are chosen. While learning happens in both types, it is handled differently. Often, creating active adaptive plans is very difficult, which is why it is not used more often.

Features

Key features of both passive and active adaptive management include:

• Repeating steps to improve decisions by reviewing results and changing actions based on what is learned
• Using information from monitoring to help make better decisions (learning from experience)
• Clearly explaining uncertainty in systems by using multiple models to compare different possibilities
• Using a method called Bayesian inference to update understanding with new information
• Accepting uncertainty and risk as part of the process to improve knowledge

However, problems with how information is shared can stop adaptive management from working well:

• Not all data is collected as planned
• Data is collected but not studied
• Data is studied, but the results are unclear or not helpful
• Data is studied and shared, but decision makers do not see it
• Data is studied and shared, but it is not used for decisions because of inside or outside reasons

History

The use of adaptive management techniques can be traced back to people in ancient civilizations. For example, the Yap people of Micronesia have used these techniques for thousands of years to support large populations despite limited resources (Falanruw 1984). By using these methods, the Yap people have changed their environment, such as creating coastal mangrove depressions and seagrass meadows, to help with fishing and to find wood that is resistant to termites (Stankey and Shinder 1997).

The idea of adaptive management began with scientific management concepts introduced by Frederick Taylor in the early 1900s (Haber 1964). The term "adaptive management" was later developed during natural resource management workshops where decision makers, managers, and scientists worked together to build models that helped identify important assumptions and unknown factors (Bormann et al. 1999).

Two ecologists at The University of British Columbia, C.S. Holling and C.J. Walters, helped shape the adaptive management approach by explaining the difference between passive and active practices. Kai Lee, a physicist from Princeton, further improved the method during the late 1970s and early 1980s while completing a post-doctorate at UC Berkeley. The method was also developed at the International Institute for Applied Systems Analysis (IIASA) in Vienna, Austria, when C.S. Holling led the institute. In 1992, Hilbourne described three learning models for federal land managers—reactive, passive, and active—that could guide adaptive management practices.

Adaptive management has been most commonly used in Yap, Australia, and North America. It was first applied to fishery management but became more widely used in the 1990s and 2000s. One of the most successful examples of adaptive management is in waterfowl harvest management in North America, especially for mallards.

Adaptive management in conservation projects and programs began in the early 1990s with the creation of the Biodiversity Support Program (BSP) in 1989. BSP was a USAID-funded group that included WWF, The Nature Conservancy (TNC), and the World Resources Institute (WRI). Its Analysis and Adaptive Management Program aimed to understand when certain conservation strategies were most effective and to share lessons from different projects. After BSP ended in 2001, TNC and Foundations of Success (FOS), a non-profit group formed from BSP, continued to promote adaptive management. Their methods included Conservation by Design (TNC) and Measures of Success (FOS).

In 2004, the Conservation Measures Partnership (CMP)—a group that includes former members of BSP—developed shared standards and guidelines for using adaptive management in conservation projects and programs.

Use in environmental practices

Applying adaptive management in a conservation or ecosystem project means combining the planning, managing, and monitoring of the project to test ideas in a planned way. This helps people adjust and learn over time. The three parts of adaptive management in environmental work are:

• Testing assumptions means trying different actions to reach a goal. It is not just trying things randomly. Instead, it uses what is known about the area to choose the best strategy, explains the ideas behind how that strategy might work, and then collects data to see if the ideas are correct.
• Adaptation means changing plans or actions based on new information learned from monitoring or past project experiences.
• Learning means clearly recording the team’s planning, actions, and results—both what worked and what did not. This helps the team and others in the conservation field improve future projects and avoid problems others have faced. Learning is only helpful if the same management choices are used again in the future.

Application to environmental projects and programs

The Open Standards for the Practice of Conservation outlines five main steps in an adaptive management project cycle (see Figure 1). These standards combine and adjust best practices and guidelines from various fields and organizations within the conservation community. Since the first version of the Open Standards was released (updated to version 5.0 in 2025), many project teams from conservation organizations (such as TNC, Rare, and WWF), local groups, and donors have used these standards in their work. Additionally, several CMP members have created training materials and courses to help others apply the standards effectively.

Recent examples of adaptive management in conservation include wildlife protection (SWAP, 2008), forest ecosystem protection (CMER, 2010), coastal protection and restoration (LACPR, 2009), natural resource management (water, land, and soil), species conservation (especially fish conservation to prevent overfishing, FOS, 2007), and climate change (DFG, 2010). Other examples include:

• In 2006–2007, FOS partnered with The National Fish and Wildlife Foundation (NFWF) to create an evaluation system to measure the impact of coral reef habitat and species conservation projects.
• In 2007, FOS worked with the Ocean Conservancy (OC) to test the effectiveness of a Scorecard in helping reduce overfishing in domestic fisheries.
• Between 1999 and 2004, FOS supported WWF's Asian Rhino and Elephant Action Strategy (AREAS) Program to ensure Asian elephants and rhinos live in safe habitats within their historical range and coexist with people.
• The Department of Fish and Game (DFG) is developing and using strategies to protect, restore, and manage fish and wildlife, recognizing that climate change will affect ecosystems in the United States.
• The Adaptive Management program, created by CMR, provides science-based recommendations and technical information to help 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 was developed by the United States Army Corps of Engineers (USACE) using the adaptive management process.
• Since 2009, the Kenya Wildlife Service has used adaptive management to manage marine protected areas through the Science for Active Management (SAM) Program, learning and improving over time.

In international development

Adaptive management is a method used not only for managing natural resources and ecosystems but also in international development programs. This approach is often used because many development challenges are complex and traditional planning methods have limitations. A major change for international development organizations is the need to be more flexible, adaptable, and focused on learning. This idea is seen in development approaches like Doing Development Differently, Politically Informed Programming, and Problem Driven Iterative Adaptation.

An example of adaptive management in international development is the Global Learning for Adaptive Management (GLAM) program. This program aims to support adaptive management practices within the Department for International Development and USAID by creating a center for learning about these methods. Donors are also updating their program guidelines to emphasize the importance of learning, such as USAID’s recent focus on collaboration, learning, and adaptation in its ADS guidance. Similarly, the Department for International Development’s Smart Rules provide a framework for programs that use evidence to guide decisions. Tools like learning agendas and decision cycles are used to apply adaptive management in programs.

Collaborating, learning, and adapting (CLA) is a method used to implement adaptive management in international development. It describes a way to design, carry out, adjust, and evaluate programs. CLA includes three key ideas:
1. Working intentionally with stakeholders to share knowledge and avoid repeating efforts,
2. Learning systematically by using evidence from different sources and reflecting on program implementation, and
3. Adapting strategically based on lessons learned.

Studies show that organizations using data-driven and adaptive practices perform better than those that do not. CLA connects three related ideas in organizational theory: collaborating, learning, and adapting. Research shows that collaboration within and between organizations helps produce and share knowledge, including both knowledge that is written down and knowledge gained through experience. Collaboration is important for innovation and learning, as seen in the benefits of staff working together and sharing ideas. The ability of organizations to learn from each other is a key part of what is called a "learning organization" in the literature.

CLA is a practice used by organizations funded by the U.S. federal government, but it is mainly a framework for internal changes within USAID, including its global missions. CLA is part of USAID’s effort to become a learning organization. It combines strategic collaboration, continuous learning, and adaptive management. Tools like the Learning Lab are provided to USAID staff and partners to support CLA. The CLA approach is detailed in USAID’s updated program policy guidance.

Use in other practices as a tool for sustainability

Adaptive management is an organized method used to improve how people care for the environment. This method is often used in environmental policies, but it can also help other areas, like businesses and communities, find ways to be more sustainable. Adaptive management focuses on changing with the environment and learning from actions taken. Using this method in ecosystems makes sense because the environment is always changing. The ability to be flexible and keep learning is also useful for organizations that want to use sustainable practices. Businesses that aim for sustainability might use adaptive management to prepare for unexpected events and stay ready for change. When a business uses adaptive management, it works like a connected system that adjusts and learns from many different factors, including the environment, economy, and society (Dunphy, Griffiths, & Benn, 2007). The goal of a sustainable organization using adaptive management is to actively learn and guide changes toward sustainability (Verine, 2008). This idea, called "learning to manage by managing to learn" (Bormann, 1993), becomes the main part of a business's strategy for sustainability.

Creating sustainable communities requires understanding how the environment, economy, and social systems in a community work together. Using adaptive management to develop community policies and practices also highlights the connection between these elements. Looking at cultural traditions that shape a community's values often shows similarities to adaptive management, which focuses on learning from feedback and dealing with uncertainty (Berkes, Colding, & Folke, 2000). These traditions often come from indigenous knowledge and past decisions made by societies that lived closely with nature (Berkes, Colding, & Folke, 2000). When adaptive management is used in community development, systems can be designed to include sustainable practices. As explained by the Environmental Advisory Council (2002), "active adaptive management sees policies as experiments to understand how to build or keep resilience. It needs and helps create a social environment with flexible and open systems that allow learning and improve the ability to adapt without limiting future choices" (p. 1121). A real example of using adaptive management for sustainability was a project on tribal lands. Researchers used tools like artvoice, photovoice, and agent-based modeling in a group effort to solve the problem of illegal trash dumping. They tested ideas using a computer model called NetLogo to imagine a "regional cooperative clean-energy economy." This plan combined traditional recycling with a process that turns non-recyclable trash into ethanol fuel. This method was inspired by the work of a Canadian company called Enerkem (Bruss, 2012 – PhD dissertation: Human Environment Interactions and Collaborative Adaptive Capacity Building in a Resilience Framework, GDPE Colorado State University).

In a world that is always changing, adaptive management helps many areas find sustainable solutions. It offers a way to make decisions that support a future where "diversity in species, human opportunities, learning institutions, and economic choices" is protected and cared for (The Environmental Advisory Council, 2002, p. 1121).

Effectiveness

Testing how well adaptive management works is hard compared to other management methods. A challenge is that once a system is managed using one approach, it is hard to know how another approach would have worked in the same situation. One study compared formal passive adaptive management with human intuition by asking natural resource management students to decide how to harvest a pretend fish population in an online computer game. On average, the students did worse than computer programs using passive adaptive management.

Collaborative adaptive management is often praised as a good way to handle natural resource management when there are high levels of conflict, uncertainty, and complexity. However, these efforts can face challenges from both social and technical issues. For example, the Glenn Canyon Dam Adaptive Management Program in the US shows that successful collaborative adaptive management needs clear and measurable goals, tools to encourage teamwork, long-term plans for monitoring and adapting, and simple rules for shared fact-finding. In Colorado, USA, a ten-year experiment started in 2012 at the Agricultural Research Service (ARS) Central Plains Experimental Range tested how well collaborative adaptive management works on rangelands. The Collaborative Adaptive Rangeland Management (CARM) project tracks results from yearling steer grazing on 10, 130 ha pastures managed by a group of conservationists, ranchers, public employees, and researchers. This team compares data about ecological health, profitability, and conservation outcomes with results from a "traditional" management method: ten other pastures managed without adaptive decision-making but with the same number of animals. Early findings from social scientists suggest that trust is essential for learning in adaptive management, not just a side benefit. Also, having a lot of monitoring data or large-scale efforts does not automatically lead to successful collaboration. Building trust between scientists and stakeholders over time is important. Lastly, it is necessary to understand, share, and respect different types of knowledge, including local ecological knowledge used by people who live and work in the area. Practitioners should expect adaptive management to be a complex and not straightforward process influenced by social, political, and ecological factors, as well as how data is collected and interpreted.

General resources

Information and guidance about the adaptive management process can be found on websites of CMP members and other online sources:

• The Conservation Measures Partnership's Open Standards for the Practice of Conservation offer basic advice and rules for using adaptive management in conservation work.
• Miradi Adaptive Management Software for Conservation Projects is an easy-to-use tool created by CMP and Benetech. It helps conservation teams follow each step of the Open Standards.
• Foundations of Success (FOS) Resources and Training web pages provide reference materials about adaptive management and monitoring and evaluation, as well as details about online or in-person courses on adaptive management.
• The Nature Conservancy's Conservation Action Planning (CAP) Resources page includes detailed instructions and tools for using the CAP adaptive management process. See also TNC's CAP Standards.
• The Wildlife Conservation Society's Living Landscapes page contains detailed guidance on WCS's method for adaptive management.
• WWF's web page on the WWF Standards of Conservation Project and Programme Management includes detailed instructions, resources, and tools for each step in WWF's adaptive management process.
• Measures of Success: Designing, Managing, and Monitoring Conservation and Development Projects, written in 1998 by Richard Margoluis and Nick Salafsky, was one of the first detailed guides on applying adaptive management to conservation projects. Also available in Spanish.
• Foundations of Success (FOS) web pages list the Asian Rhino and Elephant Program Evaluation from 2004.
• Foundations of Success (FOS) web pages list the National Fish & Wildlife Foundation's Coral Fund from 2007.
• Foundations of Success (FOS) web pages list Ocean Conservancy's Overfishing Scorecard from 2007.
• The Department of Fish and Game (DFG) web pages list the Adapting to Climate Change programme.
• U.S. Army Corps of Engineers web pages list the Louisiana Coastal Protection and Restoration Final Technical Report from 2009.
• Washington State Department of Natural Resource (CMR) web pages list the Forest Practices Adaptive Management Program from 2010.