Adaptive Management

Introduction

Wise management practices provide the framework to envision and actualize a successful river or watershed restoration project. Adaptive management (AM) has evolved as restoration practitioners and organizations realize the need to have flexible management that can respond to actual conditions in the field as restoration projects progress.

AM is employed because it is a structured management style that focuses on “learning by doing” so that restoration projects meet the team’s **objectives** and are successful in action (Williams, Szaro, & Shapiro, 2009). Using AM “compels resource managers to say, "I don't know which actions best achieve my management objectives, so I am going to proceed in a manner to help me learn just that” (Murray & Marmorek).

This experimental approach incorporates flexible project design and includes scientific monitoring and evaluation protocols. With this collaborative, community-driven approach, managers, scientists, engineers, and stakeholders cooperate to improve a river or watershed systematically, with minimal risk. It is especially effective in instances where there is a high degree of management uncertainty. Still, successfully implementing AM requires a significant investment of organizational time and resources.

A successful AM approach requires that certain conditions be met: (1) feasibility for conducting a test of management actions, (2) potential for learning about action effectiveness within a reasonable time frame, (3) acceptable risk from failure of those tests, and (4) flexibility to change management practices based on what is learned.

How Is AM Unique?

AM is different from traditional research, equilibrium-based approaches, or top-down institutional management. Traditional research focuses on uncovering information, while AM emphasizes management and seeks data that will improve management capacity. In the past, equilibrium-based approaches focused on maintaining a system at an optimal state that often reduced its ability to respond to stressors. These traditional approaches have tended to fail when applied to large, complex systems; it is likely AM is more effective in these situations (Johnson, 1999). AM also reverses a top-down, institutional approach to management. It is a collaborative, bottom-up approach that involves collaboration among multiple stakeholders (Gerlak, 2008).

In addition, AM embraces uncertainty and replaces the previous paradigm, in which managers have felt an unspoken institutional stigma against acknowledging uncertainty in environmental assessments and management strategies (Williams, Szaro, and Shapiro, 2009). An AM approach encourages exploration and responsiveness in restoration project design to create an expanding base of knowledge that will support current and future decision-making. And, because it accepts that there are unknown aspects of river and watershed management, AM is especially effective in large, complex ecosystems.

History of AM

C.S. Holling and C. Walters first applied AM to natural resources management in the 1970s. AM was initially applied to fisheries management, then more broadly applied to restoration and conservation projects in the 1990s and 2000s. The National Research Council endorsed AM for ecosystem restoration in 1992. Today, the U.S. Army Corps of Engineers and the U.S. Bureau of Reclamation follow an AM approach in several U.S. ecosystems, including the Everglades (Gerlak, 2008). AM has also been used with Glen Canyon Dam, Columbia River salmonids, the New Brunswick forest, North American waterfowl harvest, and the Colorado River (Johnson, 1999).

Applying Active Management Principles
Six Steps of Adaptive Management

AM encompasses six steps (Figure 1) that aim to systematically allow restoration practitioners to evaluate alternative actions while minimizing risk and reducing critical uncertainties.

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Figure 1. Adaptive Management Process, U.S. Department of the Interior

**Assessment** involves identifying goals and objectives, potential management decisions and uncertainties, hypotheses and conceptual models, management actions, and spatial and temporal bounds. At this point, practitioners identify the available “decision space,” which includes the range of decisions facing managers and the degree of flexibility they have in making these decisions. Managers create strategies to work within the bounds of policy restrictions and requirements. At this stage, stakeholder workshops, computer simulation models, conceptual models, hypotheses, and decision analysis are all useful tools (Murray & Marmorek).

Design entails creating a powerful experimental design that includes contrasts, controls, and replication. Because of the variability of a natural system and the complexity of hypotheses being tested, it can be challenging to implement an ideal experimental design. Still, managers can work to create estimates of anticipated outcomes of various alternative actions, explore which are most likely to offer resolution, determine the feasibility of monitoring outcomes, and analyze cost versus benefit. The design must also be activated within the context of a complex natural ecosystem, existing water management infrastructure, and operational rules and constraints (Murray, Smith, & Marmorek, 2011).

Implementation is the step when the plan is put into action. It is imperative that the individuals responsible for implementation understand the logic of the restoration plan and adhere to it (Murray & Marmorek).

Monitoring typically falls into three categories. Implementation monitoring determines if actions are being implemented according to design requirements and standards. Effectiveness monitoring checks physical habitat indicators to determine if management actions are achieving performance criteria. Validation monitoring monitors specific indicators to determine overall progress toward biological objectives (Murray, Smith, & Marmorek, 2011).

Evaluation includes analysis of collected data and synthesis of numerous analyses to determine how well management strategies are working within the river or watershed. At this stage, nonworking hypotheses can be rejected (Murray & Marmorek).

Finally, adjustment involves using what has been learned to make more effective decisions (Murray, Smith, & Marmorek, 2011).

Active and Passive Adaptive Management

AM can be approached actively or passively. Through active AM, several alternatives are implemented concurrently to see which is the best approach. Active AM requires an initial investment of time, labor, and funds, but learning happens quickly since multiple alternatives are tested (Murray & Marmorek).

In passive AM, managers choose the apparent best option and implement it, then monitor to see if their assumption is correct and make adjustments if need be. While passive AM may be less expensive and require fewer people initially, if managers have made incorrect assumptions, it can take longer to determine the best course of action (Murray & Marmorek).

Adaptive Management in Action
Comprehensive Everglades Restoration Plan

Canals and levees constructed in the Everglades under the 1948 Central and South Florida Project resulted in an interruption in historic flow patterns, increased discharge of water to the ocean, and created scarcity/overabundance extremes within the system. **Water quality** has also deteriorated over time as untreated wastewater is discharged into the wetland system (RECOVER, 2010).

The 1992 Water Resources Development Act authorized the Corps of Engineers to reassess the South Florida Project. After a series of public meetings, Congress approved the 30-year, $10.5 billion Comprehensive Everglades Restoration Plan (CERP) in 2000. CERP is “the largest environmental restoration effort in history” (US Army Corps, 2005). The overarching objective of CERP is to restore, preserve, and protect the South Florida ecosystem while providing for other water-related needs of the region, including water supply and flood protection (Figure 2; Kurzbach & Ogden, 2006).

Two documents guide AM in the Florida Everglades. The Comprehensive Everglades Restoration Plan (CERP) AM Strategy gives a high-level framework for applying AM in the Everglades, and the CERP AM Integration Guide “helps project teams, managers, scientists, and other shareholders use AM to make decisions” by identifying key uncertainties and incorporating AM into existing CERP plans and processes (Murray, Smith, & Marmorek, 2011).

The management team anticipates using a primarily passive AM approach for the Everglades restoration projects. AM was chosen to reduce scientific/technical and policy/management uncertainties, such as uncertainty in how to assess the impact of stressors on the ecosystem or funding constraints (Murray, Smith, & Marmorek, 2011).

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Figure 2. Comprehensive Everglades Restoration Plan, from CERP

The plan includes more than 50 individual projects, such as creating water storage reservoirs, removing manmade barriers to water flow, developing treatment marshes, and reducing underground seepage. By 2005, the U.S. Army Corps of Engineers and their partners had made progress on 19 of these projects. Each project is prioritized and banded into a five-year timeframe.

True to the collaborative aspect of AM, CERP seeks to actively involve the public through workshops and events. Low-income and minority individuals, as well as non-English speakers, are also targeted (US Army Corps, 2005).

CERP includes nine activities as part of its AM process: (1) Collaborative Planning, (2) Establishing Restoration Goals and Objectives, (3) Identifying and Prioritizing Priorities, (4) Applying Models and Developing Hypotheses and Performance Measures, (5) Alternative Plan Development and Implementation, (6) Monitoring, (7) Assessment, (8) Feedback, and (9) Adjustment (Murray, Smith, & Marmorek, 2011).

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Figure 3. Florida Everglades, from CERP


Middle Rio Grande Endangered Species Collaborative

AM is also being used locally by the Middle Rio Grande Endangered Species Collaborative (MRGESC). In 2011, MRGESC released version one of its AM plan to ascertain “the effectiveness of various management actions related to the silvery minnow and flycatcher.” The plan will be continuously refined. Version two will include clear action proposals.

The MRGESC intends to alleviate jeopardy to the silvery minnow and flycatcher, contribute to the recovery of these species, and protect existing and future water uses. Critical uncertainties in the **Middle Rio Grande** (MRG) include: (1) variation in silvery minnow abundance, reproduction, survival, and spatial distribution as a function of hydrological and habitat parameters, (2) the form of the spawning-recruitment relationship, (3) response of the population age structure and genetic diversity to AM treatments, (4) estimating probability of extinction and recovery, and (5) how flycatcher habitat use, nest success, fledge ratio, and nest location vary as a function of hydrological and habitat parameters.

Because of the nature of the MRG, an AM approach cannot include the deliberate creation of large flow contrasts and instead must rely on natural variability to provide large contrasts in flow. This passive AM approach can still use contrasting conditions “across both space (i.e., Cochiti, Albuquerque, Isleta and San Acacia reaches, as well as finer scale examinations of particular habitat areas) and time (i.e., across water years and seasonal differences within years) to estimate various performance measures and parameters that reflect silvery minnow and flycatcher responses to AM actions and to evaluate the outcomes of tests or specific hypotheses related to critical uncertainties outlined in the AM plan” (Murray, Smith, & Marmorek, 2011).

The MRGESC plan includes re-assessment seasonally, annually, and after several years (Murray, Smith, & Marmorek, 2011).

Barriers to Implementing AM

While AM improves management flexibility and allows restoration practitioners to address uncertainty in complex ecosystems, it is a time- and resource-intensive management approach. Because it requires intensive monitoring over an extended period of time, AM is unlikely to be implemented if the restoration team lacks long-term stability, funding, or human resources. For example, because AM requires a wide variety of skilled professionals to interact on a regular basis to develop, implement, monitor, assess, and change the project design. A restoration team will be unable to use AM if they lack regular access to individuals with the right technical skills.

AM can also be a complex process that attempts to engage multiple stakeholders. It is pivotal that the restoration team be well organized so that all participants remain on the same page with the project. An inability to keep all interested parties up to date or ensure that everyone is operating from the same set of standards may prevent AM from being used successfully.

Conclusion

AM improves on past management styles by embracing uncertainty and incorporating the expertise of a diverse body of stakeholders. Because it is a flexible approach, restoration practitioners can learn as they go and determine the best management approach for a given ecosystem based on its response to their actions.

Passive AM is currently being used in the MRG and the Florida Everglades with some signs of success. While AM in the MRG is still in its infancy, multiple restoration projects have been implemented in the Everglades, and the Florida team has clear objectives for implementing future projects. Both teams have created organizational clarity by collaborating with various stakeholders to create manuals that will guide the restoration projects in their respective ecosystems.

Ideally, restoration practitioners who are using an AM approach will continue to clearly document the outcomes of their projects and provide these in a public forum so that natural resource managers worldwide can benefit from their successes and failures.

References

Gerlak, A. (2008). “Today’s pragmatic water policy: restoration, collaboration, and adaptive management along US rivers.” Society and Natural Resources, 21:538-545.

Johnson, B. L. (1999). “The role of adaptive management as an operational approach for resource management agencies.” Ecology and Society, 3.2.

Kurzbach, E., & Ogden, J. (2006). “Comprehensive Everglades Restoration Plan Adaptive Management Strategy.”

Murray, C., & Marmorek, D. “Adaptive Management and Ecological Restoration.” Conducting Restoration.

Murray, C., Smith, C., & Marmorek, D. (2011). “Middle Rio Grande Endangered Species Collaborative Adaptive Management Plan Version 1.” From http://www.middleriogrande.com/Default.aspx?tabid=460

RECOVER, 2010. CERP Adaptive Management Integration Guide. Restoration Coordination and Verification, C/O U.S. Army Corps of Engineers, Jacksonville District, Jacksonville, FL and South Florida Water Management District, West Palm Beach, FL.

US Army Corps of Engineers. (2005). “Comprehensive Everglades Restoration Plan: The First Five Years.”
Williams, B., Szaro, R., and Shapiro, C. (2009). “Adaptive Management: The US Department of the Interior Technical Guide.” Adaptive Management Working Group.