Adaptive management

Adaptive management (AM), also known as adaptive resource management (ARM) or adaptive environmental assessment and management (AEAM), 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.[1] 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.[2] This approach has more recently been employed in implementing international development programs.


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 (

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.[1][3] 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.[4]


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:[5]

  • 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


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[1] and C.J Walters[3] 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.[6]

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)[7] in 1989. BSP was a USAID-funded consortium of WWF[8] The Nature Conservancy (TNC),[9] and World Resources Institute (WRI).[10] 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[11] (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[12] (TNC) and Measures of Success[13] (FOS).

In 2004, the Conservation Measures Partnership (CMP)[14] – which includes several former BSP members – developed a common set of standards and guidelines[15] 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:

  • 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.[16] Learning about a managed system is only useful in cases where management decisions are repeated.[17]

Application to environmental projects and programs

CMP Cycle - 2008-02-20
Figure 1: CMP Adaptive Management Cycle

Open Standards for the Practice of Conservation[18] 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 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:

  • 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 1999–2004, 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)[19] Program.

In international development

The concept of adaptive management is not restricted to natural resources or ecosystem management, as similar concepts have been applied to international development programming.[20][21] This has often been a recognition to the "wicked" nature of many development challenges and the limits of traditional planning processes.[22][23][24] One of the principal changes facing international development organizations is the need to be more flexible, adaptable and focused on learning.[25] This is reflected in international development approaches such as Doing Development Differently, Politically Informed Programming and Problem Driven Iterative Adaptation.[26][27][28]

One recent example of the use of adaptive management by international development donors is the planned Global Learning for Adaptive Management (GLAM) programme to support adaptive management in Department for International Development and USAID. The program is establishing a centre for learning about adaptive management to support the utilization and accessibility of adaptive management.[29][30] In addition, donors have been focused on amending their own programmatic guidance to reflect the importance of learning within programs: for instance, USAID's recent focus in their ADS guidance on the importance of collaborating, learning and adapting.[31][32] This is also reflected in Department for International Development's Smart Rules that provide the operating framework for their programs including the use of evidence to inform their decisions.[33] There are a variety of tools used to operationalize adaptive management in programs, such as learning agendas and decision cycles.[34]

Collaborating, learning and adapting (CLA) is a concept related to the operationalizing of adaptive management in international development that describes a specific way of designing, implementing, adapting and evaluating programs.[35]:85[36]:46 CLA involves three concepts:

  1. collaborating intentionally with stakeholders to share knowledge and reduce duplication of effort,
  2. learning systematically by drawing on evidence from a variety of sources and taking the time to reflect on implementation, and
  3. adapting strategically based on applied learning. CLA practices have tangible benefits; for instance, a recent study recently found that companies "which apply more data-driven and adaptive leadership practices perform better" when examined against those which focus less on those practices.[37]

CLA integrates three closely connected concepts within the organizational theory literature: namely collaborating, learning and adapting. There is evidence of the benefits of collaborating internally within an organization and externally with organizations.[38] Much of the production and transmission of knowledge—both explicit knowledge and tacit knowledge—occurs through collaboration.[39] There is evidence for the importance of collaboration among individuals and groups for innovation, knowledge production, and diffusion—for example, the benefits of staff interacting with one another and transmitting knowledge.[40][41][42] The importance of collaboration is closely linked to the ability of organizations to collectively learn from each other, a concept noted in the literature on learning organizations.[43][44][45]

CLA, an adaptive management practice, is being employed by implementing partners[46][47] that receive funding from the federal government of the United States,[48][49][50] but it is primarily a framework for internal change efforts that aim at incorporating collaboration, learning, and adaptation within the United States Agency for International Development (USAID) including its missions located around the world.[51] CLA has been linked to a part of USAID's commitment to becoming a learning organization.[52] CLA represents an approach to combine strategic collaboration, continuous learning, and adaptive management.[53] A part of integrating the CLA approach is providing tools and resources, such as the Learning Lab, to staff and partner organizations.[54] The CLA approach is detailed for USAID staff in the recently revised program policy guidance.[31]

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).


It is difficult to test the effectiveness of adaptive management in comparison to other management approaches. One challenge is that once a system is managed using one approach it is difficult to determine how another approach would have performed in exactly the same situation.[55] One study tested the effectiveness of formal passive adaptive management in comparison to human intuition by having natural resource management students make decisions about how to harvest a hypothetical fish population in an online computer game. The students on average performed poorly in comparison to the computer programs implementing passive adaptive management.[55][56]

Collaborative adaptive management is often celebrated as an effective way to deal with natural resource management under high levels of conflict, uncertainty and complexity.[57] The effectiveness of these efforts can be constrained by both social and technical barriers. As the case of the Glenn Canyon Dam Adaptive Management Program in the US illustrates, effective collaborative adaptive management efforts require clear and measurable goals and objectives, incentives and tools to foster collaboration, long-term commitment to monitoring and adaptation, and straightforward joint fact-finding protocols.[58] In Colorado, USA, a ten-year, ranch-scale (2590 ha) experiment began in 2012 at the Agricultural Research Service (ARS) Central Plains Experimental range to evaluate the effectiveness and process of collaborative adaptive management [57] on rangelands. The Collaborative Adaptive Rangeland Management or “CARM” project monitors outcomes from yearling steer grazing management on 10, 130 ha pastures conducted by a group of conservationists, ranchers, and public employees, and researchers. This team compares ecological monitoring data tracking profitability and conservation outcomes with outcomes from a “traditional” management treatment: a second set of ten pastures managed without adaptive decision making but with the same stocking rate. Early evaluations of the project by social scientists offer insights for more effective adaptive management.[59] First, trust is primary and essential to learning in adaptive management, not a side benefit. Second, practitioners cannot assume that extensive monitoring data or large-scale efforts will automatically facilitate successful collaborative adaptive management. Active, long-term efforts to build trust among scientists and stakeholders are also important. Finally, explicit efforts to understand, share and respect multiple types of manager knowledge, including place-based ecological knowledge practiced by local managers, is necessary to manage adaptively for multiple conservation and livelihood goals on rangelands.[59] Practitioners can expect adaptive management to be a complex, non-linear process shaped by social, political and ecological processes, as well as by data collection and interpretation.

General resources

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

  • The Conservation Measures Partnership's Open Standards for the Practice of Conservation provide general guidance and principles for good adaptive management in conservation.
  • Miradi Adaptive Management Software for Conservation Projects is user friendly software developed through a joint venture between CMP and Benetech. The software walks conservation teams through each step of the Open Standards.
  • Foundations of Success (FOS) Resources and Training web pages list reference materials on adaptive management and monitoring and evaluation, as well as information about online or in-person courses in adaptive management.
  • The Nature Conservancy's Conservation Action Planning (CAP) Resources page includes detailed guidance and tools for implementing the CAP adaptive management process. See also TNC's CAP Standards.
  • The Wildlife Conservation Society's Living Landscapes page contains extensive guidance materials on WCS's approach to adaptive management.
  • WWF's web page on the WWF Standards of Conservation Project and Programme Management contains detailed guidance, resources, and tools for the steps 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 manuals about applying adaptive management to conservation projects. Also available in Spanish.
  • Foundations of Success (FOS) web pages list Asian Rhino and Elephant Program Evaluation in 2004.
  • Foundations of Success (FOS) web pages list National Fish & Wildlife Foundation's Coral Fund in 2007.
  • Foundations of Success (FOS) web pages list Ocean Conservancy's Overfishing Scorecard in 2007.
  • The Department of Fish and Game (DFG) web pages list Adapting to Climate Change programme.
  • U.S. Army Corps of Engineers web pages list Louisiana Coastal Protection and Restoration Final Technical Report in 2009.
  • Washington State Department of Natural Resource (CMR) web pages list Forest Practices Adaptive Management Program in 2010.

See also


  1. ^ a b c Holling, C.S. (1978). Adaptive Environmental Assessment and Management. John Wiley & Sons. ISBN 9781932846072.
  2. ^ Allan, Catherine; Stankey, George Henry (2009-06-05). Adaptive Environmental Management: A Practitioner's Guide. Springer Science & Business Media. ISBN 9781402096327.
  3. ^ a b 1944-, Walters, Carl J. (1986-01-01). Adaptive management of renewable resources. Macmillan. ISBN 978-0029479704. OCLC 13184654.
  4. ^ Carey, Gemma; Crammond, Brad; Malbon, Eleanor; Carey, Nic (2015-09-18). "Adaptive Policies for Reducing Inequalities in the Social Determinants of Health". International Journal of Health Policy and Management. 4 (11): 763–767. doi:10.15171/ijhpm.2015.170. ISSN 2322-5939. PMC 4629702. PMID 26673337.
  5. ^ L, Elzinga, Caryl; W, Salzer, Daniel; W, Willoughby, John (1998-01-01). "Measuring & Monitering Plant Populations". U.s. Bureau of Land Management Papers.
  6. ^ Nichols, James D.; Johnson, Fred A.; Williams, Byron K.; Boomer, G. Scott (2015-06-01). "On formally integrating science and policy: walking the walk". Journal of Applied Ecology. 52 (3): 539–543. doi:10.1111/1365-2664.12406. ISSN 1365-2664.
  7. ^ Biodiversity Support Program
  8. ^ WWF
  9. ^ The Nature Conservancy
  10. ^ World Resources Institute
  11. ^ Foundations of Success
  12. ^ Conservation by Design
  13. ^ Measures of Success
  14. ^ Conservation Measures Partnership
  15. ^ "Home".
  16. ^ Stankey, George H.; Clark, Roger N.; Bormann, Bernard T.; Stankey, George H.; Clark, Roger N.; Bormann, Bernard T. "Adaptive management of natural resources: theory, concepts, and management institutions".
  17. ^ Rout, Tracy M.; Hauser, Cindy E.; Possingham, Hugh P. (2009-03-01). "Optimal adaptive management for the translocation of a threatened species" (PDF). Ecological Applications. 19 (2): 515–526. doi:10.1890/07-1989.1. ISSN 1939-5582. PMID 19323207.
  18. ^ Open Standards for the Practice of Conservation
  19. ^ Science for Active Management
  20. ^ "2 Adaptive Management Theories, Frameworks, and Practices." National Research Council. 2004. Adaptive Management for Water Resources Project Planning. Washington, DC: The National Academies Press. doi: 10.17226/10972.
  21. ^ Rondinell, D. A. (1993) Development Projects as Policy Experiments: an adaptive approach to development administration, 2nd ed, Routledge, London and New York
  22. ^ Webber, M. and Rittel, H. (1973), "Dilemmas in a General Theory of Planning", Policy Sciences, vol. 4, no. 2, pp. 155-169.
  23. ^ Ramalingam, B., Laric, M. and Primrose, J. (2014) 'From Best Practice to Best Fit: Understanding and Navigating Wicked Problems in International Development'. Working Paper. London: ODI
  24. ^ Head, B. and Alford, J. (2008) "Wicked Problems: The Implications for Public Management", 12th Annual Conference International Research Society for Public Management, Vol. Panel on Public Management in Practice, 26–28 March 2008, Brisbane.
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  26. ^ Andrews, M., Pritchett, L. and Woolcock, M. (2015) Doing problem driven work. Working Paper 30. Cambridge, MA: Center for International Development at Harvard University.
  27. ^ Booth, D. and Unsworth, S. (2014) Politically smart, locally-led development. ODI discussion paper London: Overseas Development Institute.
  28. ^ Fritz, V., Levy, B., and Ort, R. (2014) Problem-driven political economy analysis: The World Bank's experience. Washington DC: World Bank.
  29. ^ Funds for NGOs. "DFID: Global Learning for Adaptive Management (GLAM) Programme". Retrieved April 19, 2017.
  30. ^ Oxfam "Adaptive Management at Oxfam". Retrieved May 25, 2017
  31. ^ a b USAID. "ADS Chapter 201 Program Cycle Operational Policy". Retrieved April 19, 2017.
  32. ^ USAID Learning Lab. "CLA". Retrieved April 19, 2017.
  33. ^ DFID. "DFID Smart Rules: Better Programme Deliver". Retrieved April 19, 2017.
  34. ^ "Knowing When to Adapt - A Decision Tree" Retrieved March 22, 2019
  35. ^ Altschuld, J. W., & Watkins, R. (2015). Needs assessment: trends and a view toward the future. New Directions for Evaluation, Number 144. Hoboken, NJ: John Wiley & Sons.
  36. ^ Janus, Steffen Soulejman. (2016). Becoming a knowledge-sharing organization: a handbook for scaling up solutions through knowledge capturing and sharing. Washington, D.C.: World Bank Group.
  37. ^ Akhtar, P., Tse, M., Khan, Z. and Rao-Nicholson, R. (2016) Data-driven and adaptive leadership contributing to the sustainability of global agri-food supply chains connected with emerging markets. International Journal of Production Economics, 181. pp. 392-401. ISSN 0925-5273.
  38. ^ Lab, Learning (2016-08-11). "Literature review of the evidence base for collaborating, learning, and adapting". USAID Learning Lab. Retrieved 2017-06-06.
  39. ^ For example: Polanyi, Michael (1966), The tacit dimension. Chicago: University of Chicago Press.
  40. ^ Kelly, Kip, and Schaefer, Alan (2014). "Creating a collaborative organizational culture". UNC White Paper.
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  42. ^ Hackman, J. R. (2002). Leading teams: setting the stage for great performances. Boston: Harvard Business School Press.
  43. ^ Garvin, David A. August 1993. "Building a learning organization." Harvard Business Review 71, no. 4: 78–91.
  44. ^ Senge, P. M. (1990). The fifth discipline: the art and practice of the learning organization. New York: Doubleday Business.
  45. ^ Argyris, C. and Schön, D. (1978) Organizational learning: a theory of action perspective, Reading, Mass: Addison Wesley.
  46. ^ "CLA Case Study 2015". USAID Learning Lab. Retrieved 2017-06-06.
  47. ^ "CLA Case Study 2016". USAID Learning Lab. Retrieved 2017-06-06.
  48. ^ Fintrac. "Collaborating, Learning and Adapting" Archived 2017-06-25 at the Wayback Machine. Retrieved April 19, 2017.
  49. ^ QED Group LLC. "Impact Stories: Collaborating, Learning and Adapting: Facilitating Agile Program Success Through CLA". Retrieved April 19, 2017.
  50. ^ Global Communities. (2016). M&E for "Collaboration, Learning and Adapting" in PACE.
  51. ^ USAID Learning Lab "Understanding CLA". Retrieved June 4, 2017.
  52. ^ OECD, 2016. Development Co-operation Peer Reviews: United States. doi:10.1787/9789264266971-en
  53. ^ USAID Learning Lab. "CLA". Retrieved April 19, 2017.
  54. ^ Borgen. "A Roadmap to USAID Learning Lab". Retrieved April 19, 2017
  55. ^ a b Holden, Matthew H.; Ellner, Stephen P. (2016-07-01). "Human judgment vs. quantitative models for the management of ecological resources". Ecological Applications. 26 (5): 1553–1565. arXiv:1603.04518. doi:10.1890/15-1295. ISSN 1939-5582. PMID 27755756.
  56. ^ Standard, Pacific (2016-03-11). "Sometimes, Even Bad Models Make Better Decisions Than People". Pacific Standard. Retrieved 2016-12-22.
  57. ^ a b Beratan, Kathi (2014-03-28). "Summary: Addressing the Interactional Challenges of Moving Collaborative Adaptive Management From Theory to Practice". Ecology and Society. 19 (1). doi:10.5751/ES-06399-190146. ISSN 1708-3087.
  58. ^ Susskind, Lawrence; Camacho, Alejandro E.; Schenk, Todd (2011-10-31). "A critical assessment of collaborative adaptive management in practice". Journal of Applied Ecology. 49 (1): 47–51. doi:10.1111/j.1365-2664.2011.02070.x. ISSN 0021-8901.
  59. ^ a b Wilmer, Hailey; Derner, Justin D.; Fernández-Giménez, María E.; Briske, David D.; Augustine, David J.; Porensky, Lauren M. (September 2018). "Collaborative Adaptive Rangeland Management Fosters Management-Science Partnerships". Rangeland Ecology & Management. 71 (5): 646–657. doi:10.1016/j.rama.2017.07.008. ISSN 1550-7424.


Carl Walters

Carl Walters (born 1944) is an American-born Canadian biologist known for his work involving fisheries stock assessments, the adaptive management concept, and ecosystem modeling. Walters has been a professor of Zoology and Fisheries at the University of British Columbia since 1969. He is one of the main developers of the ecological modelling software Ecopath. His most recent work focuses on how to adjust human behaviors in environments that are full of uncertainty. He is a recent recipient of the Volvo Environment Prize (2006).

Decision cycle

A decision cycle is a sequence of steps used by an entity on a repeated basis to reach and implement decisions and to learn from the results. The "decision cycle" phrase has a history of use to broadly categorize various methods of making decisions, going upstream to the need, downstream to the outcomes, and cycling around to connect the outcomes to the needs.

Earth systems engineering and management

Earth systems engineering and management (ESEM) is a discipline used to analyze, design, engineer and manage complex environmental systems. It entails a wide range of subject areas including anthropology, engineering, environmental science, ethics and philosophy. At its core, ESEM looks to "rationally design and manage coupled human-natural systems in a highly integrated and ethical fashion" ESEM is a newly emerging area of study that has taken root at the University of Virginia, Cornell and other universities throughout the United States. Founders of Earth Systems Engineering & Management are Braden Allenby and Michael Gorman.

In the UK, the Centre for Earth Systems Engineering Research (CESER) at Newcastle University has a large ESEM programme, led by Professor Richard Dawson.

Ecologically based invasive plant management

Ecologically-based invasive plant management (EBIPM) is a decision-making framework to improve the management of invasive plant species. When land managers are faced with infestations of invasive plants, a step by step framework to develop integrated management plans will improve their success at managing these plants. EBIPM is founded on the principles of ecology to manage invasive weed infestations and restore landscapes. The framework combines an ecosystem health assessment (Rangeland Health Assessment), a method to recognize how ecological processes affect causes of succession, ecological principles to guide the choices of tools and strategies to manage invasive plants and how to use adaptive management to generate a step-by-step decision model. The focus of EBIPM is to encourage managers to move away from simply killing the weeds and move toward management efforts that repair the underlying causes of invasion.EBIPM guides users through a 5-step process that begins with (step 1) an assessment of rangeland health to (step 2) determine why invasive species are present and what ecological processes are in need of repair. Managers can then (step 3) use ecological principles as targets to (step 4) choose the appropriate tools and strategies that will give them the best chances of successful and lasting results. The final step in the EBIPM process is to use adaptive management to design and implement a management plan.

Ecosystem management

Ecosystem management is a process that aims to conserve major ecological services and restore natural resources while meeting the socioeconomic, political, and cultural needs of current and future generations.The principal objective of ecosystem management is the efficient maintenance and ethical use of natural resources. It is a multifaceted and holistic approach which requires a significant change in how the natural and human environments are identified.

Several approaches to effective ecosystem management engage conservation efforts at both local and landscape levels and involve: adaptive management, natural resource management, strategic management, and command and control management.

Endangered species recovery plan

An endangered species recovery plan is a document describing the current status, threats and intended methods for increasing rare and endangered species population sizes. The U.S. Endangered Species Act of 1973 requires that all species considered endangered must have a plan implemented for their recovery, but the format is also useful when considering the conservation of any endangered species. Recovery plans act as a foundation from which you can build a conservation effort and they can help to make conservation more effective.

Environmental resource management

Environmental resource management is the management of the interaction and impact of human societies on the environment. It is not, as the phrase might suggest, the management of the environment itself. Environmental resources management aims to ensure that ecosystem services are protected and maintained for future human generations, and also maintain ecosystem integrity through considering ethical, economic, and scientific (ecological) variables. Environmental resource management tries to identify factors affected by conflicts that rise between meeting needs and protecting resources. It is thus linked to environmental protection, sustainability and integrated landscape management.

Great Darling Anabranch

The Great Darling Anabranch, commonly called the Darling Anabranch, is an anabranch and ancestral path of the Darling River in the lower Murray-Darling basin in the Far West and Riverina regions of New South Wales, Australia.

Institutional Learning and Change Initiative

Institutional Learning and Change (ILAC) was an Initiative of the CGIAR created in 2003 and discontinued in 2015.

The Initiative was hosted by the CGIAR Center Bioversity International, in Rome, Italy.

The Initiative was funded by a series of Funders, such as Rockefeller Foundation, Germany (GIZ), Netherlands (DGIS), and later by IFAD.

Initially the Initiative focused on impact evaluation theories and practices, supporting CGIAR practitioners on experimenting with alternative methodologies, besides advocating for changes in impact studies methodologies. Later in 2010 the Initiative shifted its focus to work more towards monitoring for learning and adaptive management.

The main output of the Initiative was a study on CGIAR activities and partnerships, through analyzing interactions of researchers and non-researchers of the CGIAR with their partners.

International Joint Commission

The International Joint Commission (French: Commission mixte internationale) is a bi-national organization established by the governments of the United States and Canada under the Boundary Waters Treaty of 1909. Its responsibilities were expanded with the signing of the Great Lakes Water Quality Agreement of 1978 (later amended 1987 and 2012).

Joy Zedler

Joy Buswell Zedler (born 1943) is an American ecologist and professor of botany at the University of Wisconsin–Madison (UW), holding the title of Aldo Leopold Chair of Restoration Ecology. In addition to restoration ecology, she specializes in the ecology of wetlands, rare species, interactions between native and introduced species, and adaptive management.

Kai Lee

Kai Lee is the program officer of science for the Conservation and Science Program of the Packard Foundation. Lee's work focuses on science-based environmental issues. Lee is well regarded for his advocacy of Adaptive Management.

Kuka Kanyini

Kuka Kanyini loosely means "looking after game animals" in the Australian Aboriginal Pitjantjatjara/Yankunytjatjara (APY) languages. In some of the most remote regions of Central Australia, Anangu Pitjantjatjara/Yankunytjatjara people manage their land and wildlife resources using a method that is loosely based on adaptive management plans which, in turn, are based on the Kuka Kanyini.It sets out priorities for scientists to work with indigenous communities to help them manage their lands themselves. It is currently being implemented in the APY Lands, South Australia and on Angas Downs Indigenous Protected Area, Northern Territory.

Laguna de Bay

Laguna de Baý (Filipino: Lawa ng Baé; English: Lake of Baý) is the largest lake in the Philippines located east of Metro Manila between the provinces of Laguna to the south and Rizal to the north. The freshwater lake has a surface area of 911–949 km² (352–366 sq mi), with an average depth of about 2.8 metres (9 ft 2 in) and an elevation of about 1 metre (3 ft 3 in) above sea level. The lake is shaped like a stylized 'W', with two peninsulas jutting out from the northern shore. Between these peninsulas, the middle lobe fills the large volcanic Laguna Caldera. In the middle of the lake is the large island of Talim, which falls under the jurisdiction of the towns of Binangonan and Cardona in Rizal province.

The lake is one of the primary sources of freshwater fish in the country. Its water drains to Manila Bay via the Pasig River.

Lisbon Principles

In 1997 a core set of six principles was established by ecological economist Robert Costanza for the sustainability governance of the oceans. These six principles became known as the "Lisbon Principles": together they provide basic guidelines for administering the use of common natural and social resources.

Principle 1: Responsibility. Access to environmental resources carries attendant responsibilities to use them in an ecologically sustainable, economically efficient, and socially fair manner. Individual and corporate responsibilities and incentives should be aligned with each other and with broad social and ecological goals.

Principle 2: Scale-matching. Ecological problems are rarely confined to a single scale. Decision-making on environmental resources should (i) be assigned to institutional levels that maximize ecological input, (ii) ensure the flow of ecological information between institutional levels, (iii) take ownership and actors into account, and (iv) internalize costs and benefits. Appropriate scales of governance will be those that have the most relevant information, can respond quickly and efficiently, and are able to integrate across scale boundaries.

Principle 3: Precaution. In the face of uncertainty about potentially irreversible environmental impacts, decisions concerning their use should err on the side of caution. The burden of proof should shift to those whose activities potentially damage the environment.

Principle 4: Adaptive management. Given that some level of uncertainty always exists in environmental resource management, decision-makers should continuously gather and integrate appropriate ecological, social, and economic information with the goal of adaptive improvement.

Principle 5: Full cost allocation. All of the internal and external costs and benefits, including social and ecological, of alternative decisions concerning the use of environmental resources should be identified and allocated. When appropriate, markets should be adjusted to reflect full costs.

Principle 6: Participation. All stakeholders should be engaged in the formulation and implementation of decisions concerning environmental resources. Full stakeholder awareness and participation contributes to credible, accepted rules that identify and assign the corresponding responsibilities appropriately.

Natural resource management

Natural resource management refers to the management of natural resources such as land, water, soil, plants and animals, with a particular focus on how management affects the quality of life for both present and future generations (stewardship).

Natural resource management deals with managing the way in which people and natural landscapes interact. It brings together land use planning, water management, biodiversity conservation, and the future sustainability of industries like agriculture, mining, tourism, fisheries and forestry. It recognises that people and their livelihoods rely on the health and productivity of our landscapes, and their actions as stewards of the land play a critical role in maintaining this health and productivity.Natural resource management specifically focuses on a scientific and technical understanding of resources and ecology and the life-supporting capacity of those resources. Environmental management is also similar to natural resource management. In academic contexts, the sociology of natural resources is closely related to, but distinct from, natural resource management.

Organizational ecology

Organizational ecology (also organizational demography and the population ecology of organizations) is a theoretical and empirical approach in the social sciences that is considered a sub-field of organizational studies. Organizational ecology utilizes insights from biology, economics, and sociology, and employs statistical analysis to try to understand the conditions under which organizations emerge, grow, and die.

The ecology of organizations is divided into three levels, the community, the population, and the organization. The community level is the functionally integrated system of interacting populations. The population level is the set of organizations engaged in similar activities. The organization level focuses on the individual organizations (some research further divides organizations into individual member and sub-unit levels).

What is generally referred to as organizational ecology in research is more accurately population ecology, focusing on the second level.

Phoenix Vernal Pools

The Phoenix Vernal Pools are located in Fair Oaks, a suburb of Sacramento city, around 20 miles east of the city of Sacramento and north of highway 50. This land consists of seasonally inundated wetlands that form after winter rains. The climate type of Phoenix Vernal Pools is classified as Mediterranean, receiving 24 in (610 mm) of rain per year. The rainwater percolates into the soil until it reaches an impermeable hardpan that causes an elevated water table, forming the vernal pools. The Phoenix Vernal Pool ecosystem is relatively unique as is supports many species of fauna and flora endemic to vernal pools.

Shared vision planning

Shared vision planning was developed by the U.S. Army Corps of Engineers during the National Drought Study (1989–1993). At the end of the Drought Study, Shared vision planning had three basic elements: (1) an updated version of the systems approach to water resources management developed during the Harvard Water Program; (2) an approach to public involvement called "Circles of Influence"; and (3) collaboratively built computer models of the system to be managed. Alternative dispute resolution methods are often used to bring people in conflict to the table, and to resolve differences that occur during planning. A method of collaborative decision making called "Informed consent" is used to make decisions internally consistent, more defensible and transparent.


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