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==Description== | ==Description== | ||
Adaptive management wiki is intended for adaptive management (AM) practitioners to share tools, information and ideas about applying adaptive management to natural resource management problems. | |||
The discussion | The discussion page will be used to build a community of practice where people can post or respond to questions and make connections with others practicing or interested in adaptive management. | ||
==Defining | ==Defining Adaptive Management== | ||
The concept of | The concept of adaptive management has been widely debated and different definitions exist. This presents a challenge to practitioners who must reach a common understanding with partners, stakeholders, managers, scientists and decision makers. In order to bring some consistency to what the British Columbia Forest Service means by “adaptive management”, the following standard working definition was adopted: ''Adaptive management is a systematic process for continually improving management policies and practices by learning from the outcomes of operational programs'' (British Columbia, Ministry of Forests and Range). [http://en.wikipedia.org/wiki/Adaptive_management Wikipedia] | ||
The | The adaptive management approach assumes natural resource management policies and management actions are not static but adjusted based on the combination of new scientific and socio-economic information in order to improve management by learning from the ecosystems being affected. Often people think adaptive management simply means “trial and error”, in which management policies and practices evolve in response to past performance and changing priorities, but in fact this misses an essential element of the concept which is deliberate experimentation. | ||
Although definitions of adaptive management vary by source, several key characteristics of the concept are universal and fundamental: | |||
1. | 1. Learning; reducing key uncertainties | ||
There is explicit | There is explicit acknowledgement of uncertainties and knowledge gaps about the response of the system to management actions. Reducing these uncertainties (i.e. learning) becomes one objective of management. | ||
2. Using | 2. Using what is learned to change policy and practice | ||
Process in | Process in place to make certain that what is learned informs decisions (i.e. closing the loop). It is essential to have a good idea at project design stage of what policies and practices may change and what institutional mechanisms are in place to support that change. | ||
3. Focus is on improving | 3. Focus is on improving management | ||
AM integrates the worlds of science and management, ensuring applied science is well directed to key uncertainties and scientific advances are transferred to managers (i.e. this is where the learning is applied) | |||
4. Often | 4. Often called experimental management | ||
AM is about thoughtfully applying management activities as experiments to see which are most effective in achieving desired goals. | |||
5. It is | 5. It is formal, structured, systematic | ||
AM is a deliberate process, not ad-hoc or simply reactionary. Some flexibility in the approach is important to allow the creativity in management that is crucial to dealing with uncertainty and change. | |||
Adaptive management is visualized as a cyclical and iterative process. The British Columbia Forest Service identifies 6 steps: ''Assess, design, implement, monitor, evaluate'' and ''adjust''. Within each of the steps, several elements are defined. These elements are the specific components of each step such as defining the management objectives, identifying stakeholders, articulating hypotheses and developing conceptual models . Although the full suite of elements may not be implemented for every AM project, it is important to understand them and the implications of omissions. | |||
[[ | [[Image:AMcycle.gif]] | ||
Adaptive management takes a couple of forms: passive or active (Walters, 1986) | |||
Passive AM is an approach whereby, faced with uncertainty, managers implement the alternative they think is ‘best’ (with respect to meeting management objectives), and then monitor to see if they were right, making adjustments if desired objectives are not in fact met. | |||
Active AM is an experimental approach whereby, when faced with uncertainty, managers implement more than one alternative as concurrent experiments to see which will best meet management objectives. It is characterised by “actively probing” the system in order to distinguish between competing hypotheses (where the different hypotheses suggest different “optimal” actions). The key is that there are alternatives that can be more confidently compared. | |||
[[ | [[Image:Activepassive.gif]] | ||
==References | ==References and Useful links== | ||
The following is | The following is a list of books, articles and websites that AM practitioners may find helpful. Please edit, update and add to this reference list. | ||
==See | ==See also== | ||
*[[ | *[[Conservation ecology]] | ||
*[[Decision Theory]] | *[[Decision Theory]] | ||
*[[Ecology]] | *[[Ecology]] | ||
*[[Fisheries]] | *[[Fisheries]] | ||
*[[Forestry]] | *[[Forestry]] | ||
*[[ | *[[Optimization (mathematics)]] | ||
*[[ | *[[Operations research]] | ||
*[[ | *[[Uncertainty]] | ||
[[ | [[Category:Learning methods]] | ||
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Latest revision as of 11:18, 23 December 2024
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Adaptive management wiki [No Recent changes] [No WikiNode] [No About] [No Mobile URL] |
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| Language: | English |
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| Main topic: | Science |
Description[edit]
Adaptive management wiki is intended for adaptive management (AM) practitioners to share tools, information and ideas about applying adaptive management to natural resource management problems.
The discussion page will be used to build a community of practice where people can post or respond to questions and make connections with others practicing or interested in adaptive management.
Defining Adaptive Management[edit]
The concept of adaptive management has been widely debated and different definitions exist. This presents a challenge to practitioners who must reach a common understanding with partners, stakeholders, managers, scientists and decision makers. In order to bring some consistency to what the British Columbia Forest Service means by “adaptive management”, the following standard working definition was adopted: Adaptive management is a systematic process for continually improving management policies and practices by learning from the outcomes of operational programs (British Columbia, Ministry of Forests and Range). Wikipedia The adaptive management approach assumes natural resource management policies and management actions are not static but adjusted based on the combination of new scientific and socio-economic information in order to improve management by learning from the ecosystems being affected. Often people think adaptive management simply means “trial and error”, in which management policies and practices evolve in response to past performance and changing priorities, but in fact this misses an essential element of the concept which is deliberate experimentation. Although definitions of adaptive management vary by source, several key characteristics of the concept are universal and fundamental:
1. Learning; reducing key uncertainties
There is explicit acknowledgement of uncertainties and knowledge gaps about the response of the system to management actions. Reducing these uncertainties (i.e. learning) becomes one objective of management.
2. Using what is learned to change policy and practice
Process in place to make certain that what is learned informs decisions (i.e. closing the loop). It is essential to have a good idea at project design stage of what policies and practices may change and what institutional mechanisms are in place to support that change.
3. Focus is on improving management
AM integrates the worlds of science and management, ensuring applied science is well directed to key uncertainties and scientific advances are transferred to managers (i.e. this is where the learning is applied)
4. Often called experimental management
AM is about thoughtfully applying management activities as experiments to see which are most effective in achieving desired goals.
5. It is formal, structured, systematic
AM is a deliberate process, not ad-hoc or simply reactionary. Some flexibility in the approach is important to allow the creativity in management that is crucial to dealing with uncertainty and change.
Adaptive management is visualized as a cyclical and iterative process. The British Columbia Forest Service identifies 6 steps: Assess, design, implement, monitor, evaluate and adjust. Within each of the steps, several elements are defined. These elements are the specific components of each step such as defining the management objectives, identifying stakeholders, articulating hypotheses and developing conceptual models . Although the full suite of elements may not be implemented for every AM project, it is important to understand them and the implications of omissions.
Adaptive management takes a couple of forms: passive or active (Walters, 1986)
Passive AM is an approach whereby, faced with uncertainty, managers implement the alternative they think is ‘best’ (with respect to meeting management objectives), and then monitor to see if they were right, making adjustments if desired objectives are not in fact met.
Active AM is an experimental approach whereby, when faced with uncertainty, managers implement more than one alternative as concurrent experiments to see which will best meet management objectives. It is characterised by “actively probing” the system in order to distinguish between competing hypotheses (where the different hypotheses suggest different “optimal” actions). The key is that there are alternatives that can be more confidently compared.
References and Useful links[edit]
The following is a list of books, articles and websites that AM practitioners may find helpful. Please edit, update and add to this reference list.
See also[edit]
- Conservation ecology
- Decision Theory
- Ecology
- Fisheries
- Forestry
- Optimization (mathematics)
- Operations research
- Uncertainty