NOTE
- If you cannot see the images below (which is a problem in some countries), click here to download a PDF document of this blog page.
- You may freely use these images for academic and educational purposes, and if you fully cite this blog post as the source. This blog post may be cited as:
Lew, A.A. (2017). Modeling the Resilience Adaptive Cycle. Collaborative for Sustainable Tourism and Resilient Communities Blog (21 January). Retrieved from http://www.tourismcommunities.com/blog/modeling-the-resilience-adaptive-cycle. - If you have any questions about these, feel free to send me an email using the comment box, below. - Alan Lew
The Adaptive Cycle
The Adaptive Cycle was one of the early resilience theory concepts that captured the imagination of may researchers. Holling (2001) introduced the Adaptive Cycle as part of his systems approach to resilience theory using a 3-dimensional diagram, with the cycle moving in a roller coaster pattern among the three key variables of resilience, potential, and connectedness (see below). I think that this was probably too complex for many people to conceptualize, and so he simplified it into a two-dimensional diagram that showed the cycle as a figure 8 (or folded infinity loop) pattern, and which should be well known to most anyone interested in resilience theory and thinking.
While visually compelling, the figure 8 pattern is still unnecessarily complicated and makes implications that need to be explained away in one way or another. I personally prefer the more simple circle diagram what was introduced by Walker and Salt (2006). I have reconfigured their diagram below, which has the advantage of showing more clearly the Fore Loop (moving from (re)organization to exploitation to consolidation) and Back Loop (moving from consolidation to collapse and again back to (re)organization). This version, below, first appeared in Lew, 2016.
The Adaptive Cycle was one of the early resilience theory concepts that captured the imagination of may researchers. Holling (2001) introduced the Adaptive Cycle as part of his systems approach to resilience theory using a 3-dimensional diagram, with the cycle moving in a roller coaster pattern among the three key variables of resilience, potential, and connectedness (see below). I think that this was probably too complex for many people to conceptualize, and so he simplified it into a two-dimensional diagram that showed the cycle as a figure 8 (or folded infinity loop) pattern, and which should be well known to most anyone interested in resilience theory and thinking.
While visually compelling, the figure 8 pattern is still unnecessarily complicated and makes implications that need to be explained away in one way or another. I personally prefer the more simple circle diagram what was introduced by Walker and Salt (2006). I have reconfigured their diagram below, which has the advantage of showing more clearly the Fore Loop (moving from (re)organization to exploitation to consolidation) and Back Loop (moving from consolidation to collapse and again back to (re)organization). This version, below, first appeared in Lew, 2016.
Tourism researchers have often pointed out similarities to between the Holling's Adaptive Cycle and Butler's Tourism Area Life Cycle (TALC) model. Here I attempt to show the comparison in a diagram (based on Butler, 1980 and Holling, 2001).
In addition to being posted here, with a creative commons copyright, this diagram will appear in: Bakti, L.A., Lew, A.A., and Kim, Y-S. (2017). A Resilient Approach to Collaborative Coral Reef Conservation on Gili Trawangan, Indonesia. In A.A. Lew & J. Cheer, eds., Understanding Tourism Resilience: Adapting to Environmental Change, pp. (forthcoming). London: Routledge.
In addition to being posted here, with a creative commons copyright, this diagram will appear in: Bakti, L.A., Lew, A.A., and Kim, Y-S. (2017). A Resilient Approach to Collaborative Coral Reef Conservation on Gili Trawangan, Indonesia. In A.A. Lew & J. Cheer, eds., Understanding Tourism Resilience: Adapting to Environmental Change, pp. (forthcoming). London: Routledge.
In the same book chapter cited above, I try to summarize how the different phases of the Adaptive Cycle relate to the variables of Resilience, Potential and Connectedness, which were part of the 3-dimensional diagram that Holling introduced in 2001. I found the best definitions of these three variables (shown below) in Allison and Hobbs (2004).
One of the issues that different diagrams of the Adaptive Cycle share is the misinterpretation that all systems must go through all stages of the cycle. It needs to be continually reinforced that this is not the case. Returning to the General Adaptive Cycle model diagram above, I try to show optional adaptive paths that systems could experience. These figures have not yet been designated for use in any of my articles, other than this blog post.
The first figure below shows all the likely paths that human social systems can take over time as they adapt to changing conditions. They may experience all four stages of the adaptive cycle, or they may only experience two or three of the stages. The major types that result are shown in three successive figures.
The Large and Small Cycles figure illustrates how some systems and processes move slowly through the four stages, possibly encompassing large amounts of resources and influences. These large and slow cycles are also sometime associated with slow, controlling variables. Other systems may move very quickly through the adaptive cycle stages, to the point where they may be largely imperceptible.
The Growth and Collapse Cycles figure shows how some stages may be completely avoided. A growth cycle occurs when the system anticipates vulnerabilities that may lead to collapse and plans for them by moving directly from the consolidation phase to the reorganization phase. If successful, this results in continual adaptation to changing conditions, as suggested by the ‘evolutionary resilience’ concept (Davoudi 2012). The collapse cycle is just the opposite. It is like the ‘poverty trap’ described by Allison and Hobbs (2004), in which a system is unable to effectively escape a constant state of decline. Efforts to reorganize are quickly coopted into rigid consolidation structures that collapse before a growth stage can ensue.
The final theoretical form that modeling the adaptive cycle in this way results in is a reorganizational cycle. Here the system never reaches a stage of consolidation, but is instead is continually reorganizing itself. While it does experience growth, it is not able to enjoy the fruits (or consolidate the benefits) of that growth, but immediately turns a reflexive eye toward restructuring itself. This might be an extreme version of evolutionary resilience, and while I do not have a good example, it seemed theoretically possible.
The first figure below shows all the likely paths that human social systems can take over time as they adapt to changing conditions. They may experience all four stages of the adaptive cycle, or they may only experience two or three of the stages. The major types that result are shown in three successive figures.
The Large and Small Cycles figure illustrates how some systems and processes move slowly through the four stages, possibly encompassing large amounts of resources and influences. These large and slow cycles are also sometime associated with slow, controlling variables. Other systems may move very quickly through the adaptive cycle stages, to the point where they may be largely imperceptible.
The Growth and Collapse Cycles figure shows how some stages may be completely avoided. A growth cycle occurs when the system anticipates vulnerabilities that may lead to collapse and plans for them by moving directly from the consolidation phase to the reorganization phase. If successful, this results in continual adaptation to changing conditions, as suggested by the ‘evolutionary resilience’ concept (Davoudi 2012). The collapse cycle is just the opposite. It is like the ‘poverty trap’ described by Allison and Hobbs (2004), in which a system is unable to effectively escape a constant state of decline. Efforts to reorganize are quickly coopted into rigid consolidation structures that collapse before a growth stage can ensue.
The final theoretical form that modeling the adaptive cycle in this way results in is a reorganizational cycle. Here the system never reaches a stage of consolidation, but is instead is continually reorganizing itself. While it does experience growth, it is not able to enjoy the fruits (or consolidate the benefits) of that growth, but immediately turns a reflexive eye toward restructuring itself. This might be an extreme version of evolutionary resilience, and while I do not have a good example, it seemed theoretically possible.
This final set of two figures are not yet designated for publication in any articles that I have been associated with, other than this blog post. The figures show how different systems (each represented by an adaptive cycle infinity diagram) influence each other through “memory” (aka “remembering” or “path dependence”) and through “revolt” (aka “path divergence” or “path creation”). These are the only two ways that systems influence one another in resilience theory. The figures show nested systems (smaller subsystems that operate within a larger system) and parallel systems. I also place these within the framework of my Scale, Change and Resilience (SCR) model (Lew, 2014), although I am not sure if that is more confusing than helpful. :)
References Cited
Allison, H.E. and Hobbs, R.J. (2004). Resilience, adaptive capacity, and the “Lock-in Trap” of the Western Australian agricultural region. Ecology and Society 9(1): 3. Online at http://www.ecologyandsociety.org/vol9/iss1/art3
Butler, R. (1980). The Concept of a Tourist Area Cycle of Evolution: Implications for Management of Resources. Canadian Geographer, 24(1), 5-12.
Davoudi, S. (2012). Resilience: A bridging concept of a dead end? Planning Theory and Practice, 13(2): 299–333, http://dx.doi.org/10.1080/14649357.2012.677124
Holling, C. S. (2001). Understand the in Complexity of Economic, Ecological, and Social Systems. Ecosystem, 4, 390-405.
Lew, A.A. 2013/2014. Scale, change and resilience in community tourism planning. Tourism Geographies 16(1): 14-22. DOI:10.1080/14616688.2013.864325
Lew, A.A., Ng, P.T., Wu, T-C, and Ni, C-C. (2016). Some New Resilience Figures and Diagrams. Collaborative for Sustainable Tourism and Resilient Communities Blog (30 September). Retrieved from http://www.tourismcommunities.com/blog/some-new-resilience-figures-and-diagrams.
Walker, B.H. and Salt, D. (2006). Resilience Thinking: Sustaining Ecosystems and People in a Changing World. Washington: Island Press.
Allison, H.E. and Hobbs, R.J. (2004). Resilience, adaptive capacity, and the “Lock-in Trap” of the Western Australian agricultural region. Ecology and Society 9(1): 3. Online at http://www.ecologyandsociety.org/vol9/iss1/art3
Butler, R. (1980). The Concept of a Tourist Area Cycle of Evolution: Implications for Management of Resources. Canadian Geographer, 24(1), 5-12.
Davoudi, S. (2012). Resilience: A bridging concept of a dead end? Planning Theory and Practice, 13(2): 299–333, http://dx.doi.org/10.1080/14649357.2012.677124
Holling, C. S. (2001). Understand the in Complexity of Economic, Ecological, and Social Systems. Ecosystem, 4, 390-405.
Lew, A.A. 2013/2014. Scale, change and resilience in community tourism planning. Tourism Geographies 16(1): 14-22. DOI:10.1080/14616688.2013.864325
Lew, A.A., Ng, P.T., Wu, T-C, and Ni, C-C. (2016). Some New Resilience Figures and Diagrams. Collaborative for Sustainable Tourism and Resilient Communities Blog (30 September). Retrieved from http://www.tourismcommunities.com/blog/some-new-resilience-figures-and-diagrams.
Walker, B.H. and Salt, D. (2006). Resilience Thinking: Sustaining Ecosystems and People in a Changing World. Washington: Island Press.
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