Figure 1. Disaster Community and Non-Disaster Community Development Paths. (Based on Lew et al., 2018)

The figure above is one that I developed toward the end of the Taiwan rural resilience research project that is reported on this website. This particular figure is mostly based on the discussion of sustainable and resilient communities by Lew et al., 2018. I have used this figure in several academic presentations on community resilience in the past couple of years, with the most recent being at Ritsumekan Asia Pacific University, in Beppu, Kyushu, Japan (Lew, 2019), but have otherwise not formally published it ... until now.

The figure shows the development paths of two types of communities that we encountered in our research in Taiwan. Three of our communities had experienced major natural disasters (earthquake, flooding or both) in recent memory, while three communities had not experienced a natural disaster within the memory or stories of current residents. The development path model starts with both community types at a base Stage 1 condition. The disaster community experiences a steep decline in functioning conditions, whereas the non-disaster community experiences a gradual decline through the entropy of aging infrastructure, facilities and services. Without intervention, each would reach a degree of degradation in Stage 2, which would be much deeper in the disaster community than the non-disaster community.

Functioning as a self-organizing and self-sustaining system, all communities will respond to their degradation at some point, although some may respond sooner than others. For the disaster community, the dominant response is likely to reflect a high degree of resilience practices. These come for central government recovery funds, as well as self-organizing recovery responses by local residents. The non-disaster community, on the other hand, does not have access to recovery funds and has less motivation for a strong self-organizing response to gradual degradation, and the nature of its responses reflect this.

In general, we refer to the non-disaster responses as "sustainability practices" because they are mostly trying to sustain a status quo while moving through incremental shifts toward community improvement over the long term. Resilience recovery responses tend to be more innovative, with more of an acceptance of large, short term changes to a local economy and culture. This was clearly evident in the community interviews we conducted in Taiwan. The disaster communities were more likely to have undergone a shift in their economies (with tourism being a major new product), that was driven by new ideas generated by both local residents and newcomers who moved to the communities initially to provide disaster relief, and then decided to stay for the long term. The disaster communities were also much more adept at securing government grants for a variety of short and long term projects than were the less organized and less socially cohesive non-disaster communities.

However, even small rural communities can be complex in their social and political relationships. We try to capture this by using the symbol "Rs" to indicate emphasis on resilience practices primarily, but with also some ongoing sustainability practices, as well. The "Sr" symbol is the opposite, with an emphasis on sustainability practices, but with some awareness and utilization of resilience opportunities and initiatives.

In Stage 3, each type of community returns to a stage that is somewhat similar in functions the initial Stage 1. If properly planned and managed, non-disaster communities never really exhibit a Stage 2 decline because maintenance needs are regularly cared for. As such, they maintain their status quo in moving from Stage 1 to Stage 3. In either event, the next question is what will be the development path for the future of each community. There are three options suggested by the model:

1. A disaster may hit the community causing a rapid and significant decline and forcing them into a resilience development path seeking recovery back to the original stable condition. Resilience theory suggests that communities that have already experienced disasters are better prepared to respond to a new event than those that have not had such an experience in recent memory. As such, the impact would be less and their recovery might be quicker.
2. For most communities, there will not be a major disaster and they will only have the normal degradation of time to address, which is mostly done through physical and long range community community planning by local governments and individual entrepreneurs. This would be a sustainability development path that maintains the status quo.
3. The third option is for a community to incorporate the strengths of both resilience practices and sustainability practices to move them to a new level of community well-being and quality of life. For a community to be even better than they were in the past requires them to be both resilient (innovative and change oriented) and sustainable (maintaining sense of place and continuity). This is how we envision a successful sustainable and resilient community to be (see Lew et al., 2018). 

Sustainability and resilience are two powerful ways that communities manage their development. Unfortunately, they are often confused and used interchangeably in both common and professional discussions. While some people may disagree with our definitions of the terms here, in the end it does not matter what words we use. It is the intention and resources available to better the communities that we live in that are most important. Change is a constant, but so is identity. How these are managed so both is allowed to flourish is the goal of a sustainable and resilient people and place.

NOTE

1. 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.
2. 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.
3. If you have any questions about these, feel free to send me an email using the comment box, below. - Alan Lew

Creative Commons Copyright CC BY-SA 4.0. Updated 11 February 2017.

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).
​

​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.

​Below are figures and tables that my collaborators and I have developed based on our sustainability and resilience research in Taiwan. Please note:

1. If you cannot see the images below (which is a problem for people in some countries), click here to download a PDF document of this blog page. 
2. 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., 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.
3. The references cited below will be updates as they appear in print in 2017 (or later).
4. The figures should be self-explanatory, but if you have any questions about these, feel free to send me an email using the comment box, below. - Alan Lew

Creative Commons Copyright CC BY-SA 4.0. Originally posted 30 September 2016; Updated 11 February 2017

(1) The first three figures (with an accompanying table of descriptions) will also appear in: 

• ​Lew, A.A.; Wu, Tsung-chiung; Ni, Chin-cheng; and Ng, Pin T. 2017. Community Tourism Resilience: Some applications of the Scale, Change and Resilience (SCR) Model. In Richard Butler, ed., Tourism and Resilience, pp. (forthcoming). Oxfordshire: CABI.

(2) This second set of four figures and two tables will also appear in: 

• Lew, A.A. 2017. Planning for Slow Resilience in a Tourism Community Context. In Joseph Cheer and A.A. Lew, eds., Understanding Tourism Resilience: Adapting to Social, Political and Economic Change, pp. (forthcoming). London: Routledge.

(3) This third set of two figures will also appear in:

• Lew, A.A.; Ni, Chin-cheng; Wu, Tsung-chiung; and Ng, Pin T. 2017. The Sustainable and Resilient Community: A new paradigm for community development. In A.A. Lew & Joseph Cheer, eds., Understanding Tourism Resilience: Adapting to Environmental Change, pp. (forthcoming). London: Routledge.