Resilient Communities are the Foundations of a Resilient America.

Practitioner’s Model of Community Resilience: From Identity to Model

Today is the 10th anniversary of the Greensburg, KS, tornado. Its population was almost instantly halved by the tornado, and apparently continues to slowly dwindle.  The town made a desperate bet that it could reinvent itself and thus begin to thrive again.  While it appears that that bet was lost, let us acknowledge that there is a kind of nobility in the attempt – a love of community, a reverence for its past, a commitment to its future.  And let us hope that the leaders of our own communities have that same nobility.

In the previous post in this series, I broke down the loss-recovery curve into four components:  pre-shock capacity, trajectory, loss and recovery.  As I pointed out, this is simply a mathematical identity, i.e., if we know those four then the loss-recovery curve for that part of the community is defined. If we can do that for all parts of a community, then we’ll have a model we can use to better understand a community’s resilience – how it will respond to a disruption.

The trajectory and pre-event capacity of a community are relatively simple concepts that I’ll discuss more when I talk about using the model.  The loss and recovery functions are more complex and I want to focus on them here.

My conception of both is colored by two observations:

  • When a shock occurs it may directly impact some part of the community (e.g., a hurricane knocking down houses in a neighborhood), or its impacts may be felt indirectly (e.g., roads and bridges leading into and out of the community are washed away or blocked so that food and other supplies can’t readily be brought in.).  The latter can lead to cascading consequences that may extend far beyond the area directly impacted by the original shock (This led me to coin the term “Disasters have Direction.”).  The flooding in Big Sur in February is a great example of these indirect effects:  very little direct damage but bridges washed away and other roads blocked by rock slides isolating the inhabitants.  Understanding the impacts of a shock requires some knowledge of a community’s “structure” – its internal and external physical, social and financial connections and especially its interdependencies.
  • Recovery is very much dependent on those connections as well.  Excellent work by Dave Butler and Ward Sayre shows that the path to recovery of Gulf Coast communities impacted by Katrina was very different than the same communities followed after the BP oil spill.  A very nice paper from Shade Shutters found that greater connectedness led to more disruption after the Great Recession but also faster recovery.

Thus, an important part of the model involves breaking down a community into its constituent parts so that I can envision its “structure.”  There’s really no magic in how to do this; several approaches are available – for example, the service area concept we at CARRI have used for our Community Resilience System, or the Triple Bottom Line, or the 18 functional areas proposed by ANCR.  The key is to be able to discern in a reliable and consistent manner a community’s internal and external connections.  In the following I’m not going to favor any approach. I’ll simply refer to “Whole of Community” to imply that I have a systematic way to parse the community.

With that as backdrop, let me look at loss and recovery.  When a shock occurs, it will directly impact one or more parts of the community, e.g., a tornado will knock down buildings.  If the buildings are schools the capacity of the entire educational system will be reduced, i.e., an indirect effect resulting from the direct impact of the tornado. Longer term, families and businesses may leave the community reducing the community government’s tax base (e.g., Greensburg, KS).

Thus, for a given part of the community, its loss function or change in capacity or functionality over time is the sum of the direct impact of the disruption on that part of the community and the sum (over the Whole Community) of all of the indirect impacts:

Loss for each part of the community

= (Direct impact of the shock + the sum of all of the indirect impacts)

Each of these will vary over time.  In math-speak (see trigger warning from the previous post), if “S” denotes the shock or disruption, the loss over time, Li(t+dt), in functionality “Fi” of the “i”-th part of the community, becomes

Loss

The term in which i = j in the sum represents the direct impact, and the rest of the terms capture the indirect impacts (As I’ll discuss in a later post, some of these terms may be positive; i.e., the “loss” may actually be a net gain.  Conversely, a positive change for one part of the community may result in a negative change for others.).

If we consider a community’s recovery from a disaster, we know that resources are required.  These may be of various types – usually financial and human, but often including all of the other types of “Community Capital.”  But resources are not enough – there must be the knowledge and the ability to use them to restore the functionality of that part of the community.  If we dub this competence, then

Recovery of each part of the community

= the sum of (the resources available to that part of the community

x the competence of that part of the community to use resources)

Again, each of these will vary over time (I’ll discuss this further in a later post.).  In math-speak, recovery, Ci, of the “i”-th part of the community becomes

Recovery

Thus, if we look at how the functionality Fi of each part of the community degrades and then recovers according to

Fi(t+dt) = Li(t+dt) + Ci(t+dt), or

Functionality of each part of the community = Loss + Recovery, over time.

The pre-event capacity, Fi(0), and the trajectory set the initial conditions.  In my next posts, I’ll discuss some implications of the model and how we’ve use it to guide our efforts with communities and institutions of higher education.