Resilience

About Resilience

Resilience is the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks. Adaptability is the capacity of actors in a system to influence resilience.

The state space of system is the three-dimension space of all the possible combination of the variables that constitute the system. (Walker et al) and defines the maximum possible potential/performance. The state of the system at any time is defined by their current values.

A “basin of attraction” is a region in state space in which the system tends to remain and whereby maximum potential/performance is possible. For systems that tend toward equilibrium, the equilibrium state is defined as an “attractor,” and the basin of attraction constitutes all initial conditions that will tend toward that equilibrium state.

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All real-world Social and Ecological Systems (SeS) are, however, continuously buffeted by disturbances, stochasticity (random variables), and decisions of actors (governors) that tend to move the system off the attractor. Therefore, there is a belief  SeS are moving about (a marble whirling around a bowl) within a particular basin of attraction, rather than tending directly towards an attractor. There may be more than one such basin of attraction for any given system with different state space and performance potential; which may be more favorable or less favorable, of low or high resilience. The various basins that a system may occupy, and the boundaries that separate them, are known as a “stability landscape” and are separated by resilience threshold or tipping points.

Both exogenous drivers (external drivers such rainfall, exchange rates, competitor value proposition) and endogenous processes (plant succession, management practices and governance efficacy) can impact resilience and its capacity to recover and restore its system performance potential.

There are four crucial aspects of resilience. The first three can apply both to a whole system or the sub-systems that make it up.

  • Latitude: the maximum amount a system can be changed before losing its ability to recover (before crossing a threshold which, if breached, makes recovery difficult or impossible).
  • Resistance: the ease or difficulty of changing the system; how “resistant” it is to being changed.
  • Precariousness: how close the current state of the system is to a limit or “threshold.”
  • Panarchy: because of cross-scale interactions, the resilience of a system at a particular focal scale will depend on the influences from states and dynamics at scales above and below related systems). For example, external oppressive politics, invasions, market shifts, or global climate change can trigger local surprises and regime shifts.

Resilience is defined as the capacity of a system to tolerate disturbances without collapsing into a qualitatively different state so as to still retain essentially the same function, structure, identity, and feedback” (Brian Walker) even more important governing system adaptation  ‘of what to what’; recover system performance or govern the system towards a different state space. Resilience is not just about capacity to tolerate disturbances but fundamentally:

  • Fully understating its state space
  • Its trajectory, basin of attraction and stability landscape
  • Its dynamics with basin of attraction and across regime

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The greater the resilience is in a particular system the more it can resist large or prolonged disturbances.  If resilience is low or weakened, then smaller or briefer disturbances can push the system into a different state, where its dynamics change.  Disturbances such as outside disorder (environment) the system has to cope with and the internal state of the system itself.

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Once resilience is overwhelmed (resiliency threshold will be crossed) system enters a new state, restoration to original sate will be complex, expensive, and sometimes even impossible.

The ball represents the current state of the system, or the current configuration represented by the different states with same function and feedback, and is represented by system variables, e.g. the amounts of grass, trees, livestock, and people, un-employment, debt, production). The ball moves to its basin of attraction (bottom of basin is the equilibrium state = attractor) but also move elsewhere via its trajectory due to inner dynamics (governance efficacy and system performance) as well as external dynamics causing the basin to change shape specifically location of thresholds or tipping point (dotted line). After crossing the tipping point the system tends towards a different equilibrium (change in feedback that that drive the system dynamics) depending on basin shape and location of threshold.

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When a system tips into a different basin or regime, that means a threshold is crossed. The change is sudden all in all (if one looks at the situation from the appropriate time scale), but that does not necessarily mean that the underlying (observable) variables have changed in such a sudden way. The change here can be quite slow and gradual, but once a certain value or amount is exceeded, different dynamics and feedbacks may set in which then cause the big/fast change or regime shift to happen. This of course has to do with feedbacks, the secondary effects of a direct effect of one variable on another, causing a change in the magnitude of that effect: negative feedback loops have a dampening effect (they tend to buffer or bring back to balance), positive feedback loops are reinforcing and have an enhancing effect (they cause exponential growth and may have runaway effect).

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The basin of attraction can also be influenced by external factors these external factors are external elements that influence the definition of set of states or configurations with the same functions and feedback, so: with basically the same identity. In a real situation dynamic condition implies that concurrently resilience is influenced by both shift in parameters and shift in variables that push the system in over tipping point into different regime (favorable or unfavorable) and limits ability to recover from disturbance due to fragility.

After crossing this tipping point, the system tends towards a different equilibrium (because of a change in feedbacks that drive the system’s dynamics). The stability landscape consists of multiple or alternate possible sets of states or regimes.
Fundamentally controlled resilience is about capacity of a system to absorb disturbances and restoration to maximum performance/potential and still persist with same basic structure in order to avoid crossing critical performance thresholds and remain stable around attractor basin and maintain system identity.

Research suggests that to restore some systems to their previous state requires a return to environmental conditions and the same function, structure (resources), identity, and feedback well before the collapse.   This can be seen why after prolonged economic crisis; growth has difficulty absorbing the unemployed labor force.

Where resilience is overwhelmed system may also reach extinction within the stability landscape rather than a new state. Example:  Maya, the Romans, and Kodak.

Resilience can only be effectively managed by understanding its inherent structure and its dynamics. It’s not just about managing recovery (performance levels) caused by disturbance but also understanding stability landscape, system trajectory and its momentum, thresholds in order for effective adaptation (doing the right things) and avoiding system collapse.

Resilience Structure

Effective systemic governance of resilience implies understanding system state (of what) and governing resilience (to what), recovery of performance and governing resilience within existing basin or to a different favorable regime within the stability landscape. Therefore it is fundamental to understand resilience elements in order to govern resilience:

Resilience Dynamics

Resilience is the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks.

Adaptability is the capacity of system to influence resilience, restore potential and mange disturbances considering diversity, system leadership, regimes, dynamics balance and scales.

While transformability is the capacity to create a fundamentally new system when ecological, economic, or social (including political) conditions make the existing system untenable (Paradigm Shift)

The challenge for system governors / entrepreneurs is how to take action that will shift the current system into a different basin of attraction or increase resilience to maintain stated performance potential. It is important to note that changes to a system are continuous (internal and external) and systems will crash and change (there is no eternity) The challenge is to ensure governance efficacy to guide and change (adaptation transformability) effectively without causing further damage and at the least possible cost considering system effects related to Senge’s 11 Laws of Systems.

There are four crucial aspects of resilience. The first three can apply both to a whole system or the sub-systems that make it up with respect to function, structure, identity, and feedbacks.

  • Latitude: the maximum amount a system can be changed before losing its ability to recover (before crossing a threshold which, if breached, makes recovery difficult or impossible).
  • Resistance: the ease or difficulty of changing the system; how “resistant” it is to being changed. Changes in the “depths” of basins, a measure of how difficult it is to move the system around within the basin—steep sides imply greater perturbations or management efforts are needed to change the state of the system
  • Precariousness: how close the current state of the system is to a limit or “threshold.” Moving the system around changes its position within a basin relative to the edge or moves it into a new basin where, without the state of the system itself changing, the system finds itself in a new basin of attraction, owing to changes in the stability landscape
  • Panarchy: because of cross-scale interactions, the resilience of a system at a particular focal scale will depend on the influences from states and dynamics at scales above and below. For example, external oppressive politics, invasions, market shifts, or global climate change can trigger local surprises and regime shifts.

In Westley’s words, “Where is the change you want to see’ or ‘from what to what’. In effect this is asking the question of whether to work towards increasing or to reducing resilience?

In order to effectively manage resilience dynamics, system governors have to ensure preparedness and learning capacity that can effectively manage disturbances, adaptation and transformation:

  • Viability; dealing with complexity achieving optimum potentiality and system equilibrium (homeostatic)
  • Adaptability; being flexible
  • Transformability being innovative
  • Persistence; being robust

Resilience management is fundamental for long term sustainability and viability. From a system governance perspective the key is to manage resilience effectively by understanding, internal dynamics, resilience threshold, low and high resilience applicable for adaptation. Resilience governance entails clear understanding of:

  • Understanding mechanism that act upon resilience:
    • Cumulative changes in systemic properties (environmental changes, viability, crumbling paradigms) that leads to a gradual loss of resilience.
    • An intense shock (earthquake, banking system, economic sanctions, Brit Exit from EU) that drastically changes the system state.
  • Systemic Variables that have quantities that change “quickly” in response to feedback from model dynamics

Transformation Initiatives can only effectively managed by considering resilience dynamics. Resilience engineering can assist in managing disturbances effectively and providing guidance with respect to transformation efficacy; doing the right things to avoids possibility of undesirable situations where system cannot recover or leads to inferior system state.

System Governance

Resilience management is fundamental for long term sustainability and viability. From a systemic governance perspective the key is to manage resilience effectively by understanding, internal dynamics, resilience threshold, low and high resilience applicable for adaptation. Resilience governance entails clear understanding of:

  • Understanding mechanism that act upon resilience:
    • Cumulative changes in systemic properties (environmental changes, viability, crumbling paradigms) that leads to a gradual loss of resilience.
    • An intense shock (earthquake, banking system, economic sanctions, Brit Exit from EU) that drastically changes the system state.
  • Systemic Variables that have quantities that change “quickly” in response to feedback from model dynamics

System Governor’s action influence resilience, either intentionally or unintentionally. Their collective capacity to manage resilience, intentionally, determines whether they can successfully avoid crossing into an undesirable system regime, or succeed in crossing back into a desirable one.

Fundamentally within resilience framework is to understand resilience the question ‘of what to what’ that investigates resilience in particular system contexts and configuration and to particular disturbances. Resilience engineering is about effective adaptation; doing the ‘right things’ to minimize manage, maintain performance and improve performance:

  • ‘where is the change you want to see?” In effect this is implies governing the system towards increasing or to reducing resilience or towards a totally new regime.
  • Is the existing system considered brittle, in a rigidity trap? Are there factors that may be keeping a system in a deep basin or could there be an opportunity for change?
  • Restoring system performance within existing basin of attraction or equilibrium attractor an preventing undesirable regime shift
  • Effective adaptation governing regime shift by guiding system trajectory that cross threshold, understanding system context within the new regime basin of attraction in order to maintain maximum performance e potential and manage perturbation.
  • Carrying out specific governance action to pilot change to basin of attraction (reduce resilience) and guide system to new favorable regime or create a totally new one (new industry paradigm). This new innovative alternative has to have adequate resilience in order to avoid reverting back to its old state or even worse regime. Systems can exhibit very strong qualities of remembrance and revert to earlier states as a matter of course. (cited in Westley et al., 2006)

This entails the ability of System Governors to either control the trajectory of the system (change precariousness), change the topology of the stability landscape (latitude and resistance), or change the processes in response to dynamics at other scales (panarchy response), is a measure of adaptability. Both purposeful movements between basins, and purposeful reshaping of the stability landscape, demonstrate adaptability. SeS’s can move from one basin of attraction to another either by the system crossing a threshold, or by a threshold moving across the system.

System governors can intervene by increasing resilience which equates to lowering the new basin – making the new system more attractive, more stable, more likely to “stick” given a system shock. Alternatively, one might take the approach of reducing the resilience of the current system – effectively raising the level of the old basin.

  • move thresholds away from or closer to the current state of the system by altering ‘latitude’
  • move the current state of the system away from or closer to the threshold ‘precariousness’ or make the threshold more difficult or easier to reach ‘resistance’
  • governors can manage cross-scale interactions to avoid or generate loss of resilience at the largest and most socially catastrophic scales ‘Panarchy’.

In conclusion, effective system governance needs to find a balance between adaptability, persistence and transformability:

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Resilience is not only about the capacity of a system to tolerate disturbances without collapsing into a qualitatively different but to manage the resilience and system dynamics into different regime:

  • New regime (window A) caused by shift in variables. Push system over the threshold into new regime.
  • New regime (window B) caused by shift in parameters; lower the barrier (tipping point) caused by external conditions such as access or loss markets
  • Reconfiguration of the system (window C transformations) in fundamentally paradigm shift each in its own regime

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In a real world situation transitions to new regime are both influenced by shift in variables and shift in parameters. A system is a continuously influenced by changing variables and parameters due systemic conditions. Reconfiguration is either internally governed via effective adaptation whereby trajectory is controlled to tipping point that leads to ideal regime or due to overwhelming internal and external factors impacting system trajectory towards tipping point associated to less favorable regime.

Effective resilience management ‘of what to what’ cannot be viewed in isolation but rather as a sub-system of the whole; country economy is associated to the whole or fresh water basin as sub system to agricultural practice have a cross system effect impacting stability basin of the sub-system. It is important to bear in mind that “systems” consist of nested dynamics operating at particular organizational scales—“sub-systems,” as it were, of households to villages to nations, trees to patches to landscapes. Therefore managing resilience of the sub-system if of low efficacy without understanding the whole and the cross system effect; this is critical to do the right things.

No SeS can be understood by examining it at only one scale. The component of a SeS consists of groups of people organized at multiple levels with differing views as to whether some basins are desirable and others undesirable. At any particular scale, the system is actually a sub-system of the whole panarchy, and the first three aspects of resilience (latitude , resistance and precariousness ) are influenced by what is happening in the panarchy at scales above and below the scale of interest. Panarchy, the cross-scale effects, is the fourth aspect of resilience that needs to be considered.

 

Resilience System Governance Framework

Resilience governance framework is not just about resilience but also viability, complexity mgt, variety and potentiality and understanding system dynamics.

In order to manage resilience effectively ‘from what to what’ the following key elements need to be in place:

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  • System definition
    • System attributes that define the systemic working of the system
    • System metrics, variables and parameters
  • System governance model
    • Governance model based on Viable System Model that will include methods to deal with resilience, effectiveness, potentiality , constraints
    • Algedonic alerts to identify potential disturbances / disruptions
    • Variety engineering to deal with complexity
    • System Control tower to monitor system performance, variables , events, disturbances
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