Discussion Question 04: Indicators of Resilience

How can we identify and select indicators of resilience?
What are some possible examples of early warning signals?


  1. Indicators are important for assessing system resilience. Determining measurable indicators is difficult because the definition of resilience for coupled human-natural systems encompasses a broad array of factors (socio-ecological, socioeconomic, eco-political and more), and can change over different scales of time and space (Carpenter, Alberti, Peterson). Scenario planning can help to generate a more robust set of indicators, which can then be used to measure the impacts of these alternative futures. Indicators should be relevant to scenarios, quantifiable, communicable, and utilize available data (Alberti).

    Valid sets of indicators can provide warning signals of regime shifts in current systems and alternative futures. Early warning signals can help us detect when slow variables (variables that control system states), are nearing critical thresholds. An important resilience indicator measuring marine habitat quality is the amount of carbon retained in ocean waters, as this can help us anticipate and mitigate ocean acidification. Examples of resilience indicators for water bodies susceptible to eutrophication include the levels of phosphorus and nitrogen in the water, and the percent of surrounding land area under construction (Carpenter et al. Resilience from What to What). Institutional indicators may describe the economic ability for farmers to leave a certain area of land around the water uncultivated, as well as the farmer’s knowledge of the problem (Carpenter et al.).

  2. Though the research behind successful indicators regarding system resilience is still in its nascent development, it is of critical importance to properly understand, predict and anticipate regime shifts and the impacts shifts may have. Indicators of system performance are also necessary for monitoring the potential successes of proposed scenarios or the consequences of any chosen action (Alberti, 241). Scheffer, et al. describe the emerging research, literature and understanding of resilience indicators, detailing that recent explorations across a variety of fields suggest "the existence of generic early-warning signals that may indicate for a wide class of systems if a critical threshold is approaching." Slower recovery, increased variance, increased skewness and other potential indicators may give clarity to resilience in complex systems (Scheffer, et al., 54). If the evidence of these common traits across disciplinary lines continues to grow, indicators should follow these guidelines.

    One such indicator regarding plant health is soil quality, defined by aeration, moisture and nutrient levels. As urban development increases, soil compaction and impervious surface cover prevent plant life from receiving the necessary levels of limiting resources. A threshold in the rate of water/nutrient absorption may exist that leads to a shift in tree species viability and local extinctions. By monitoring the indicators regarding soil quality and tree health, the resilience of the system may be better understood.

  3. As Schindler (2015) notes, a critical step in developing effective policy is identifying reliable metrics, or indicators, of ecosystem condition that can inform policy strategies. Because previously-established relationships between variables and ecosystems can change with scale and over time, it is important for indicators to be reliable, yet flexible and adaptable. Two examples of monitoring frameworks that rely upon indicators are the City Resilience Index and the State of the Sound report. Each set of indicators is calibrated to a different scale and purpose and so employs a different methodology of indicator selection:

    The City Resilience Index (The Rockefeller Foundation/ARUP, 2014 http://www.arup.com/city_resilience_index), which supplies the framework for the 100 Resilient Cities initiative in which Seattle is participating, defines urban resilience as "the capacity of individuals, communities, institutions, businesses, and systems within a city to survive, adapt, and grow no matter what kinds of chronic stresses and acute shocks they experience." This set of 52 indicators works at a global scale, relying on "credible and usable" metrics that can be applied across cities that vary by size, character and location to compare their resilience performance over time.

    The State of the Sound report (Puget Sound Partnership, 2015 https://pspwa.box.com/2015-SOS-vitalsigns-report) uses a set of regionally-focused indicators called the Puget Sound Vital Signs to track progress toward goals of ecosystem recovery. The indicators that comprise the Vital Signs meet the following criteria: they are scientifically valid, resonate with the public and policymakers, represent specific and measurable metrics, are relevant to management decision making, and are supported by available, high-quality data.

    Although it is difficult to predict critical transition points, research suggests the existence of generic warning signs that may indicate the approach of a critical threshold, which includes increased variability within the system (Alberti 2008). Scheffer et al. (2009) have noted a critical "slowing down" of system dynamics that leads to three possible early-warning signals of a regime shift: slower recovery from perturbations, increased autocorrelation, and increased variance. Systems that have regular self-organized patterns might also display particular spatial configurations in advance of a regime shift.

  4. Indicators of resilience should inform whether a system is close to a threshold, which may cause the system to slip into an alternate state, or whether a system is relatively stable in its current state. Measuring and monitoring indicators of resilience should aid in detecting, avoiding, or encouraging system state shifts. Modeling different variables that affect system dynamics and function may reveal which indicators depict actual resilience of a system to perturbation and which have little effect on overall resilience.

    Possible early warning signals for power transformer failure may include constant third-stage cooling operation, which could be an indicator that the system is overheating or insulation is insufficient.

  5. Essentially, indicators of resilience can be identified quantitatively, by measuring a system's rate of recovery as it changes over time. In natural systems, the theoretical framework for identifying indicators of resilience is based partly on the process known as "critical slowing down," in which the system becomes progressively slower to recover from small disturbances (Scheffer et al. 2009). Evidence for this waning in recovery can be shown by the system returning increasingly to a state that resembles its past and by increasing variance in pattern fluctuations. Unrelated to critical slowing down, "flickering" is another way to identify indicators. As an early-warning signal, a flickering system is one that passes back and forth between two attractors before collapsing in regime shift.

    Selecting indicators of resilience depends on what the system is. For example, Scheffer et al. (2009) differentiate the stochastic system indicators described in the above paragraph from indicators that are unique to cyclic and chaotic systems. There are also spatial patterns that tend to prompt a regime shift. These pattern changes are unique to the geospatial context in which they emerge. Habitat fragmentation is one example of an early-warning signal. Another example is in desertification, a regime shift for which symmetrical patterns of vegetation patches constitute a reliable signal.


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