Author: Prof. Shade T. Shutter (Arizona State University)
As Ian Kelman previously wrote here, Resilience can mean almost anything. And yet its presence in the scientific literature has undergone an explosive growth, with resilience-themed listings in the Web of Science increasing by over 1,000% between 2000 and 2010. Among practitioners the subject is also en vogue as major cities around the world appoint new Chief Resilience Officers, and global networks of cities, such as ICLEI, shift the emphasis of their organizations to resilience. Yet for all of its promise, the concept of resilience continues to reside largely in the world of practice as opposed to science. And without a theoretically grounded, quantitative methodology, the concept of resilience will likely remain there – a nebulous notion framed in whatever terms are most convenient to its user. Still, using theory and methods from the emerging field of complex systems, there may be a way forward. And the focus of this approach is on the phenomenon of interdependence.
When people concentrate their labors on what each does best, all of society benefits. So said Adam Smith in 1776 at the dawn of modern economic thinking. A few years later David Ricardo extended this idea to nations, claiming that if each country focuses its production capacity on what it does better than anyone else – exploiting their comparative advantage – all nations will be better off. These early thinkers were advancing the notion that specialization increases efficiency, which in turn creates a greater aggregate good for a given amount of effort. Henry Ford capitalized on this concept when he implemented assembly lines to mass-produce his Model T cars for, what were at the time, shockingly small costs. More generally, labor or task specialization is a feature of division of labor – a hallmark of human systems and of complex social systems more generally.
Unfortunately, the efficiency gains from specialization is only half of the story. Like all good things, there is a tradeoff that often goes unnoticed. In the case of increasing specialization, the tradeoff results from increased interdependence. As a society’s efforts are divided into ever more discrete tasks, each member of that society becomes ever more dependent on others for production of social goods and, ultimately, for survival. But these societies that are more interdependent, more connected, more integrated, are also more fragile, more brittle, more vulnerable to cascading failures. So while highly integrated societies can accomplish feats that no group of unspecialized laborers could dream of, they do not do so well when subjected to shocks.
Consider the following example from the realm of social insects. In a recent study using a single species of ant, researchers modified two colonies so that one was composed of task specialists while the other was composed of so-called generalists – individuals that do not specialize on any certain task. When subjected to attack by an enemy ant species – a clear type of shock – the colony of specialists was decimated, losing over 80% of its members, while the colony of generalists lost about 50%.
In another, more relevant study, researchers developed a labor-based measure of economic interdependence for 364 U.S. metropolitan areas. When compared with each city’s response to the shock of the Great Recession, the authors found that the most integrated, interdependent cities (typically also the largest cities) had larger percentage drops in economic performance and took longer to recover than less integrated cities.
These studies illustrate that the tradeoff between efficiency and vulnerability, between productivity and lower resilience, is navigated in the currency of interdependence. Understanding those interdependencies is the key to understanding, analyzing, and even quantifying the resilience of a system, including urban systems. And the optimal framework for analyzing, visualizing, and mapping these interdependencies is through the use of networks. Ascribing quantified structure to a system’s internal web of interacting and interdependent parts makes that system amenable to a suite of analytical tools and quantitative methods from network analysis and graph theory.
Using networks to understand systemic vulnerabilities has recently been embraced in studies of ecosystems, power and communication grids, global food trade, and urban water supplies. Cities, composed of a network of interacting parts and subsystems, are just as amenable to these types of analysis. Perhaps even more so. Indeed, complex urban systems are virtually defined as a multiplex of interacting complex networks: interpersonal, transportation, financial, resource distribution, sewer and water infrastructure, electricity, communication and data, economic trade, and others.
Thus, a proposed agenda for future urban resilience research might be composed of three broad approaches: (1) cataloging and understanding the massive amounts of available data now flowing from cities, (2) using that data to construct quantitative network maps of the systems comprising the city, and (3) defining network-based metrics that best capture the resilience and vulnerabilities of the city. In this way, resilience may better fulfill its potential and become more than just another buzzword.
Biography: Shade Shutters is Research Scientist for the Global Security Initiative, Core Faculty at the Center for Social Dynamics & Complexity, Senior Sustainability Scientist at the Global Institute of Sustainability and Faculty Affiliate, Center for Policy Informatics, School of Public Affairs, at the Arizona State University.
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