Albert-László Barabási and his colleagues have published a breakthrough paper in Nature about the first-ever tool they developed to identify whether complex systems—be they technological, ecological, or biological—are in danger of failing. Will they collapse under disconnections/ disruptions, partial failures & outages, efficiency streamlining/ simplification/ cleansing/ isolation and loss of diversity? And they can define and measure a resilience index which describes how far the total system is from total catastrophic network failure.
- Their paper is presented in the following article: http://www.northeastern.edu/news/2016/02/researchers-find-the-tipping-point-between-resilience-and-collapse-in-complex-systems/ (I recommend you watch the video from this article). I show part of that article here:
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Honeybees have been dying in record numbers, threatening the continued production of nutritious foods such as apples, nuts, blueberries, broccoli, and onions. Without bees to pollinate these crops, the environmental ecosystem—and our health—stands in the balance. Have we reached the tipping point, where the plant-pollinator system is due to collapse?
There was no way to calculate that—until now.
Using statistical physics, Northeastern network scientist Albert-László Barabási and his colleagues Jianxi Gao and Baruch Barzel have developed a tool to identify that tipping point—for everything from ecological systems such as bees and plants to technological systems such as power grids. It opens the door to planning and implementing preventive measures before it’s too late, as well as preparing for recovery after a disaster.
The tool, described in a new paper published on Wednesday in the prestigious journal Nature, fills a longstanding gap in scientists’ understanding of what determines “resilience”—that is, a system’s ability to adjust to disturbances, both internal and external, in order to remain functional.
“The failure of a system can lead to serious consequences, whether to the environment, economy, human health, or technology,” said Barabási, Robert Gray Dodge Professor of Network Science and University Distinguished Professor in the Department of Physics. “But there was no theory that considered the complexity of the networks underlying those systems—that is, their many parameters and components. That made it very difficult, if not impossible, to predict the systems’ resilience in the face of disturbances to those parameters and components.”
“Our tool, for the first time, enables those predictions,” said Barabási, who is also a leader in Northeastern’s Network Science Institute.
2. Here is the summary of the Paper: ( http://www.nature.com/nature/journal/v530/n7590/full/nature16948.html )
Resilience, a system’s ability to adjust its activity to retain its basic functionality when errors, failures and environmental changes occur, is a defining property of many complex systems1. Despite widespread consequences for human health2, the economy3 and the environment4, events leading to loss of resilience—from cascading failures in technological systems5 to mass extinctions in ecological networks6—are rarely predictable and are often irreversible. These limitations are rooted in a theoretical gap: the current analytical framework of resilience is designed to treat low-dimensional models with a few interacting components7, and is unsuitable for multi-dimensional systems consisting of a large number of components that interact through a complex network. Here we bridge this theoretical gap by developing a set of analytical tools with which to identify the natural control and state parameters of a multi-dimensional complex system, helping us derive effective one-dimensional dynamics that accurately predict the system’s resilience. The proposed analytical framework allows us systematically to separate the roles of the system’s dynamics and topology, collapsing the behaviour of different networks onto a single universal resilience function. The analytical results unveil the network characteristics that can enhance or diminish resilience, offering ways to prevent the collapse of ecological, biological or economic systems, and guiding the design of technological systems resilient to both internal failures and environmental changes.
Please notice the definition of “Resilience” in the summary. The crux of this research IMHO is not only to retain resilience under deminishing connectivity (quantities) but also under loss of DIVERSITY (of species, tribes, parts of foodchains/ valuechains that die or are disconnected (BREXIT ?)).
3. As mentioned in the remarks below is the very exiting work of ecologist Prof. Marten Scheffer and his team at Wageningen University ( WUR, NL) , I recommend you watch his video lecture mentioned below in the remarks. He suggested me to read his paper in Nature: “Anticipating Critical Transitions ” , which is available on Internet at:
and his recent work, together with Ingrid van de Leemput et.al. on “sudden depression” (just to remind you that the human mind is a dynamic & non-linear & complex networked system too !):
Leemput et al 2013 PNAS : ” Critical slowing down as early warning for the onset and termination of depression “
4. I hope that the groups of Barabasi and Scheffer can interconnect and build an resilient ecosystem for this extremely important subject, vital for survival on this planet !
Jaap van Till, TheConnectivist