HR4RS stamp
Newsroom
When a single species invades an ecosystem or a cyberattack occurs on a power grid, a damaging event occurs. These types of events are always present, but rarely lead to relevant consequences. So how is it that these systems are so stable and resilient that they can withstand such external disturbances? In fact, these systems lack a central design or model, yet exhibit exceptionally reliable functionality.
In the early 1970s, the field of ecology was divided over the question of whether biodiversity is good or bad for an ecosystem. In 1972, Sir Robert May, an Australian scientist who became chief scientific adviser to the British government and president of the Royal Academy, focused on the dynamics of animal populations and the relationship between complexity and stability in natural communities, demonstrating mathematically that an increase in biodiversity leads to greater ecological instability. Furthermore, he suggested that a large ecosystem cannot maintain its stable functionality beyond a certain level of biodiversity and will inevitably collapse at the slightest movement.
May's publication not only contradicts current knowledge and empirical observations of real ecosystems, but overall seems to challenge everything that is known about the networks of interaction in social, technological, and biological systems.
Although May's prediction suggests that all of these systems are unstable, the research team of which URJC researcher Stefano Boccaletti is a part affirms that their experience is directly contradictory because "biology manifests itself through networks of genetic interaction and our brains are based on a complex network of neurons and synapses. Our social and economic systems are powered by social networks, and our technological infrastructure, from the Internet to the electrical grid, are large, complex networks that actually work quite robustly." .
The missing piece of the puzzle
The scientific team has discovered that the missing piece in the puzzle of May's original formulation is that the patterns of interaction in social, biological and technological networks are not random.
“Random networks tend to be quite homogeneous and all the nodes within these networks are approximately the same. For example, the probability that a person has many more friends than average is small. Such networks can be sensitive and unstable. Networks in the real world, on the other hand, are extremely diverse and heterogeneous. These results have been published in the article Emerging stability in complex dynamic networks, in the magazine Nature physics.
During the investigation, the team discovered that this heterogeneity can fundamentally change the behavior of the system. Surprisingly, it actually improves stability. The analysis shows that when a network is large and heterogeneous, it is given a guaranteed stability that is extremely robust against external forces. This explains the fact that most networks, from the Internet to the brain, exhibit extremely resilient functionality despite constant interruptions and obstacles.
“This extreme heterogeneity can be seen in almost all the networks around us, from genetic networks to social and technological networks,” says Boccaletti. “To give an example, imagine having a friend on Twitter who has 10.000 followers, a thousand times the average. In everyday life, with an average height of about two meters, a deviation of a thousand times in height would be equivalent to having a person two kilometers tall, which is obviously impossible. But it is what we observe every day in the context of social, biological and technological networks”.
Large, heterogeneous complex networks can not only be stable, but often have to be. “Discovering the rules that make a large, complex system stable may offer new guidelines for addressing the pressing scientific and policy challenge of designing resilient infrastructure networks that not only protect against viable threats, but also the resilience of critical but fragile ecosystems. .”