An ecosystem is overrun by a single species, which leads to its demise. A severe malfunction is brought on by a cyberattack on the electrical supply. Even though we think about these kinds of things all the time, they rarely have such profound effects.
So how are these systems able to resist such external perturbations while being so steady and resilient?
These systems do, in fact, lack a centralised design or plan, but they still display incredibly dependable operation.
Ecology experts disagreed on whether biodiversity was beneficial or detrimental to an environment in the early 1970s. Sir Robert May demonstrated in 1972 using mathematics that a rise in biodiversity reduces ecological stability.
Therefore, a big ecological system will surely collapse in the face of even the slightest twitch and cannot maintain its stable functionality beyond a certain degree of biodiversity.
In addition to contradicting current knowledge and empirical observations of actual ecosystems, May’s conclusion also appears to go against all that is generally accepted about the interaction networks that exist in social, technical, and biological systems.
All of these systems appear to be unstable according to May’s forecast, but our reality is in stark contrast. Our biology is based on networks of genetic interactions, our brain functions on a complex web of synapses and neuron connections, our social and economic systems are fueled by social networks, and our technological infrastructure—from the Internet to the power grid—is made up of enormous, complex networks that actually work.
When May realised how inadequate his answer was, he pondered, “What then are nature’s cunning strategies to ensure the stability of complex networks?” The diversity-stability conundrum, as it is known in the area, has perplexed scientists for more than 50 years.
Researchers from Bar-Ilan University in Israel have answered this conundrum by providing, for the first time, a basic solution to this nagging dilemma in a report published today (April 20, 2023) in the journal Nature Physics.
The researchers discovered that the fact that the patterns of interaction in social, biological, and technical networks are substantially non-random is the crucial missing component in May’s original formulation. The nodes in random networks are typically quite homogeneous and similar to one another. For instance, there is very little chance that one person will have far more friends than is typical. These networks could be unreliable and sensitive. On the other hand, real-world networks are incredibly varied and heterogeneous. They combine average, often sparsely connected nodes with hubs, which may contain ten, one hundred, or more linkages.
The Bar-Ilan team’s calculations revealed that this heterogeneity can significantly change the system’s behaviour. Surprisingly, it really makes stability better. According to the analysis, when a network is big and heterogeneous, it develops a guaranteed stability that is incredibly resistant to outside factors. This explains why most networks in our environment, including the Internet and the brain, function in a highly resilient manner in spite of ongoing disruptions and impediments.
“This extreme heterogeneity can be seen in almost all networks around us, from genetic networks, to social and technological networks,” says Prof. Barzel, of Bar-Ilan University’s Department of Mathematics and Gonda (Goldschmied) Multidisciplinary Brain Research Center, the study’s lead author.
“To put this in context, consider your friend on Twitter who has 10,000 followers, a thousand times the average. In everyday terms, if the average person is roughly two meters tall, such thousand-fold deviation would be tantamount to meeting a two kilometer tall individual, which is obviously impossible. But it is what we observe every day in the context of social, biological and technological networks,” adds Barzel in explaining the strong link between abstract mathematical analysis and seemingly simple, everyday phenomena.
Not only are large and heterogeneous complex networks capable of stability, but stability is frequently required of them. The urgent scientific and policymaking challenge of creating stable infrastructure networks that can not only protect against real threats but also boost the resilience of vital, yet fragile ecosystems can be addressed by understanding the principles that keep a large complex system stable.
