Power laws and fragility in flow networks

What makes economic and ecological networks so unlike other highly skewed networks in their tendency toward turbulence and collapse? Here, we explore the consequences of a defining feature of these networks: their nodes are tied together by flow. We show that flow networks tend to the power law degree distribution (PLDD) due to a self-reinforcing process involving position within the global network structure, and thus present the first random graph model for PLDDs that does not depend on a rich-get-richer function of nodal degree. We also show that in contrast to non-flow networks, PLDD flow networks are dramatically more vulnerable to catastrophic failure than non-PLDD flow networks, a finding with potential explanatory power in our age of resource- and financial-interdependence and turbulence.

► We show how dependence on position gives flow networks have an intrinsic tendency to skewed degree distributions.
► Flow networks have an intrinsic tendency to collapse when in a power-law degree distribution.
► We present the first non-rich-get-richer algorithm to explain power law degree distributions.